U.S. patent application number 15/205345 was filed with the patent office on 2017-10-12 for compressor diagnostics for a modular outdoor refrigeration system.
The applicant listed for this patent is Heatcraft Refrigeration Products LLC. Invention is credited to Jonathan Douglas, Umesh Gokhale.
Application Number | 20170292742 15/205345 |
Document ID | / |
Family ID | 59998057 |
Filed Date | 2017-10-12 |
United States Patent
Application |
20170292742 |
Kind Code |
A1 |
Douglas; Jonathan ; et
al. |
October 12, 2017 |
COMPRESSOR DIAGNOSTICS FOR A MODULAR OUTDOOR REFRIGERATION
SYSTEM
Abstract
A refrigeration system includes a compressor, one or more
sensors, and a controller. The one or more sensors are operable to
sense data associated with the operation of the refrigeration
system. The controller is operable to receive the data associated
with the operation of the refrigeration system from the one or more
sensors, determine an ideal output value of the compressor based at
least on data associated with the operation of the refrigeration
system, and determine, based at least on the data associated with
the operation of the refrigeration system and the ideal output
variable, that the performance of the compressor is abnormal.
Inventors: |
Douglas; Jonathan;
(Lewisville, TX) ; Gokhale; Umesh; (Irving,
TX) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Heatcraft Refrigeration Products LLC |
Stone Mountain |
GA |
US |
|
|
Family ID: |
59998057 |
Appl. No.: |
15/205345 |
Filed: |
July 8, 2016 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
62318889 |
Apr 6, 2016 |
|
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|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
F25B 2400/06 20130101;
F25B 2700/21151 20130101; F24F 11/70 20180101; F25B 5/02 20130101;
F24F 11/62 20180101; F25B 2700/13 20130101; F25B 2700/1933
20130101; F24F 11/30 20180101; F25B 13/00 20130101; F25B 49/02
20130101; F25B 2500/19 20130101; F25B 2600/02 20130101; F25B
2600/11 20130101; G05B 15/02 20130101; F25B 2600/025 20130101; F24F
2140/50 20180101; F25B 2700/2116 20130101; F25B 2700/21163
20130101; F25B 2700/2106 20130101; F25D 29/003 20130101; F25B
2700/195 20130101; F24F 11/46 20180101; F25B 2600/2515 20130101;
F25B 2600/024 20130101; F25B 2700/15 20130101; F24F 2140/60
20180101; F25D 17/045 20130101; F25B 2700/21152 20130101; F24F
11/64 20180101; F25B 49/022 20130101; F25B 2700/1931 20130101; F24F
2110/00 20180101; F25B 2700/151 20130101; F25B 2700/21162 20130101;
F25B 2400/075 20130101 |
International
Class: |
F25B 49/02 20060101
F25B049/02; F25B 13/00 20060101 F25B013/00 |
Claims
1. A refrigeration system comprising: a compressor; one or more
sensors operable to sense a suction pressure, a suction
temperature, a discharge pressure, and an actual current associated
with the compressor; a controller operable to: receive the suction
pressure, the suction temperature, the discharge pressure, and the
actual current sensed by the one or more sensors; calculate a range
of values representing an ideal current for the compressor, the
range of values determined based on the suction pressure, the
suction temperature, and the discharge pressure sensed by the one
or more sensors; and trigger an alarm in response to a
determination that the actual current sensed by the one or more
sensors is outside the calculated range of values representing the
ideal current.
2. A refrigeration system comprising: a compressor; one or more
sensors operable to sense data associated with the operation of the
refrigeration system; a controller operable to: receive the data
associated with the operation of the refrigeration system from the
one or more sensors; determine an ideal output variable of the
compressor based at least on the data associated with the operation
of the refrigeration system; determine, based at least on the data
associated with the operation of the refrigeration system and the
ideal output variable, that the performance of the compressor is
abnormal.
3. The refrigeration system of claim 2, wherein the controller is
further operable to report when the performance of the compressor
is abnormal.
4. The refrigeration system of claim 2, wherein the ideal output
variable is one of: mass flow; power; current; or capacity.
5. The refrigeration system of claim 2, wherein the sensors are
operable to sense: suction temperature of the compressor; suction
pressure of the compressor; discharge pressure of the compressor;
and actual current of the compressor.
6. The refrigeration system of claim 2, wherein: to determine the
ideal output variable of the compressor, the controller is operable
to calculate a range of values associated with the ideal output
variable; and to determine that the performance of the compressor
is abnormal, the controller is operable to determine that a value
associated with the operational data is outside the range of values
associated with the ideal output value.
7. The refrigeration system of claim 2, wherein the controller is
operable to: determine a reserve measurement based on a value
associated with the ideal output variable and a value associated
with the operational data; report when the reserve measurement is
less than a specified value.
8. The refrigeration system of claim 7, wherein the reserve
measurement corresponds to a reserve capacity, the ideal output
variable corresponds to a maximum capacity of the refrigeration
system, and the value associated with the operational data
corresponds to an actual capacity of the refrigeration system.
9. A method for a refrigeration system, comprising: receiving data
associated with the operation of the refrigeration system;
determining an ideal output variable of a compressor based at least
on the data associated with the operation of the refrigeration
system; determining, based at least on the data associated with the
operation of the refrigeration system and the ideal output
variable, that the performance of the compressor is abnormal.
10. The method of claim 9, further comprising: reporting when the
performance of the compressor is abnormal.
11. The method of claim 9, wherein the ideal output variable is one
of: mass flow; power; current; or capacity.
12. The method of claim 9, wherein the data associated with the
operation of the refrigeration system is received from sensors, the
sensors operable to sense: suction temperature of the compressor;
suction pressure of the compressor; discharge pressure of the
compressor; and actual current of the compressor.
13. The method of claim 9, wherein determining a reserve
measurement comprises: calculating a range of values associated
with the ideal output variable; and determining that a value
associated with the operational data is outside the range of values
associated with the ideal output variable.
14. The method of claim 9, further comprising: determining a
reserve measurement based on a value associated with the ideal
output variable and a value associated with the operational data;
and reporting when the reserve measurement is less than a specified
value.
15. The method of claim 14, wherein the reserve measurement
corresponds to a reserve capacity, the ideal output variable
corresponds to a maximum capacity of the refrigeration system, and
the value associated with the operational data corresponds to an
actual capacity of the refrigeration system.
16. A controller for a refrigeration system, the controller
comprising one or more processors and logic encoded in
non-transitory computer readable memory, the logic, when executed
by the one or more processors, operable to: receive data associated
with the operation of the refrigeration system from one or more
sensors; determine an ideal output variable of a compressor based
at least on the data associated with the operation of the
refrigeration system; determine, based at least on the data
associated with the operation of the refrigeration system and the
ideal output variable, that the performance of the compressor is
abnormal; and report when the performance of the compressor is
abnormal.
17. The controller of claim 16, wherein the ideal output variable
is one of: mass flow; power; current; or capacity.
18. The controller of claim 16, wherein the one or more sensors are
operable to sense: suction temperature of the compressor; suction
pressure of the compressor; discharge pressure of the compressor;
and actual current.
19. The controller of claim 16, further operable to: determine the
ideal output variable of the compressor by calculating a range of
values associated with the ideal output variable; and determine
that the performance of the compressor is abnormal by determining
that a value associated with the operational data is outside the
range of values associated with the ideal output variable.
20. The controller of claim 19, further operable to: determine a
reserve measurement based on a value associated with the ideal
output variable and a value associated with the operational data;
and report when the reserve measurement is less than a specified
value.
Description
RELATED APPLICATIONS
[0001] This application claims the benefit of U.S. Provisional
Application No. 62/318,889, filed Apr. 6, 2016 and entitled
"Modular Outdoor Refrigeration System," which is hereby
incorporated by reference in its entirety.
TECHNICAL FIELD
[0002] This disclosure relates generally to a refrigeration system,
specifically compressor diagnostics for a modular outdoor
refrigeration system.
BACKGROUND
[0003] Refrigeration systems can be used to regulate the
environment within an enclosed space. Various types of
refrigeration systems, such as residential and commercial, may be
used to maintain cold temperatures within an enclosed space such as
a refrigerated case. To maintain cold temperatures within
refrigerated cases, refrigeration systems must control the
temperature and pressure of the refrigerant as it moves through the
refrigeration system.
[0004] Each refrigeration system typically includes at least one
controller that directs the operation of the refrigeration system.
The controller can direct the operation of one or more components
of the refrigeration system, such as the condenser and compressors,
to maintain cold temperatures within refrigerated cases.
SUMMARY OF THE DISCLOSURE
[0005] According to one embodiment, a refrigeration system includes
a compressor, one or more sensors, and a controller. The one or
more sensors are operable to sense data associated with the
operation of the refrigeration system. The controller is operable
to receive the data associated with the operation of the
refrigeration system from the one or more sensors, determine an
ideal output value of the compressor based at least on data
associated with the operation of the refrigeration system, and
determine, based at least on the data associated with the operation
of the refrigeration system and the ideal output variable, that the
performance of the compressor is abnormal.
[0006] Certain embodiments may provide one or more technical
advantages. For example, an embodiment of the present disclosure
may result in more efficient operation of refrigeration system. As
another example, an embodiment of the present disclosure may result
in the detection of defective components of the refrigeration
system. Certain embodiments may include none, some, or all of the
above technical advantages. One or more other technical advantages
may be readily apparent to one skilled in the art from the figures,
descriptions, and claims included herein.
BRIEF DESCRIPTION OF THE DRAWINGS
[0007] For a more complete understanding of the present disclosure,
reference is now made to the following description, taken in
conjunction with the accompanying drawings, in which:
[0008] FIG. 1 illustrates an example refrigeration system according
to certain embodiments of the present disclosure.
[0009] FIG. 2 illustrates an example controller of a refrigeration
system, according to certain embodiments of the present
disclosure.
[0010] FIGS. 3A-3D are graphical representations of the
relationships between various components, and power usage thereof,
of the example refrigeration system of FIG. 1, according to certain
embodiments.
[0011] FIG. 4 is a block diagram illustrating an example method of
determining outputs associated with the refrigeration system of
FIG. 1 using a compressor map equation, according to certain
embodiments.
[0012] FIGS. 5A-5B are example graphs illustrating compressor
diagnostics of the refrigeration system of FIG. 1, according to
certain embodiments.
[0013] FIG. 6 is an example graph illustrating an example method of
detecting whether the refrigeration system of FIG. 1 is meeting its
control objective, according to certain embodiments.
[0014] FIG. 7 is an example graph illustrating another method of
detecting whether the refrigeration system of FIG. 1 is meeting its
control objective, according to certain embodiments.
[0015] FIG. 8 is a flow chart illustrating a method of optimizing
power usage in the refrigeration system of FIG. 1, according to one
embodiment of the present disclosure.
[0016] FIG. 9 is a flow chart illustrating a method of optimizing
liquid pressure and temperature in the refrigeration system of FIG.
1, according to one embodiment of the present disclosure.
[0017] FIG. 10 is a flow diagram illustrating an example method of
optimizing compressor staging in the refrigeration system of FIG. 1
according to one embodiment of the present disclosure.
[0018] FIG. 11 is a flow diagram illustrating an example method of
detecting defects or deficiencies in the refrigeration system of
FIG. 1, according to one embodiment of the present disclosure.
[0019] FIG. 12 is a flow diagram illustrating another example
method of detecting defects or deficiencies in the refrigeration
system of FIG. 1, according to one embodiment of the present
disclosure.
[0020] FIG. 13 is a flow diagram illustrating an example method of
detecting whether the refrigeration system of FIG. 1 is meeting its
control objective, according to one embodiment of the present
disclosure.
DETAILED DESCRIPTION
[0021] Embodiments of the present disclosure and its advantages are
best understood by referring to FIGS. 1 through 13 of the drawings,
like numerals being used for like and corresponding parts of the
various drawings.
[0022] A refrigeration system can be used to maintain cool
temperatures within an enclosed space, such as a refrigerated case
for storing food, beverages, etc. This disclosure contemplates a
configuration of a refrigeration system that may provide various
energy-efficient benefits. As an example, certain embodiments
provide for optimizing power usage. As another example, certain
embodiments provide optimal liquid pressure and temperature
settings to a valve controlling an evaporator. As yet another
example, certain embodiments provide optimal compressor staging.
This disclosure also contemplates a refrigeration system that can
detect possible component defects or deficiencies. This disclosure
also contemplates methods of determining whether a refrigeration
system is meeting its control objectives.
[0023] Generally, a refrigeration system 100 includes at least one
compressor 110, a condenser 120, at least one valve 130, and one or
more evaporators 140. Refrigeration system 100 continuously
circulates refrigerant through it to maintain a cold environment
for an enclosed space such as a refrigerated case. Typically,
liquid refrigerant is added to refrigeration system 100, and the
liquid refrigerant changes phases as it undergoes changes in
temperature and pressure as it moves through refrigeration system
100.
[0024] In some embodiments, refrigeration system 100 includes a
compressor 110. Refrigeration system 100 may include any suitable
number of compressors 110. For example, as depicted in FIG. 1,
refrigeration system 100 includes four compressors 110a-d.
Compressors 110 may vary by design. For example, some compressor
designs may be more energy efficient than other compressor designs.
As another example, some compressors may have modular capacity
(i.e., capability to vary capacity). Herein, compressor capacity
may refer to the capacity of refrigerant vapor that a compressor
will displace based on the operating conditions of the compressor.
Compressors may also vary by capacity. For example, compressors
110a and 110b may have a capacity of 18 kBTU/hr and compressors
110c and 110d may have a capacity of 41 kBTU/hr. In such an
example, the refrigeration rack would have a total capacity of 118
kBTU/hr.
[0025] In some embodiments, compressors 110 may include sensors
160. For example, as depicted in FIG. 1, compressors 110 may be
associated with sensor 160b, 160c, and 160e. These compressor
sensors 160 may be operable to sense information about the
compressors 110 such as suction pressure, suction temperature,
discharge pressure and actual current. Because compressors 110 may
vary by design or capacity, the information sensed by each
compressor sensor 160 may be different. For example, sensor 160e of
compressor 110a may sense a first current and sensor 160e of
compressor 110b may sense a second current. This disclosure
recognizes that in some instances, such as when a compressor is not
activated or selected by refrigeration system 100, compressor
sensors 160 may sense a zero value associated with the suction
pressure, suction temperature, discharge pressure and/or
current.
[0026] In some embodiments, refrigeration system 100 includes a
condenser 120. Refrigeration system 100 may include any suitable
number of condensers 120. Condenser 120 may include at least one
heat exchanger and at least one condenser fan 125. In some
embodiments, condenser 120 includes sensors 160. For example,
condenser 120 may include a sensor 160 that is configured to detect
the speed of condenser fan (i.e., 160d).
[0027] In some embodiments, refrigeration system 100 includes a
valve 130. Refrigeration system 100 may include any suitable number
of valves 130. For example, in FIG. 1, refrigeration system 100 has
three valves 130a-c. Generally, valves 130 control the flow of
refrigerant to each evaporator 140. In some embodiments, a single
valve 130 controls the flow to a single evaporator 140. For
example, in FIG. 1, valve 130a controls the refrigerant flow to
evaporator 140a, valve 130b controls the refrigerant flow to
evaporator 140b, and valve 130c controls the refrigerant flow to
evaporator 140c.
[0028] In some embodiments, refrigeration system 100 includes one
or more evaporators 140. Evaporators 140 may be included in any
suitable component of refrigeration system 100 that provides
cooling to an enclosed space. For example, evaporator 140 may be
included in a refrigerated display case, a unit cooler, a walk-in
cooler, a deli case, a unit cooler in a deep freezer, etc.
Refrigeration system 100 may include any suitable number of
evaporators 140. For example, as depicted in FIG. 1, refrigeration
system 100 includes three evaporators 140a-c. Evaporator 140 may be
associated with at least one heat exchanger and at least one fan
145.
[0029] In some embodiments, refrigeration system 100 includes at
least one controller 150 that directs the operations of
refrigeration system 100. Controller 150 may be communicably
coupled to one or more components of refrigeration system 100. For
example, controller 150 may be configured to receive data sensed by
sensors 160. As another example, controller 150 may be configured
to receive data of refrigeration system 100.
[0030] Controller 150 may be configured to provide instructions to
one or more components of refrigeration system 100. Controller 150
may be configured to provide instructions via any appropriate
communications link (e.g., wired or wireless) or analog control
signal. As depicted in FIG. 1, controller 150 is configured to
wirelessly communicate with components of refrigeration system 100.
For example, in response to receiving an instruction from
controller 150, speed of condenser fan 125 may increase or
decrease. As another example, in response to receiving an
instruction from controller 150, compressor 110a may increase
discharge pressure. An example of controller 150 is further
described below with respect to FIG. 2. In some embodiments,
controller 150 includes or is a computer system.
[0031] Some components of refrigeration system 100 may be arranged
on a refrigeration rack on the roof of a building. In some
embodiments, refrigeration rack may include compressors 110 and
condenser 120. In some other embodiments, refrigeration rack may
also include an oil separator 170.
[0032] Refrigeration system 100 may also include one or more
sensors 160. For example, the refrigeration rack may include a
temperature sensor 160 configured to sense data related to outdoor
temperature. As another example, one or more sensors may be
configured to sense data related to liquid temperature and pressure
leaving condenser 120 (e.g., sensor 160a). Sensors 160 may also be
configured to sense data related to suction pressure into
compressor 110 (e.g., sensor 160b), data related to discharge
pressure out of compressor 110 (e.g., sensor 160c), and/or data
related to speed of condenser fan 125 (e.g., sensor 160d). As
another example, a sensor may be configured to sense data related
to current and capacity of compressors 110 (e.g., sensor 160e).
Although this disclosure describes and depicts specific types of
sensors, refrigeration system 100 may include any other type and
any suitable number of sensors 160.
[0033] FIG. 2 illustrates an example controller 150 of
refrigeration system 100, according to certain embodiments of the
present disclosure. Controller 150 may comprise one or more
interfaces 210, memory 220, and one or more processors 230.
Interface 210 receives input (e.g., sensor data or system data),
sends output (e.g., instructions), processes the input and/or
output, and/or performs other suitable operation. Interface 210 may
comprise hardware and/or software.
[0034] Processor 230 may include any suitable combination of
hardware and software implemented in one or more modules to execute
instructions and manipulate data to perform some or all of the
described functions of controller 150. In some embodiments,
processor 230 may include, for example, one or more computers, one
or more central processing units (CPUs), one or more
microprocessors, one or more applications, one or more application
specific integrated circuits (ASICs), one or more field
programmable gate arrays (FPGAs), and/or other logic.
[0035] Memory (or memory unit) 220 stores information. Memory 220
may comprise one or more non-transitory, tangible,
computer-readable, and/or computer-executable storage media.
Examples of memory 220 include computer memory (for example, Random
Access Memory (RAM) or Read Only Memory (ROM)), mass storage media
(for example, a hard disk), removable storage media (for example, a
Compact Disk (CD) or a Digital Video Disk (DVD)), database and/or
network storage (for example, a server), and/or other
computer-readable medium.
[0036] This disclosure recognizes optimizing power usage to improve
the energy efficiency of a refrigeration system. Generally, the
refrigerant supplied to evaporators should be maintained within
pre-determined temperature and pressure ranges. The pre-determined
temperature and pressure ranges are maintained by adjusting the
discharge pressure of the compressors and the condenser fan speed.
In typical refrigeration systems, the condenser fan speed is
adjusted in order to maintain a constant temperature difference
(TD) between the outside air and refrigerant. Commonly, the
standard TD is 15.degree. Fahrenheit (F). In typical refrigeration
systems, the speed of condenser fan is continually adjusted to
maintain the condenser TD, and the discharge pressure of the
compressors is continually adjusted to maintain the refrigerant
supplied to the evaporators within the pre-determined temperature
and pressure ranges. As such, the condenser fan (e.g., fan 125) and
compressors (e.g., compressors 110a-110d) contribute to high power
usage.
[0037] These and other problems of typical refrigeration systems
may be reduced or eliminated by using a refrigeration system that
uses an optimal TD setpoint. The optimal TD setpoint may be
continually adjusted to an optimal setting based on the current
compressor loading conditions and/or outdoor temperature
conditions. As an example, under certain compressor loading
conditions and/or outdoor temperature conditions, it may be more
power efficient to increase the condenser fan speed (thereby
increasing condenser fan power) in order to reduce compressor power
by a greater extent. Under these conditions, the TD setpoint can be
adjusted to cause the condenser fan speed to increase. As another
example, under other compressor loading conditions and/or outdoor
temperature conditions, it may be more power efficient to decrease
the condenser fan speed (thereby reducing fan power) and increase
the compressor discharge pressure. The corresponding increase in
discharge pressure will increase compressor power, but to a lesser
extent than the decrease in fan power. Under these conditions, the
TD setpoint can be adjusted to cause the condenser fan speed to
decrease.
[0038] FIG. 3A illustrates the relationship between compressor
power and discharge pressure. As depicted, discharge pressure
increases as power of compressor 110 increases. In some
embodiments, discharge pressure is measured using sensor 160c. In
some embodiments, power of compressor 110 is measured using sensor
160e.
[0039] FIG. 3B illustrates the relationship between discharge
pressure and condenser fan speed. As depicted, discharge pressure
decreases as speed of condenser fan increases. In some embodiments,
speed of condenser fan 125 is measured using sensor 160d.
[0040] FIG. 3C illustrates the relationship between power of
condenser fan and speed of condenser fan. As depicted, power of
condenser fan increases as the speed of condenser fan increases. In
some embodiments, power of condenser fan is measured using sensor
160d.
[0041] Based on data from FIGS. 3A-3C, FIG. 3D may be constructed
to represent the relationship between total power usage of
refrigeration system 100 and speed of condenser fan 125. As
depicted, total power of refrigeration system 100 is high when the
speed of condenser fan is low (i.e., when compressor 110 is
discharging refrigerant at high pressures). On the other hand,
total power of refrigeration system 100 is also high when the speed
of condenser fan is high. FIG. 3D illustrates that the most
efficient operation of refrigeration system 100 occurs when the
compressors 110 and condenser fan 125 operate jointly. As such,
this disclosure recognizes using an optimal TD setpoint that
maximizes the efficiency of compressors 110 and condenser fan 125.
As depicted in FIG. 3D, maximum power efficiency of refrigeration
system 100 is achieved at optimal TD setpoint 310.
[0042] In some embodiments, the optimal TD setpoint is calculated
by controller 150. The optimal TD setpoint may vary based on the
temperature of the environment (e.g., outdoor temperature). The
optimal TD setpoint may also vary based on rack loading. This
disclosure recognizes that certain benefits may result by achieving
the optimal TD setpoint when the increase in fan power is less than
the decrease in compressor power, or alternatively, when the
increase in compressor power is less than the decrease in fan
power.
[0043] In some embodiments, controller 150 of refrigeration system
100 calculates the optimal TD setpoint. Optimal TD setpoint values
may be calculated as a function of outdoor temperature and
compressor loading. Because the optimal TD setpoint is dependent on
outdoor temperature and compressor loading, the optimal TD setpoint
may change over time. In some embodiments, optimal TD setpoints can
be predetermined by the manufacturer and uploaded to memory 220 of
controller 150 of refrigeration system 100.
[0044] In other embodiments, controller 150 adjusts settings as it
operates thereby creating feedback regarding total power usage. For
example, controller 150 may create a new setting wherein it
increases the speed of condenser fan 125 resulting in an increase
in power to condenser fan 125. If this increase in power to
condenser fan 125 results in a significant decrease in power to
compressor(s) 110, the total power consumption of refrigeration
system 100 may be reduced. Speed of condenser fan 125 may be
measured by sensor 160d and discharge pressure of compressor 110
may be measured by sensor 160c. If this new setting results in
lower power consumption, the new setting may be saved to memory 220
of controller 150. In some embodiments, controller 150 may override
an optimal TD setpoint preloaded by the manufacturer.
[0045] FIG. 8 is directed to a method of optimizing power usage in
a refrigeration system. The refrigeration system may be
refrigeration system 100 of FIG. 1. A controller such as described
with respect to FIG. 1 or 2 may be used to perform the method of
FIG. 8. The method of FIG. 8 may represent an algorithm that is
stored on computer readable medium, such as a memory of a
controller (e.g., the memory 220 of FIG. 2).
[0046] Turning now to FIG. 8, the method 800 begins at step 805. At
step 810, the refrigeration system receives a temperature
difference (TD) setpoint indicating a desired temperature
difference between outside air and refrigerant. For example, the TD
setpoint may be received from memory 220 of controller 150. In some
embodiments, the method 800 continues to step 820.
[0047] At step 820, the refrigeration system modifies the TD
setpoint based on conditions currently being experienced by the
system. In some embodiments, the conditions being experienced by
the refrigeration system may comprise an outdoor temperature and/or
the loading conditions of the compressor. For example, the
conditions may be determined based on information received from
sensors 160. The modified TD setpoint may be selected to cause a
decrease in total power consumption of the refrigeration system.
Total power consumption may comprise the power consumed by a
compressor to yield a discharge pressure and the power consumed by
a condenser fan to operate a fan speed. In some embodiments,
modifying the TD setpoint causes the power consumed by the
compressor to decrease more than the power consumed by the
condenser fan increases. In other embodiments, modifying the TD
setpoint causes the power consumed by the condenser fan to decrease
more than the power consumed by the compressor increases. As such,
in some embodiments, modifying the setpoint results in a decrease
in the system power consumption. In some embodiments, the method
continues to step 830.
[0048] At a decision step 830, the refrigeration system determines
whether the total power consumption associated with the modified TD
setpoint is lower than the total power consumption associated with
the original TD setpoint. If the refrigeration system determines
that the total power consumption associated with the modified TD
setpoint is greater than the total power consumption associated
with the original TD setpoint, the method 800 may continue to end
step 845. Alternatively, if the refrigeration system determines
that the total power consumption associated with the modified TD
setpoint is lower than the total power consumption associated with
the original TD setpoint, the method 800 may continue to step
840.
[0049] At step 840, the refrigeration system saves the modified TD
setpoint as an optimal TD setpoint for the conditions currently
being experienced by the refrigeration system in response to
feedback indicating that the modified TD setpoint caused the total
power consumption to decrease. For example, in response to
determining that the modified TD setpoint resulted in a decrease in
total power consumption of the refrigeration system, the
refrigeration system may save the modified TD setpoint for future
use when the conditions experienced by the refrigeration system
reoccur. In some embodiments, the method continues to end step
845.
[0050] This disclosure also recognizes improving the energy
efficiency of a refrigeration system by optimizing the liquid
temperature and pressure of the refrigerant circulating through the
refrigeration system. In most conventional refrigeration systems,
the liquid outlet temperature from the refrigeration rack is
controlled to a constant temperature even though the refrigeration
rack may be capable of running lower temperatures. This disclosure
recognizes that running lower temperatures through the
refrigeration rack may provide various benefits such as improving
the energy efficiency of the refrigeration rack. Typically,
conventional refrigeration systems do not run lower temperatures
through the refrigeration rack because adjusting the liquid outlet
temperature may interfere with the position of the valve, thereby
causing unstable operation of the refrigeration system. This
disclosure contemplates a configuration of a refrigeration system
that may provide optimal liquid pressure and temperature settings
to a valve controlling an evaporator.
[0051] Generally, the liquid outlet temperature from the
refrigeration rack is controlled to a constant temperature (e.g.,
50.degree. F.) even though efficiency of the refrigeration rack may
be improved by running lower temperatures. As described above,
lower temperatures are generally not run because lowering the
liquid temperature interferes with operation of valve 130. For
example, decreasing the temperature of the refrigerant causes an
increase in enthalpy change which in turn decreases the mass flow
required by evaporator(s) 140 and causes valve(s) 130 to close.
Valves 130 operating near the fully closed position may cause
unstable operation of refrigeration system 100. Accordingly, there
is a need for a refrigeration system that permits refrigerant to be
run through refrigeration system 100 at a lower temperature without
interfering with the operation of valve 130. Such a system may be
associated with various energy-efficient benefits.
[0052] This disclosure recognizes that maintaining the enthalpy of
refrigeration system 100 holds valve 130 in a constant position
(i.e., does not interfere with the operation of valve 130). This
disclosure also recognizes that decreasing liquid pressure results
in a decrease in pressure difference across valve 130 which in turn
decreases the actual mass flow and causes valve 130 to open to
increase the flow to the required mass flow. Thus, this disclosure
recognizes controlling the liquid temperature and liquid pressure
to maintain the enthalpy of refrigeration system 100.
[0053] In some embodiments, refrigeration system 100 uses an
optimal liquid setting. The optimal liquid setting may be a
function of both the temperature and pressure of the liquid
refrigerant. In some embodiments, the optimal liquid setting
maintains the enthalpy of refrigeration system 100. For example,
valve 130 is in position one when liquid outlet temperature is
50.degree. F. and liquid outlet pressure is 104 pounds per square
inch (PSI). In some embodiments, liquid outlet temperature and
liquid outlet pressure is measured by sensor 160a. In other
embodiments, liquid outlet temperature and liquid outlet pressure
are measured using any other suitable means.
[0054] To maintain valve 130 in the same position, the temperature
and pressure of liquid refrigerant are adjusted simultaneously. In
some embodiments, the temperature and pressure are adjusted by
substantially the same proportion. For example, valve 130 remains
in position one when liquid outlet temperature is 40.degree. F. and
liquid outlet pressure is 90 PSI. In some embodiments, the optimal
liquid setting may improve the efficiency of refrigeration system
100.
[0055] In some embodiments, controller 150 operates refrigeration
system 100 using an optimal liquid setting. Because the optimal
liquid setting is dependent on temperature (e.g., the outdoor
temperature), the optimal liquid setting may change over time. In
some embodiments, optimal liquid settings corresponding to each
temperature can be predetermined by the manufacturer and uploaded
to controller 150 of refrigeration system 100. For example,
controller 150 may be preloaded with information from TABLE 1
below:
TABLE-US-00001 TABLE 1 Optimal Liquid Refrigerant Refrigerant
Setting Temperature Pressure 1 50.degree. F. 104 PSI 2 40.degree.
F. 90 PSI 3 32.degree. F. 80 PSI
[0056] In some embodiments, controller 150 may be configured to
adjust liquid outlet temperature and pressure of refrigeration
system 100 using feedback. For example, in response to receiving a
sensed outdoor temperature, controller 150 may adjust the liquid
outlet temperature and pressure values. If this new setting results
in higher efficiency of refrigeration system 100, the new setting
may be saved to memory 220 of controller 150. Controller 150 may be
configured to run refrigeration system 100 using the optimal liquid
setting that results in the highest efficiency of refrigeration
system 100.
[0057] FIG. 9 is directed to a method of optimizing liquid pressure
and temperature in a refrigeration system. The refrigeration system
may be refrigeration system 100 of FIG. 1. A controller such as
described with respect to FIG. 1 or 2 may be used to perform the
method of FIG. 9. The method of FIG. 9 may represent algorithms
that are stored on computer readable medium, such as a memory of a
controller (e.g., the memory 220 of FIG. 2).
[0058] Turning now to FIG. 9, the method 900 begins at step 905. At
step 910, the refrigeration system receives a liquid setting. The
liquid setting may comprise the temperature and pressure at which
refrigerant flows through a valve (e.g., valve 130). In some
embodiments, the temperature and pressure of the refrigerant is
sensed by sensors 160. For example, the temperature and pressure of
the refrigerant may be sensed by sensor 160a. In some embodiments,
the method 900 continues to step 920.
[0059] At step 920, the refrigeration system adjusts the liquid
setting to an adjusted liquid setting. The adjusted liquid setting
may comprise a temperature and a pressure that improves the energy
efficiency under conditions currently being experienced by the
refrigeration system. In some embodiments, the conditions being
experienced by the refrigeration system comprise an outdoor
temperature. In some embodiments, the conditions may be determined
based on information from sensors 160. The pressure associated with
the adjusted liquid setting may be selected such that the valve
maintains its same amount of openness. For example, the
refrigeration system may select a pressure that maintains the same
valve position when the temperature associated with the adjusted
liquid setting is lower than the temperature associated with the
original liquid setting. The temperature and pressure of the
refrigerant may be adjusted simultaneously to ensure that the
adjustment does not interfere with operation of the valve. The
temperature and pressure of the refrigerant may be adjusted by
substantially the same proportion to ensure that the adjustment
does not interfere with operation of the valve. In some
embodiments, the method 900 continues to step 930.
[0060] At a decision step 930, the refrigeration system determines
whether the adjusted liquid setting is more energy efficient than
the original liquid setting. In some embodiments, the refrigeration
system makes such a determination based on feedback. If the
refrigeration system determines that the adjusted liquid setting is
more energy efficient than the original liquid setting, the method
may continue to step 935. Alternatively, if the refrigeration
system determines that the original liquid setting is more energy
efficient than the adjusted liquid setting, the method may continue
to an end step 945. At step 935, the refrigeration system saves the
adjusted liquid setting as an optimal liquid setting for the
conditions currently being experienced by the refrigeration system.
In some embodiments, after saving the adjusted liquid setting as
the optimal liquid setting, the method 900 may continue to end step
940.
[0061] In some embodiments, the method 900 may include one or more
additional steps. For example, in some embodiments, the
refrigeration system may monitor feedback indicating the energy
efficiency associated with each of a plurality of liquid settings
that have been applied under the conditions currently being
experienced by the refrigeration system. As another example, in
some embodiments, the refrigeration system may save the most energy
efficient of the plurality of liquid settings as an optimal liquid
setting for the conditions currently being experienced by the
refrigeration system.
[0062] This disclosure also recognizes optimizing compressor
staging in a refrigeration system to improve energy efficiency.
Traditionally, compressors are operated in stages such that each
compressor is operated to its maximum capacity before another
compressor is operated. Although this traditional staging may be
sufficient to maintain cool temperatures in the enclosed space, it
does not account for energy efficiency. In most conventional
refrigeration systems, compressors are configured to operate in
stages as the system load increases (i.e., compressors are
configured to operate sequentially to their maximum capacity). For
example, if refrigeration system 100 includes four compressors
(e.g., 110a, 110b, 110c, and 110d), each having a maximum capacity
of 18 kBTU/hr, and the system load is 24 kBTU/hr, system 100 may
operate 110a to its maximum capacity (i.e., 18 kBTU/hr) and then
operate 110b to achieve the remainder of the load (i.e., 6
kBTU/hr). However, this traditional operation of refrigeration
system 100 does not account for efficiency. For example,
compressors 110a and 110b may not be the most efficient combination
of compressors to meet the system load. Accordingly there is a need
for a refrigeration system operable to determine the most efficient
combination of compressors to meet the load.
[0063] In some embodiments, refrigeration system 100 may determine
the most efficient combination of compressors 110 to meet the
system load. Refrigeration system 100 may be configured to receive
information associated with the system load and information
associated with compressors 110. In some embodiments, refrigeration
system 100 receives this information from sensors (e.g., 160e).
[0064] In some embodiments, controller 150 uses the system load and
compressor information to determine the most efficient combination
of compressors 110. For example, in some embodiments, system 100
may determine that compressors 110 operate most efficiently when
the 24 kBTU/hr system load is distributed equally between
compressors 110a, 110b, 110c, and 110d. In other embodiments,
system 100 may determine that compressors 110 operate most
efficiently when the 24 kBTU/hr system load is distributed to the
most efficiently operating compressors (e.g., 110a and 110d). In
other embodiments, system 100 may determine that compressors 110
operate most efficiently when the 24 kBTU/hr system load is
distributed to as follows: 18 kBTU/hr to 110a, 3 kBTU/hr to 110b,
and 3 kBTU/hr to 110c. Although this disclosure describes specific
variations of compressor 110 combinations, this disclosure
contemplates any combination of compressors 110 that results in
increased energy efficiency.
[0065] Information associated with compressors may include data
regarding model name, model number, total capacity, efficiency,
portability, drive system, type (e.g., modular, reciprocating,
screw, rotary, centrifugal). Although specific types of information
associated with compressors has been described, this disclosure
contemplates controller 150 may use any information associated with
compressors 110 that results in determining the most efficient
combination of compressors 110. In some embodiments, information
associated with compressors 110 may be loaded into memory 220 of
controller 150. For example, manufacturer may upload information
regarding compressor models in memory 220 of controller 150. In
other embodiments, controller 150 is configured to identify
information associated with compressors (e.g., using sensors
160).
[0066] In some embodiments, controller 150 uses a data map to
determine the most efficient combination of compressors. In some
embodiments, data map is predetermined by manufacturer based on
information associated with compressors 110. Data map may provide
information to controller 150 that permits controller 150 to
determine which compressors 110 to operate at any given time. In
some embodiments, data map may be uploaded to memory 220 of
controller 150 by manufacturer.
[0067] In some embodiments, data map may be edited or updated. For
example, data map may be updated to reflect that compressor 110a is
operating below performance expectations. In some embodiments,
controller 150 updates data map based on its identification of
changes to compressors 110 (e.g., using sensors 160). In other
embodiments, memory 220 of controller 150 is manually updated to
reflect such changes.
[0068] In some embodiments, controller 150 uses feedback to
determine the most efficient operation of compressors 110. In doing
such, controller 150 may operate compressors 110 in various
combinations and measure efficiency levels at each combination. If
a particular combination of compressors 110 results in increased
efficiency, controller 150 may save this combination setting into
memory 220 for future use.
[0069] An advantage of certain embodiments may allow for deploying
new refrigeration systems in a cost effective manner. For example,
energy efficient compressors tend to be more expensive to purchase
but less expensive to operate than energy inefficient compressors.
Refrigeration system 100 could be planned to include a sufficient
number of energy efficient compressors to handle the typical
demand. Refrigeration system 100 could further include additional
inefficient compressors that would not be needed to handle the
typical demand, but could be used to provide extra capacity in the
event that demand is unusually high. The optimized compressor
staging may be configured so that the most efficient compressors
are used first and the less efficient compressors are rarely used
(e.g., only in the event that the efficient compressors cannot meet
the demand on their own).
[0070] FIG. 10 is directed to a method of optimizing compressor
staging in a refrigeration system. The refrigeration system can be
the refrigeration system of FIG. 1. A controller such as described
with respect to FIG. 1 or 2 may be used to perform the method of
FIG. 10. The method of FIG. 10 may represent an algorithm that is
stored on a computer readable medium, such as a memory of a
controller (e.g., the memory 220 of FIG. 2).
[0071] The method 1000 begins at step 1005. At step 1010, the
refrigeration system receives information associated with a load of
the refrigeration system. In some embodiments, the refrigeration
system receives this information from sensors 160 configured to
detect load information. For example, one or more sensors 160 of
the refrigeration system 100 may detect that the system load is 24
kBTU/hr. The method 1000 may then continue to step 1020.
[0072] At step 1020, the refrigeration system receives information
associated with the compressors. The information associated with
the compressors may comprise one of: model name, model number,
total capacity, compressor efficiency, portability, drive system,
and/or compressor type. In some embodiments, the information
associated with the compressors may be received from one or more
sensors 160 of the refrigeration system. In some embodiments, the
information associated with the compressors may be loaded into
memory 220 of controller 150. For example, a data map corresponding
to a particular compressor 110 may be uploaded to the memory 220 of
the controller 150. The data map may be predetermined by the
compressor manufacturer based on information associated with the
compressor. In some embodiments, the method 1000 may continue to
step 1030.
[0073] At step 1030, the refrigeration system determines, based on
the information associated with the compressors, a first efficiency
value associated with allocating the load among one or more of the
compressors according to a first compressor staging. In some
embodiments, the first efficiency value is determined using a data
map. The data map may comprise one or more equations used to
calculate the efficiency of a compressor 110. For example, based on
known and measured properties of a compressor 110, the
refrigeration system may calculate the efficiency of the compressor
to be 70%. In some embodiments, the calculated efficiency value may
be associated with the operation of the compressor according to a
first compressor staging.
[0074] In other embodiments, the first efficiency value corresponds
to a saved value determined from feedback obtained during previous
operation of the compressors according to the first compressor
staging. For example, the first compressor staging may include
distributing a 24 kBTU/hr load to compressors 110a and 110b. The
refrigeration system may determine that the first efficiency value
associated with this compressor staging is 70%. The refrigeration
system may then save the determined efficiency value to memory. In
a subsequent operation of the refrigeration system, the
refrigeration system may determine that it is operating according
to the first compressor staging (e.g., distributing a 24 kBTU/hr
load to compressors 110a and 110b) and receive the first efficiency
value (i.e., 70%) from memory. Thus, the refrigeration system may
determine that the overall system efficiency is 70% when the
compressors distribute the system load according to the first
compressor staging. In some embodiments, the method 1000 may
continue to step 1040.
[0075] At step 1040, the refrigeration system determines, based on
information associated with the compressors, a second efficiency
value associated with allocating the load among one or more the
compressors according to a second compressor staging. For example,
the refrigeration system may determine that the overall system
efficiency is 85% when the compressors distribute the system load
according to the second compressor staging. The second efficiency
value may be determined similarly to the first efficiency value.
For example, in some embodiments, the second efficiency value may
be determined using a data map. In other embodiments, the second
efficiency value may be determined using a saved value determined
from feedback obtained during a previous operation of the
refrigeration system. In some embodiments, the method 1000
continues to step 1050.
[0076] At step 1050, the refrigeration system determines whether
the efficiency value of the first compressor staging (also referred
to as the first efficiency value) is more efficient than the
efficiency value of the second compressor staging (also referred to
as the second efficiency value). In some embodiments, determining
whether the efficiency value of the first compressor staging is
more efficient than the efficiency value of the second compressor
staging is based on a comparison of the first and second efficiency
values. For example, the refrigeration system may determine that
second efficiency value is more efficient than the first efficiency
value when the efficiency value of the first compressor staging is
70% and the efficiency value of the second compressor staging is
85%. In response to determining which compressor staging is more
efficient, refrigeration system may operate the compressors
accordingly at step 1060.
[0077] At step 1060, refrigeration system operates the compressors
based on the more efficient compressor staging determined in step
1050. In some embodiments, refrigeration system may operate the
compressors with the load allocated according to the first
compressor staging if the first efficiency value is more efficient
than the second efficiency value (see e.g., step 1060a). In other
embodiments, refrigeration system may operate the load allocated
according to the second compressor staging if the second efficiency
value is more efficient than the first efficiency value (see e.g.,
step 1060b). As depicted in FIG. 10, the refrigeration system
continues from step 1050 to either step 1060a or 1060b. At step
1060a, the refrigeration system operates according to the first
compressor staging when the first efficiency value is determined to
be more efficient than the second efficiency value. Alternatively,
at step 1060b, the refrigeration system operates according to the
second compressor staging when the second efficiency value is
determined to be more efficient than the first efficiency value. In
some embodiments, the method 1000 may continue to an end step
1065.
[0078] In other embodiments, the method 1000 may comprise one or
more additional steps. For example, it may be beneficial for the
refrigeration system to recalibrate after detecting a change in the
refrigeration system. Thus, the method 1000 may further include
updating the data map in response to identifying a change to one or
more of the compressors 110. For example, refrigeration system 100
may identify that compressor 110a has stopped working. In response,
refrigeration system 100 may update the data map to reflect that
compressor 110a has stopped working so that the system load may be
allocated, based on efficiency, to the remaining three operable
compressors (e.g., compressors 110b-d). In this manner,
refrigeration system 100 operates its operable compressors 110b-d
at (adjusted) maximum efficiency by staging the compressors
accordingly.
[0079] In some embodiments, the refrigeration system may use
feedback to determine the most efficient combination of
compressors. In such an embodiment, the refrigeration system may
operate the compressors in a plurality of combinations, measure the
efficiency of the refrigeration system for each combination, and
save a particular combination in response to determining that the
refrigeration system is operating more efficiently than the other
combinations. For example, the refrigeration system may operate the
compressors in various combinations (e.g., combination one:
compressors 110a, 110c; combination two: compressors 110a, 110b,
110d; combination three: compressors 110a, 110b, 110c, 110d). At
each combination, the refrigeration system may measure the
efficiency (e.g., combination one: 72%; combination two: 68%;
combination three: 78%). In response to determining that the
refrigeration system is operating more efficiently given a
particular combination than at other combinations, the
refrigeration system may save the particular combination (e.g.,
refrigeration system may save combination three to memory because
it yields the most efficient combination (78%) of the three
combinations).
[0080] This disclosure also recognizes improving the efficiency of
a refrigeration system by performing compressor diagnostics.
Generally, to maintain such cool temperatures, refrigeration
systems typically include one or more compressors configured to
compress refrigerant running through the refrigeration system.
Because compressors play a vital role in maintaining a cool
environment, compressor reliability may be of concern to both
manufacturers and owners of refrigeration systems. For example, a
defective compressor in a grocery store may lead to costs
associated with repairing or replacing the defective compressor, or
in worse cases, to food spoilage, damages liability, and lost
profits. Thus, this disclosure recognizes that an owner of a
refrigeration system may benefit from early detection of compressor
defects. Accordingly, there exists a need for a refrigeration
system that is configured to detect possible deficiencies or
defects of compressors by performing diagnostics.
[0081] Manufacturers of refrigeration systems typically provide
compressor maps associated with their compressor models. A
compressor map typically includes data and equations associated
with a particular compressor model. This disclosure recognizes
using the information from compressor maps in an analytics routine
to determine when compressors 110 may be under or over-performing.
For example, as depicted in FIG. 4, a compressor map equation may
be used to calculate mass flow, power, and current of compressor
110 by inputting refrigeration system information (e.g., suction
pressure, suction temperature, and discharge pressure). Such
refrigeration system information may be received by refrigeration
system 100. For example, refrigeration system 100 may receive
refrigeration system information using a plurality of sensors 160.
Sensors 160 may be configured to sense data related to suction
temperature, suction pressure, discharge pressure, current, and
capacity of compressors 110.
[0082] In some embodiments, controller 150 is configured to detect
deficiencies in compressor 110 using values associated with a
compressor current. For example, as depicted in FIGS. 5A and 5B,
based on inputting values associated with suction temperature,
suction pressure, and discharge pressure, controller 150 may
calculate a range of values representing the "ideal" current 510 of
compressor 110. As shown in FIGS. 5A and 5B, current fluctuates
throughout the day, for example, depending on the outdoor
temperature. In the abstract, it may be difficult to determine
whether the fluctuation is good or bad. Certain embodiments may
allow for determining whether such a fluctuation is good or
bad.
[0083] As one example, example, controller 150 may compare the
actual current measurement 520 (sensed by current sensor 160) to
the "ideal" current range 510. In some embodiments, detection of an
actual value 520 inside the "ideal" range 510 may indicate that
compressor 110 is in good operating condition (e.g., FIG. 5A).
Detection of an actual value 520 outside of the "ideal" range 510
may indicate that compressor 110 is deficient and/or defective
(e.g., FIG. 5B). In some embodiments, refrigeration system 100 is
configured to trigger an alarm if the actual current measurement
520 is outside of the "ideal" current range 510 (i.e., if
controller 150 detects a possible deficiency).
[0084] As another example, controller 150 may determine whether a
fluctuation is good or bad by analyzing the trend of the delta
between actual current and ideal current. For example, controller
150 may determine that a fluctuation is good when the trend of the
delta becomes smaller over time. On the other hand, controller 150
may determine that a fluctuation is bad when the trend of the delta
becomes greater over time. In some embodiments, controller 150 may
trigger an alarm if the trend of the delta increases for a
specified period of time (i.e., indicating a possible defect or
deficiency).
[0085] In some embodiments, the ideal range 510 may comprise more
than one value (e.g., a low value corresponding to the minimum
value of the ideal range and a high value corresponding to the
maximum value of the ideal range). In other embodiments, the ideal
range 510 may be a single value associated with a deviation band.
For example, controller 150 may calculate an ideal maximum capacity
range of 15 kBTU/hr with a 3.sigma. standard deviation band. In
some embodiments, deviation bands may be pre-programmed into memory
220 of controller 150. In other embodiments, deviation bands may be
learned by controller 150 through operation of HVAC system 100.
[0086] In some embodiments, the ideal range 510 is fixed. In other
embodiments, the ideal range 510 may be variable. For example, the
ideal range 510 may be changed remotely (e.g., via an update from
the manufacturer). As another example, the ideal range 510 may be
changed by the operator of the HVAC system 100. This disclosure
recognizes that the ideal range 510 may be adjusted to be broader
or narrower. In some embodiments, the ideal range 510 is adjusted
based on operator preferences. In other embodiments, the ideal
range 510 is adjusted based on sensitivity of the algorithm.
[0087] A similar method could be used to compare actual power to
ideal power. Alternatively, current may be used as a proxy for
power due to the relationship between current and power (e.g.,
P=IV).
[0088] In other embodiments, controller 150 is configured to detect
deficiencies in compressor 110 using values associated with
capacity. For example, based on inputting values associated with
suction temperature, suction pressure, and discharge pressure,
controller 150 may calculate a range of values representing the
"ideal" capacity of compressor 110. Controller 150 may then compare
the actual capacity measurement (sensed by capacity sensor) to the
"ideal" capacity range. Detection of an actual capacity measurement
outside of the "ideal" capacity range may indicate that compressor
110 is deficient and/or defective. In some embodiments,
refrigeration system 100 is configured to trigger an alarm if the
actual capacity measurement is outside of the "ideal" capacity
range (i.e., if controller detects a possible deficiency).
[0089] In some embodiments, refrigeration system 100 may be
configured to trigger an alarm indicating a deficiency based on a
reserve measurement. As used herein, reserve measurement refers to
the difference between a value associated with the ideal input
variable and the actual measured value sensed by sensor. In some
embodiments, the value associated with the ideal input variable may
be the maximum value of the calculated "ideal" range. In other
embodiments, the reserve measurement may be calculated using the
minimum value of the calculated "ideal" range. As an example,
refrigeration system 100 may be configured to monitor capacity of
compressor 110 and trigger an alarm if the amount of capacity in
reserve is less than a threshold.
[0090] For example, controller 150 may calculate an "ideal" maximum
capacity value (using the inputs and compressor map equation
discussed above) to be 18 kBTU/hr and receive an actual measurement
of capacity from capacity sensor of 12 kBTU/hr. In such example,
the reserve measurement would be 6 kBTU/hr if calculated using the
maximum value of the "ideal" range.
[0091] Controller 150 may be configured to trigger an alarm
indicating deficiency if the reserve measurement is less than a
specified value. For example, controller 150 may be configured to
trigger an alarm if the reserve measurement is less than 4 kBTU/hr.
Because the reserve measurement in the above example (6 kBTU/hr) is
greater than the specified value (4 kBTU/hr), controller 150 will
not trigger an alarm. However, if the reserve capacity is 2 kBTU/hr
which is less than the 4 kBTU/hr threshold, an alarm will be
triggered indicating that there may be a defect with compressor 110
and/or that additional capacity may be required.
[0092] FIGS. 11 and 12 are directed to methods of detecting defects
or deficiencies in a refrigeration system. The refrigeration system
can be the refrigeration system of FIG. 1. A controller such as
described with respect to FIG. 1 or 2 may be used to perform the
methods of FIGS. 11 and 12. The methods of FIGS. 11 and 12 may
represent algorithms that are stored on a computer readable medium,
such as a memory of a controller (e.g., the memory 220 of FIG.
2).
[0093] Turning now to FIG. 11, the method 1100 begins at step 1105.
At step 1110, the refrigeration system receives data associated
with the operation of the refrigeration system. The data associated
with the operation of the refrigeration system may be one or more
of suction temperature, suction pressure, discharge pressure,
current, and/or capacity associated with one or more compressors of
the refrigeration system. In some embodiments, the data is received
by one or more sensors 160 operable to sense the suction
temperature, suction pressure, discharge pressure, current, and
capacity of the one or more compressors. The method 1100 may then
continue to step 1120.
[0094] At step 1120, the refrigeration system determines an ideal
output variable of a compressor based at least on the data
associated with the operation of the refrigeration system. The
ideal output variable of a compressor may be one of mass flow,
power, current, and/or capacity. In some embodiments, the
refrigeration system determines the ideal output variable using a
compressor map equation. For example, the suction temperature,
suction pressure, and/or discharge pressure received from the
sensors 160 may be inputs to a compressor map equation (e.g., the
compressor map equation of FIG. 4) that outputs ideal values for
mass flow, power, current, and/or capacity.
[0095] In some embodiments, the refrigeration system may calculate
a range of values associated with the ideal output variable by
inputting the data associated with the operation of the
refrigeration system (received in step 1110) into a compressor map
equation. For example, as shown in FIGS. 5A and 5B, the
refrigeration system may calculate a range of values representing
an ideal current for the compressor (e.g., ideal current 410) based
on the suction pressure, suction temperature, and discharge
pressure sensed by the one or more sensors (e.g., sensors 160b,
160c, and/or 160e). In some embodiments, the method 1100 continues
to a decision step 1130.
[0096] In decision step 1130, the refrigeration system determines,
based at least on the data associated with the operation of the
refrigeration system (e.g., actual values for mass flow, power,
capacity, and/or current received from the sensors at step 1110)
and the ideal output variable (e.g., ideal values for mass flow,
power, capacity, and/or current determined in step 1120), whether
the performance of the compressor is abnormal. For example, in some
embodiments, the data associated with the operation of the
refrigeration system is compared to a value associated with the
ideal output variable to determine that the performance of the
compressor is abnormal.
[0097] In some embodiments, determining that the performance of the
compressor is abnormal includes determining that a value associated
with the operational data is outside the range of values associated
with the ideal output variable. For example, as depicted in FIG.
5B, the refrigeration system determines that a value associated
with the operational data (i.e., actual current 520) is outside the
range of values associated with the ideal output variable (i.e.,
ideal current 510).
[0098] In some embodiments, determining that the performance of the
compressor is abnormal comprises determining that the compressor is
under or over-performing. For example, in some embodiments, the
refrigeration system may determine that the compressor is
under-performing when it senses that the operational data is lower
than a value associated with the ideal output variable.
Alternatively, in some embodiments, the refrigeration system may
determine that the compressor is over-performing when it senses
that the operational data is higher than a value associated with
the ideal output variable. If the refrigeration system determines
that the performance of the compressor(s) is normal, the method
1100 may continue to an end step 1145. Alternatively, if the
refrigeration system that the performance of the compressor is
abnormal, the method 1100 may continue to step 1140.
[0099] At step 1140, the refrigeration system reports that
compressor performance is abnormal. In some embodiments, reporting
comprises triggering an alarm. In other embodiments, reporting
comprises sending a notification or warning to the operator of the
refrigeration system. Although this disclosure describes specific
methods of reporting, this disclosure recognizes any suitable
method of reporting that the compressor performance is abnormal. In
some embodiments, method 1100 may continue to an step 1145 where
the method ends.
[0100] In other embodiments, such as depicted in FIG. 12, the
method 1200 may determine abnormal compressor performance based on
a reserve measurement. The method 1200 may begin at step 1205 and
then continue to step 1210. At step 1210, the refrigeration system
receives data associated with the operation of the refrigeration
system. As described above, this information may be received by one
or more sensors 160 associated with the refrigeration system. The
method 1200 may then continue to step 1220. At step 1220, the
refrigeration system determines an ideal output variable. As
described above, the ideal output variable may be one of mass flow,
power, current, and/or capacity. The method 1200 may then continue
to step 1230.
[0101] At step 1230, the refrigeration system calculates a value
associated with the ideal output variable. In some embodiments, the
value may be calculated using a compressor map equation provided by
the manufacturer of a compressor. For example, a compressor map
equation may be used to calculate a value associated with the ideal
output variable by inputting the data associated with the operation
of the refrigeration system. The method 1200 may then continue to
step 1240.
[0102] At step 1240, the refrigeration system determines a reserve
measurement based on a value associated with the ideal output
variable and the value associated with the operational data. In
some embodiments, the reserve measurement may be determined by
calculating the difference between a maximum value associated with
the ideal output variable and the value associated with the
operational data. For example, the refrigeration system may
calculate a maximum value associated with the ideal output variable
for capacity as 18 kBTU/hr and receive operational data indicating
that the compressor capacity is 12 kBTU/hr. In such an example, the
refrigeration system may determine that the reserve measurement is
6 kBTU/hr. In other embodiments, the reserve measurement may be
determined by calculating the difference between the value
associated with the operational data and a minimum value associated
with the ideal output variable. The method 1200 may then continue
to a decision step 1250.
[0103] At decision step 1250, the refrigeration system determines
whether the reserve measurement is less than a specified value. The
specified value may be a value specified by the manufacturer of the
compressor or by the operator of the compressor. The specified
value may be stored on a computer readable medium, such as a memory
of a controller (e.g., the memory 220 of FIG. 2). In some
embodiments, if the refrigeration system determines that the
reserve measurement is greater or equal to the specified value, the
method 1200 continues to an end step 1265. Alternatively, if the
refrigeration system determines that the reserve measurement is
less than the specified value, the method 1200 may continue to step
1260.
[0104] At step 1260, the refrigeration system reports when the
reserve measurement is less than a specified value. In some
embodiments, reporting that the reserve measurement is less than a
specified value comprises triggering an alarm. In other
embodiments, reporting that the reserve measurement is less than a
specified value comprises sending a warning to the operator of the
refrigeration system. The method 1200 may then end in a step
1265.
[0105] In certain embodiments, the methods described with respect
to FIGS. 11 AND 12 may be performed in parallel. For example,
operational data may be used to determine if compressor performance
is abnormal (as described in FIG. 11) and to determine if a reserve
measurement is low (as described in FIG. 12).
[0106] This disclosure also recognizes improving the energy
efficiency of a refrigeration system by prioritizing one control
variable over another control variable in order to meet a control
objective. Refrigeration systems may be associated with one or more
control objectives that, when met, ensure that the enclosed space
is maintaining its cool temperature. For example, a control
objective for a refrigeration system may be to maintain a specific
suction pressure, liquid pressure, liquid temperature, and/or
condenser temperature difference (TD). Consequences may vary for a
refrigeration system that is not meeting its control objectives.
For example, failure to meet a control objective may result in in
damage to one or more components of the refrigeration system, an
increase in energy consumption in the event that one component
compensates for another component, or even an inoperable
refrigeration system.
[0107] Refrigeration system 100 may be configured to send a warning
to an operator when it is at risk for not meeting a control
objective. In some embodiments, refrigeration system 100 may
determine it is at risk for not meeting a control objective based
on a statistical analysis of operating data. Control objectives may
include suction pressure, liquid pressure, and liquid temperature.
Control objectives may also include condenser temperature
difference (TD). Although this disclosure describes specific
control objectives, this disclosure contemplates controller 150 may
control any control variable of refrigeration system 100. In some
embodiments, control objectives may be associated with setpoints.
As one example, such as that depicted in FIG. 6, the control
objective for refrigeration system 100 may be to maintain suction
pressure at a setpoint of 8 PSI. As another example, the control
objective of refrigeration system 100 may be to maintain liquid
pressure at a setpoint of 104 PSI.
[0108] Control objectives may also be associated with an acceptable
range. For example, as depicted in FIG. 6, the control objective of
refrigeration system 100 may be to maintain suction pressure
between an acceptable range of 1-22 PSI. Thus, refrigeration system
100 would meet its suction pressure objective as long as the
suction pressure remains within those limits. The upper and lower
values in the range may be associated with an alarm. For example,
if refrigeration system 100 senses that suction pressure is above
22 PSI, refrigeration system 100 may alert an operator.
[0109] Refrigeration system 100 may receive actual data (operating
data) associated with each control variable. For example,
refrigeration system may receive operating data associated with
suction pressure, liquid pressure, outdoor temperature, and/or
liquid temperature. Operating data may be received from one or more
sensors 160 of refrigeration system 100.
[0110] Controller 150 of refrigeration system 100 may be configured
to calculate a confidence interval for the control objective using
the received operating data. The confidence interval may be
calculated at any suitable value. As an example, controller 150 may
determine a standard deviation band of 3.pi. at a 99% confidence
interval for the entire population of operating data associated
with suction pressure. In some embodiments, controller 150 may be
configured to trigger a warning to operator of refrigeration system
100 when operating data begins to deviate from the band. For
example, controller 150 may send a warning to operator upon
detection of actual suction pressure measurements deviating higher
or lower than 3.sigma.. The standard deviation band (or acceptable
range) may be determined by any suitable means. For example, the
band may be predetermined by the manufacturer and the values
associated with the band may be programmed in controller 150. As
another example, controller 150 may learn the typical band during
operation of HVAC system 100 and may be operable to detect any
deviation from the band during operation (e.g., during operation of
HVAC system 100, controller 150 may determine the mean of its
control variable from operating data associated with the control
variable and the standard deviation for the control variable and
thus determine whether the HVAC system is operating outside of the
band).
[0111] In some embodiments, a single control objective may be
controlled by more than one controller. For example, refrigeration
system 300 may include controllers 150a and 150b. Controller 150a
may be configured to control suction pressure and liquid pressure.
Controller 150b may be configured to control liquid pressure and
temperature difference (TD). In some embodiments, a control
objective of controller 150 may include control variables
associated with different priorities. For example, such as depicted
in FIG. 7, controller 150b may be configured to prioritize liquid
pressure over condenser TD. As such, controller 150b will manually
override control of condenser TD in favor of restoring liquid
pressure to its acceptable range.
[0112] In FIG. 7, operational data for liquid pressure and
condenser TD is depicted over a period of time. As depicted, liquid
pressure is associated with an acceptable range of 104-314 PSI and
condenser TD is associated with a setpoint of 15.degree. F. At time
period A, refrigeration system 100 is operating within an
acceptable range such that no alarms are triggered (i.e.,
refrigeration system 100 is meeting all control objectives).
However, at time period B, the actual measurement of liquid
pressure reaches the minimum value of the acceptable range (e.g., a
decrease in outdoor temperature causes a decrease in liquid
pressure). In response, controller 150b may be configured to adjust
the speed of condenser fan 125 such that liquid pressure increases.
In effect, controller 150 manually overrides the condenser TD
difference in favor of restoring liquid pressure to the acceptable
range. At time period C, all components of refrigeration system 100
are operating within their acceptable ranges.
[0113] In certain embodiments, a controller verification method may
verify that the system is acting properly. The controller
verification method may ignore the value of a lower priority
measurement (e.g., TD) near the time periods that a higher priority
measurement (e.g., liquid pressure) operates outside of its
acceptable range. This may prevent a false alarm. For example, in
FIG. 7, TD only operates outside of its acceptable range when the
liquid pressure falls to its minimum value. Thus, even though TD is
occasionally outside of its acceptable range, the system is
operating properly because maintaining liquid pressure within its
acceptable range has higher priority than maintaining TD.
[0114] FIG. 13 is directed to a method of detecting when a
refrigeration system is at risk for not meeting its control
objective. The refrigeration system can be the refrigeration system
of FIG. 1. A controller such as described with respect to FIG. 1 or
2 may be used to perform the method of FIG. 13. The method of FIG.
13 may represent an algorithm that is stored on a computer readable
medium, such as a memory of a controller (e.g., the memory 220 of
FIG. 2).
[0115] The method 1300 begins at step 1305. At step 1310,
refrigeration system 100 receives operating data associated with at
least one control variable. Refrigeration system 100 may have one
or more control variables such as: suction pressure, liquid
pressure, liquid temperature, and/or condenser temperature
difference. Refrigeration system 100 may receive operating data
from sensors 160 operable to sense data associated with
refrigeration system 100. For example, sensors 160 may be operable
to sense data associated with suction pressure (e.g., sensor 160b),
liquid pressure (e.g., sensor 160a), liquid temperature (e.g.,
sensor 160a), and/or temperature of the surrounding environment.
The method 1300 may then continue to a decision step 1320.
[0116] At decision step 1320, the refrigeration system 100
determines, based on the operating data, whether a control
objective is met. Refrigeration system 100 may have a control
objective associated with one or more control variables. In some
embodiments, the control objective of refrigeration system 100 may
include one control variable. In other embodiments, the control
objective of refrigeration system 100 may include more than one
control variable. Although specific control variables have been
described herein, this disclosure contemplates that the control
objective of refrigeration system 100 may be associated with any
variable that is controllable by refrigeration system 100.
[0117] In some embodiments, determining whether the control
objective is met according to step 1320 comprises determining
whether the refrigeration system 100's highest priority objective
is met. In some embodiments, each control variable may be
associated with a particular priority status. For example, the
control objective of refrigeration system 100 may be to prioritize
suction pressure over liquid pressure. As another example, the
control objective of refrigeration system 100 may be to prioritize
liquid pressure over liquid temperature. As yet another example,
the control objective of refrigeration system 100 may be to
prioritize suction pressure over liquid pressure but also
prioritize liquid pressure over liquid temperature. In such
embodiments, the control objective is met when the highest priority
objective is met even though a lower priority objective may not be
met.
[0118] In some embodiments, determining whether a control objective
is met according to step 1320 may comprise comparing operating data
associated with a control variable to an acceptable range or set
point. For example, suction pressure may be associated with an
acceptable range of 1-22 PSI and a setpoint of 8 PSI. As another
example, liquid pressure may be associated with an acceptable range
of 104-314 PSI and a setpoint of 104 PSI. As yet another example,
condenser temperature difference may be associated with a setpoint
of 15.degree. F.
[0119] In some embodiments, determining whether a control objective
is met according to step 1320 comprises determining whether the
operating data associated with a control variable falls within the
acceptable range. For example, refrigeration system 100 may
determine that its control objective of maintaining suction
pressure between 1-22 PSI is not met when the operating data for
suction pressure is measured at 25 PSI. As another example,
refrigeration system 100 may determine that its control objective
is not met when the operating data associated with its higher
priority control variable (e.g. suction pressure) is outside of the
acceptable range for suction pressure (e.g., 1-22 PSI).
[0120] In another embodiment, determining whether a control
objective is met according to step 1320 may comprise calculating a
confidence interval for the control objective, determining a
standard deviation band associated with the confidence interval,
and comparing the operating data to the standard deviation band.
For example, refrigeration system 100 may have a control objective
of maintaining suction pressure at 8 PSI. Based on this control
objective, refrigeration system 100 may calculate a 99% confidence
interval for the entire population of operating data associated
with suction pressure and determine that a standard deviation band
of 3.sigma. is associated with the calculated confidence interval.
In some embodiments, refrigeration system 100 may compare operating
data received from sensors 160 to the standard deviation band. In
some embodiments, refrigeration system 100 determines that it is
meeting its control objective when the operating data falls within
the standard deviation band. In other embodiments, refrigeration
system 100 determines that it is not meeting its control objective
when the operating data falls outside of the standard deviation
band.
[0121] If the refrigeration system determines that the control
objective is met, in some embodiments, the method 1300 continues to
an end step 1355. Alternatively, if the refrigeration system
determines that the control objective is not met, the method 1300
may continue to step 1330.
[0122] At step 1330, refrigeration system 100 operates according to
a configuration selected to cause the control objective to be met.
In some embodiments, refrigeration system 100 is operated according
to the configuration selected to cause the control objective to be
met in response to determining that the control objective is not
being met. For example, in response to determining that the
operating data associated with a higher priority control variable
is outside of its acceptable range, refrigeration system 100
operates according to a configuration selected to bring the
operating data associated with the higher priority control variable
within its acceptable range. Such an example may be better
understood in view of FIG. 7.
[0123] FIG. 7 depicts an example refrigeration system (e.g.,
refrigeration system 100) having a control objective of
prioritizing liquid pressure over condenser temperature difference.
At time period B, refrigeration system 100 determines that it is at
risk for not meeting its control objective (i.e., liquid pressure
falls below 104 PSI) and operates refrigeration system 100 in a
configuration that causes the control objective to be met. As an
example, the configuration that causes the control objective to be
met may comprise decreasing the speed of condenser fan 125. In some
embodiments, method 1300 may continue to an end step 1355. In other
embodiments, method 1300 may continue to step 1340. In yet other
embodiments, method 1300 may continue to step 1350 or return to
step 1305 to begin method 1300 again.
[0124] Step 1340 may be applicable when refrigeration system 100
has a control objective involving more than one control variable.
At step 1340, refrigeration system 100 overrides control of a lower
priority control variable until the operating data associated with
the higher priority control variable is within its acceptable
range. In other words, refrigeration system 100 may ignore the
operating data associated with a lower priority control variable
near the time periods when the operating data associated with the
higher priority control variable is outside of its acceptable
range.
[0125] Returning to the earlier example depicted in FIG. 7, the
control objective of refrigeration system 100 may be to prioritize
liquid pressure over condenser temperature difference (TD). At time
period B, refrigeration system 100 may operate the condenser fan
125 at a lower speed in order to increase liquid pressure and meet
its control objective. However, decreasing the speed of condenser
fan 125 may result in an increased TD between the surrounding
environment and the liquid refrigerant. See FIG. 7 (operating data
associated with condenser TD increases during time period B). Step
1340 of method 1300 permits deviation of operating data associated
with the condenser TD by overriding control of condenser TD (lower
priority control variable) until liquid pressure (i.e., higher
priority control variable) is restored to an acceptable value.
Stated differently, refrigeration system 100 may ignore that the
operating data associated with the condenser TD is deviating from
its 15.degree. F. setpoint until the operating data associated with
condenser pressure reaches at least 104 PSI.
[0126] At an optional step 1350, refrigeration system 100 reports
when the control objective is not being met. In some embodiments,
refrigeration system 100 may send a warning to the operator of
refrigeration system 100 in response to determining that the
control objective is not being met. For example, refrigeration
system 100 may report when operating data begins to deviate from a
standard deviation band. As another example, refrigeration system
100 may report when operating data is measured outside of an
acceptable range. Step 1350 may occur at any suitable time. For
example, in some embodiments, step 1350 may occur subsequent to
step 1320. In other embodiments, step 1350 may occur subsequent to
step 1340.
[0127] In some embodiments, method 1300 may include a controller
verification step. In a controller verification step, the
refrigeration system may verify that controller is working
properly. In some embodiments, refrigeration system verifies that
the controller is working properly by monitoring the operating data
of the refrigeration system. For example, in some embodiments, the
controller verification logic may ignore operating data for a lower
priority control variable during times when the operational data
for a higher priority control variable is outside the acceptable
range.
[0128] Modifications, additions, or omissions may be made to the
systems, apparatuses, and methods described herein without
departing from the scope of the disclosure. The components of the
systems and apparatuses may be integrated or separated. Moreover,
the operations of the systems and apparatuses may be performed by
more, fewer, or other components. For example, refrigeration system
100 may include any suitable number of compressors, condensers,
condenser fans, evaporators, valves, sensors, controllers, and so
on, as performance demands dictate. One skilled in the art will
also understand that refrigeration system 100 can include other
components that are not illustrated but are typically included with
refrigeration systems. Additionally, operations of the systems and
apparatuses may be performed using any suitable logic comprising
software, hardware, and/or other logic. As used in this document,
"each" refers to each member of a set or each member of a subset of
a set.
[0129] Modifications, additions, or omissions may be made to the
methods described herein without departing from the scope of the
disclosure. The methods may include more, fewer, or other steps.
Additionally, steps may be performed in any suitable order. In
certain embodiments, the methods may be performed in parallel (e.g.
methods depicted in FIGS. 11 and 12).
[0130] Although this disclosure has been described in terms of
certain embodiments, alterations and permutations of the
embodiments will be apparent to those skilled in the art.
Accordingly, the above description of the embodiments does not
constrain this disclosure. Other changes, substitutions, and
alterations are possible without departing from the spirit and
scope of this disclosure.
* * * * *