U.S. patent application number 15/707120 was filed with the patent office on 2018-11-08 for embedded sensors for in-situ cell monitoring of batteries.
The applicant listed for this patent is Aleksandra Fortier, Michael Gerald Pecht, Yinjiao Xing. Invention is credited to Aleksandra Fortier, Michael Gerald Pecht, Yinjiao Xing.
Application Number | 20180321325 15/707120 |
Document ID | / |
Family ID | 64014634 |
Filed Date | 2018-11-08 |
United States Patent
Application |
20180321325 |
Kind Code |
A1 |
Fortier; Aleksandra ; et
al. |
November 8, 2018 |
Embedded Sensors for In-Situ Cell Monitoring of Batteries
Abstract
The disclosed principles provide for techniques for the 3D
fabrication of sensing systems that are embedded inside battery
cells and provide cell parameter data for a comprehensive and an
robust battery management system. The disclosed principles provide
for online and real-time monitoring of battery state-of-health down
to the individual cell level of each battery using embedded sensors
on one or more of the internal layers of a cell, such as the
dielectric separators found in such battery cells. The
implementation of the disclosed principles in individual battery
cells therefore provides an increased likelihood to mitigate
catastrophic failures in batteries. In addition, the disclosed
fabrication processes for printing sensors directly on one or more
of the components or layers within each individual battery cell,
significantly reduce manufacturing steps required by conventional
battery management systems. The disclosed principles also provided
for a unique silica-based ink for use in the 3D printing of such
embedded cell sensing components.
Inventors: |
Fortier; Aleksandra;
(Coppell, TX) ; Pecht; Michael Gerald;
(Hyattsville, MD) ; Xing; Yinjiao; (College Park,
MD) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Fortier; Aleksandra
Pecht; Michael Gerald
Xing; Yinjiao |
Coppell
Hyattsville
College Park |
TX
MD
MD |
US
US
US |
|
|
Family ID: |
64014634 |
Appl. No.: |
15/707120 |
Filed: |
September 18, 2017 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
62502946 |
May 8, 2017 |
|
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01R 31/3835 20190101;
H01M 10/486 20130101; H01M 10/48 20130101; G01R 31/392 20190101;
Y02E 60/10 20130101; H01M 2010/4278 20130101 |
International
Class: |
G01R 31/36 20060101
G01R031/36; H01M 2/14 20060101 H01M002/14; H01M 10/48 20060101
H01M010/48 |
Goverment Interests
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT
[0002] This invention was made with government support under
Contract No. FA8650-12-D-2224 awarded by the Intellectual Property
Law Division of the Department of the Air Force. The government has
certain rights in the invention.
Claims
1. A battery cell monitoring system, comprising: an optical fiber
formed on a component within the battery cell; at least one fiber
Bragg grating (FBG) sensor formed along the optical fiber by
creating a variation in the refractive index of the optical fiber;
wherein the optical fiber is configured to receive therethrough
light transmitted from a light source, and to emit light therefrom
with one or more shifts in wavelength caused by refraction of the
transmitted light by the at least one FBG sensors.
2. A battery cell monitoring system in accordance with claim 1,
wherein the optical fiber is formed on a dielectric separator of
the battery cell.
3. A battery cell monitoring system in accordance with claim 1,
wherein the optical fiber and the at least one FBG sensor are
formed via 3D printing.
4. A battery cell monitoring system in accordance with claim 1,
wherein the light source comprises battery cell monitoring
equipment coupled to the optical fiber and configured to transmit
light therethrough and to receive the light emitted therefrom to
measure parameters of the battery cell based on the one or more
shifts in wavelength caused by refraction of the transmitted light
by the at least one FBG sensors.
5. A battery cell monitoring system in accordance with claim 4,
wherein one or more of battery cell temperature, strain, pressure,
and displacement are measured by the battery cell monitoring
equipment based on said one or more shifts in wavelength.
6. A battery cell monitoring system in accordance with claim 1,
further comprising at least two metal sleeves formed on the optical
fiber proximate ones of the FBG sensors, the at least two metal
sleeves configured to detect an internal voltage of the cell.
7. A battery cell monitoring system in accordance with claim 6,
further comprising corresponding conductive leads formed in contact
with the at least two sleeves, the conductive leads configured to
permit voltage measuring across the FBG sensors via the
corresponding metal sleeves.
8. A battery cell monitoring system in accordance with claim 7,
wherein the at least two sleeves and corresponding conductive leads
are formed via 3D printing.
9. A battery cell monitoring system in accordance with claim 1,
wherein the optical fiber comprises a cured mixture comprising
photopolymer and silica.
10. A method of forming a battery cell monitoring system, the
method comprising: forming an optical fiber on a component within
the battery cell; forming at least one fiber Bragg grating (FBG)
sensor along the optical fiber by creating a periodic variation in
the refractive index of the optical fiber; and ultraviolet (UV)
light curing the optical fiber after its forming; wherein the
optical fiber is configured to receive therethrough light
transmitted from a light source, and to emit light therefrom with
one or more shifts in wavelength caused by refraction of the
transmitted light by the at least one FBG sensors.
11. A method in accordance with claim 10, wherein forming the
optical fiber comprises forming the optical fiber on a dielectric
separator of the battery cell.
12. A method in accordance with claim 10, wherein forming the
optical fiber and the at least one FBG sensor comprises forming via
3D printing.
13. A method in accordance with claim 12, wherein the 3D printing
comprises employing aerosol jet technology.
14. A method in accordance with claim 10, further comprising
forming at least two metal sleeves on the optical fiber proximate
ones of the FBG sensors, the at least two metal sleeves configured
to detect an internal voltage of the cell.
15. A method in accordance with claim 14, further comprising
forming corresponding conductive leads in contact with the at least
two sleeves, the conductive leads configured to permit voltage
measuring across the FBG sensors via the corresponding metal
sleeves.
16. A method in accordance with claim 15, wherein forming the at
least two sleeves and corresponding conductive leads comprises
forming via 3D printing.
17. A method in accordance with claim 10, wherein the light source
comprises battery management equipment configured to receive the
emitted light to measure parameters of the battery cell based on
the one or more shifts in wavelength caused by refraction of the
transmitted light by the at least one FBG sensors.
18. An ink mixture for use in 3D printing equipment, the ink
mixture comprising: a photo-polymer solvent; silica powder; and
wherein the ink mixture has an overall viscosity sufficient for use
in the 3D printing equipment and is UV-curable immediately after
deposition.
19. An ink mixture in accordance with claim 18, wherein said ink
mixture comprises an overall viscosity of about 75 to 200 cP.
20. An ink mixture in accordance with claim 19, wherein the
photo-polymer solvent has an individual viscosity of about 30-55
cP, and wherein the ink mixture comprises about 98% of said
photo-polymer solvent and about 2% of said silica powder, and
wherein said ink mixture comprises an overall viscosity of about 86
cP.
21. An ink mixture in accordance with claim 18, further comprising
an alcohol-based agent.
22. An ink mixture in accordance with claim 21, wherein the ink
mixture comprises about 81.667% said photo-polymer solvent, about
1.667% said silica powder, and about 16.667% said alcohol-based
agent, and wherein said ink mixture comprises an overall viscosity
of about 65 cP.
23. An ink mixture in accordance with claim 18, wherein the 3D
printing equipment employs aerosol jet deposition technology.
24. An ink mixture in accordance with claim 23, wherein operating
parameters for the aerosol jet equipment comprise: step size of 50
.mu.m; 7 mm/s deposition speed; flow parameters set as 3, 1250,
1300 ccm; standoff distance between the nozzle and a target at
approximately 4 mm; and a nozzle size of 200 microns.
Description
PRIORITY CLAIM
[0001] The present disclosure is a non-provisional conversion of,
and thus claims priority to, U.S. Provisional Patent Application
Ser. No. 62/502,946, filed May 8, 2017, the contents of which are
incorporated herein by reference for all purposes.
TECHNICAL FIELD
[0003] The present disclosure relates to battery management sensors
and systems, and in particular to a unique technique for embedding
sensors in battery cells for in-situ monitoring of individual cell
state-of-health.
BACKGROUND
[0004] Rechargeable lithium-based batteries currently have the
highest energy densities available on the market, and recent
advancements in materials have also made them the most reliable. As
such, the Li-ion battery (LIB) has become the most popular choice
of energy-storage device for many applications, such as cellular
phones, mobile computers, medical, aerospace and military devices,
and is currently the lead contender to power all electric cars.
Batteries are also the primary energy source for aircraft power and
operation where monitoring energy storage, usage, and potential
failures is critical to all operations of the aircraft and even
direct energy weapons (DEWs).
[0005] To support consumer needs, many of these electronic
applications require rechargeable or secondary batteries that can
offer long cycle life, high volumetric and gravimetric energy
densities, and high power capabilities. Thus, there is also a
significant need to estimate and understand a battery's state of
charge and state of health. As an electrochemical product, a
battery acts differently under different operational and
environmental conditions. The uncertainty of a battery's
performance poses a challenge to the implementation of these
functions. There are a few battery management systems (BMS)
currently available on the market, but conventional BMSs do not
provide adequate or enough information in real time to mitigate all
failures in time. This is the case because existing BMSs do not
report all parameters at the cell-level.
[0006] Typically, battery monitoring is performed by sampling
external temperature and electrical properties, such as current and
voltage, over the external battery terminals with one measurement
made per group of 10 or more cells. The problem with existing BMSs
is lack of reporting parameters at the individual cell-level which
is crucial for good cell performance and long life cycle of the
battery pack. For example, aircraft battery packs are typically
composed of several hundreds of cells, which in turn provides
several hundreds of cell failure opportunities, and therefore
having the ability to monitor battery health at the cell-level is
crucial to ensure operational safety and efficiency. Also, aircraft
batteries will undergo different operational modes than those in
typical portable electronics. For instance, as the aircraft is used
in the open air, the batteries are subjected to damage from
alternating temperature, not only during cell operation but also
during storage. Pressure and strain are also much more prevalent
for aircraft batteries due to their environmental exposure. As
cells undergo charging and discharging cycles, performance changes
take place and integration of smart monitoring at the cell-level is
critical to ensure operational safety and efficiency in such
battery packs that are composed of several hundred cells
[0007] Several common functions of three popular commercial BMSs
are summarized below in Table 1.
TABLE-US-00001 TABLE 1 Measured BMS by Maxim BMS by Texas BMS by
O2Micro Parameters Integrated [3] Instruments [4] International UK
[5] Voltage At Cell-Level At Cell-Level At Cell-Level Temperature
No At Cell-Level At Pack-Level State of Charge (SOC) No Yes Yes
State of Health (SOH) No No No Current At Cell-Level At Cell-Level
At Cell-Level Data Logging None On PC-Based GUI Only EEPROM
From Table 1, common disadvantages can be noted in the current
commercial BMS solutions. Lack of monitoring temperature, SOC and
SOH across all levels starting from cell-level and limited data
logging function. Monitoring temperature at cell-level is essential
to prevent overheating of battery pack, SOH is supposed to show
current health status and the remaining performance of the battery
that will ensure operational safety of the aircraft and scheduled
maintenance for battery replacement, and limited data logging which
typically traces the cycling pattern of the battery that can assist
in monitoring SOC in real time. To meet the future challenges of
energy storage, a new generation of Li-ion batteries with excellent
performance, long cycle life, safety and reliability are needed not
only for applications in consumer electronics, but especially for
clean energy storage and use in all electric and aerospace
applications.
[0008] In an effort to mitigate abnormal increases in temperature
and/or pressure (i.e., "thermal runaway") in batteries and increase
their reliability, several conventional approaches have been
attempted. For example, conventional approaches have included
embedded commercial reaction temperature sensors (RTS) to improve
battery safety, the implementation of micro-temperature and voltage
sensors into li-ion batteries where sensors are fabricated using
micro-electro-mechanical systems (MEMS) technology, the monitoring
of internal battery health through a polymer or copper coated
bifunctional separator serving as third sensing terminal in
addition to the cathode and anode, and the creation of more
accurate battery management systems by implementing commercial
internal sensing devices. However, while each of these conventional
approaches may be partially beneficial, they require lengthy
implementation and fabrication processes, and are limited to
monitoring only certain battery state-of-health parameters. Indeed,
not a single conventional sensing technology is capable of
simultaneously outputting data for multiple parameters in real time
to increase the overall accuracy of each cell's
state-of-health.
[0009] Accordingly, there is a need in the art for a battery cell
sensing technology capable of providing data for multiple battery
state-of-health parameters, but which does not suffer from the
deficiencies of conventional approaches. The present disclosure
provides such a solution.
SUMMARY
[0010] To overcome the deficiencies of the prior art, the disclosed
principles provide for techniques for the 3D fabrication of sensing
systems that are embedded inside battery cells and provide cell
parameter data for a comprehensive and an robust BMS. The disclosed
principles provide for online and real-time monitoring of battery
state-of-health down to the individual cell level of each battery
using embedded sensors on one or more of the internal layers of a
cell, such as the dielectric separators found in such battery
cells. The implementation of the disclosed principles in individual
battery cells therefore provides an increased likelihood to
mitigate catastrophic failures in batteries. In addition, the
disclosed fabrication processes for printing sensors directly on
the separators of each individual battery cell significantly reduce
manufacturing steps required by conventional battery management
systems. However, although every cell in a battery pack will have
health monitoring using the printed sensors and gauges of the
disclosed principles, the weight added to the overall battery pack
will be negligible.
BRIEF DESCRIPTION OF THE DRAWINGS
[0011] The detailed description that follows, by way of
non-limiting examples of embodiments, makes reference to the noted
drawings in which reference numerals represent the same parts
throughout the several views of the drawings, and in which:
[0012] FIG. 1 illustrates a simplified diagram of the basic
construction of a Li-ion cell;
[0013] FIG. 2A illustrates a sensor system formed on a Li-ion cell
separator in accordance with the disclosed principles;
[0014] FIG. 2B illustrates a close-up view of a collection of FBG
sensors from the sensor system of FIG. 2;
[0015] FIG. 3 illustrates an image taken using a scanning electron
microscope of an optical fiber created in accordance with the
disclosed principles using nanoscribe technology;
[0016] FIG. 4 illustrates an exemplary optical stack structure
formed using a tape casting technique;
[0017] FIG. 5 illustrates an image of the strong light reflection
from the exemplary optical stack structure of FIG. 4;
[0018] FIG. 6A illustrates another exemplary embodiment of Li-ion
cell sensor system constructed in accordance with the disclosed
principles;
[0019] FIG. 6B illustrates a close-up view of two of the
collections of sensors from the sensor system in FIG. 6;
[0020] FIG. 7 illustrates an isometric close-up view of a portion
of another exemplary Li-ion cell sensor system constructed in
accordance with the disclosed principles;
[0021] FIG. 8 illustrates an isometric close-up view of a portion
of another exemplary Li-ion cell sensor system constructed in
accordance with the disclosed principles, and similar to the system
of FIG. 7;
[0022] FIG. 9 illustrates one embodiment of a strain measurement
system for a Li-ion battery cell constructed in accordance with the
disclosed principles;
[0023] FIG. 10 illustrates another embodiment of a strain
measurement system for a Li-ion battery cell constructed in
accordance with the disclosed principles;
[0024] FIG. 11 illustrates a block diagram of a battery management
system constructed and implemented in accordance with the disclosed
principles;
[0025] FIG. 12 illustrates a plot of the state-of-health (SOH)
across charging cycles for each of capacity, CVCT, resistance and
CCCT;
[0026] FIG. 13 illustrates a plot of the Final SOH across the cycle
curves for three sample batteries having embedded sensors in each
cell as disclosed herein;
[0027] FIG. 14 illustrates a plot of viscosity vs. shear rate for a
conventional photopolymer solvent alone and for an ink mixture of
the photopolymer solvent with silica powder in accordance with the
disclosed principles;
[0028] FIG. 15A illustrates a scanning electron microscope image of
the photopolymer solvent deposition alone;
[0029] FIG. 15B illustrates an electron dispersive spectroscope
analysis graph of photopolymer solvent deposition of FIG. 15A;
[0030] FIG. 16A illustrates an SEM image of an ink mixture of the
photopolymer solvent of FIGS. 15 and 15B combined with silica
powder in accordance with the disclosed principles;
[0031] FIG. 16B illustrates an electron dispersive spectroscope
analysis graph of silica-based ink mixture deposition of FIG. 16A;
and
[0032] FIG. 17 illustrates a plot of viscosity vs. shear rate for a
conventional photopolymer solvent alone, for an ink mixture of the
photopolymer solvent with silica powder, and for an ink mixture of
the photopolymer solvent, silica powder, and an alcohol-based
agent, in accordance with another embodiment of the disclosed
principles.
DETAILED DESCRIPTION
[0033] In view of the foregoing, through one or more various
aspects, embodiments and/or specific features or sub-components,
the present disclosure is thus intended to bring out one or more of
the advantages that will be evident from the description. The
present disclosure makes reference to one or more specific
embodiments by way of illustration and example. It is understood,
therefore, that the terminology, examples, drawings and embodiments
are illustrative and are not intended to limit the scope of the
disclosure.
Fabrication Processes
[0034] To fabricate the exemplary sensors and gauges disclosed
herein, two different exemplary 3D printing techniques may be used
based on the deposition scale of interest. For features less than
300.times.300.times.80 microns nanoscribe technology may be used,
and for features greater than 300.times.300.times.80 microns
aerosol jet technology may be employed. Of course, it should be
understood that no limitation to any particular printing or
deposition technology is intended or should be implied from the
teachings of the disclosed principles. Accordingly, the disclosed
principles of embedding battery cell sensors/gauges by
printing/depositing on the cell separators to create a battery
management system capable of monitoring the state-of-health (SOH)
and state-of-charge (SOC) of every cell within a battery pack may
be accomplished using any advantageous technology, either now
existing or later developed.
[0035] Nanoscribe technology--Fabrication of three-dimensional
micro- and nanostructures in photo-sensitive materials is based on
"direct laser writing", i.e., a non-linear two-photon absorption
process. Many resins that polymerize when exposed to UV-light can
undergo similar chemical reactions when two photons of
near-infrared light are absorbed simultaneously. A necessary
condition for this effect to occur is a sufficiently high light
intensity that is provided by an ultrashort pulse laser. Typically,
the laser is focused into the resin and the two-photon
polymerization (TPP) is triggered only in the focal spot volume. As
3D analog on to a pixel, the volume counterpart is called voxel.
For printed features with nanoscribe technology that need to retain
conductive properties, traditional sputtering techniques can be
used to metal-coat the printed features.
[0036] Aerosol Jet Technology--An environmentally benign,
low-temperature, computer software driven aerosol 3D jet additive
manufacturing process (such as the process developed by Optomec.TM.
Maskless Mesoscale Material Deposition (M.sup.3D) Aerosol Jet
system) may be used. Aerosol 3D jet printing is maskless,
non-contact additive manufacturing process that reduces the overall
size of electronic systems by using nano-materials to produce fine
featured circuitry and embedded components. The resulting
functional electronics can have line widths and pattern features
ranging from below 10 microns to as large as several millimeters as
aerosol jet deposition utilizes an innovative aerodynamic focusing
technology. The technique can directly deposit a wide range of
commercial and custom electronic materials, including conductive
nanoparticle inks, insulators, polymers, adhesives, dopants,
etchants, and even biological materials on virtually any planar or
non-planar substrate. The support of nanomaterials allows for
low-temperature processing and ultra-thin layers (from 100 nm)
where desired. In case of multilayer deposition, the process flow
may consist of only a few steps, such as loading and then printing
and processing the material until the final layer is deposited. The
aerosol jet processes the material using liquid ink of a desired
composition placed into an atomizer, creating a dense aerosol of
tiny droplets between 1-5 microns in size. The aerosol is carried
by a gas flow to the deposition head. The aerosol jet process
begins with a mist generator that atomizes a source material.
Particles in the resulting aerosol stream can then be refined in a
virtual impactor and further treated on the fly to provide process
flexibility.
Lithium-Ion Batteries
[0037] A lithium-ion (Li-ion) battery is a type of rechargeable
battery in which lithium ions move from the negative electrode to
the positive electrode during discharge and back when charging.
Li-ion batteries use a lithium compound for the electrode material,
where the electrolyte, which allows for ionic movement, and the two
electrodes are the constituent components of a lithium-ion battery
cell. A "cell" is a basic electrochemical unit that contains the
basic components, such as electrodes, separator, and electrolyte. A
"battery" or "battery pack" is a collection of cells which are
ready for use, as it contains an appropriate housing, electrical
interconnections, and possibly electronics to control and protect
the cells from failure.
[0038] Regardless of the shape of the Li-ion battery comprising the
cells, the basic architecture of each cells is the same.
Specifically, each cell is constructed with two electrodes (i.e.,
an anode and cathode), which are kept electrically distinct from
one another by a dielectric separator. The separator is typically a
porous material whose pores permit ionic movement between the
electrodes. FIG. 1 illustrates a simplified diagram of the basic
construction of a Li-ion cell 100 in during both a charging and a
discharging cycle. Each such cell 100 includes an anode 105 and a
cathode 110, which comprise the electrodes of the cell.
Electrically conductive current collectors 115a, 115b are coupled
to the anode 105 and cathode 110, respectively. A separator 125 is
placed between the electrodes 105, 110, and is comprised of a
porous material that permits the lithium ions to pass from one
electrode to the other. More specifically, during a charging state
of the cell 100, the lithium ions 120 pass from the cathode 110 to
the anode 105 through the separator 125, while during a discharge
state, the ions pass from the anode 105 to the cathode 110 through
the separator 125. An electrolyte material 130 is the medium
through which the ions 120 travel, and due to lithium's reactivity
with water, the electrolyte 130 is typically a non-aqueous material
such as a mixture of organic carbonates. The disclosed principles
provide sensor circuitry on the separator for each individual cell
of a Li-ion battery or pack for real time monitoring of each cell's
SOH.
Exemplary Embodiments
[0039] In one embodiment of a Li-ion cell sensor system in
accordance with the disclosed principles, a collection of fiber
Bragg grating (FBG) sensors is 3D printed onto the separator of
each cell. An FBG is a type of distributed Bragg reflector
constructed in a short segment of optical fiber that reflects
particular wavelengths of light and transmits all other
wavelengths. This is achieved by creating a periodic variation in
the refractive index of the optical fiber's core, which creates a
wavelength-specific dielectric mirror. An FBG can therefore be used
as an inline optical filter to block certain wavelengths, or as a
wavelength-specific reflector. In conventional battery monitoring
approaches, thermal monitoring of Li-ion batteries is typically
performed on their surface through the use of thermocouples or
electro-mechanical sensors. Internal monitoring is also challenging
due to the chemically aggressive and electrically noisy
environment, for which sensors with low invasiveness, mechanical
robustness, immunity to electromagnetic radiation, and resistance
to corrosion, are required. Sensors based on fiber Bragg gratings
are therefore an effective method to perform both static and
dynamic measurements of temperature, pressure, strain, and other
measurable parameters related to battery cell health and
status.
[0040] FIG. 2A illustrates a sensor system 200 formed on a Li-ion
cell separator in accordance with the disclosed principles. As
discussed above, the separator 210 is formed from a porous
material, which permits lithium ions to transfer through the
separator 210 from one electrode to another in a Li-ion cell. An
optical fiber 220 is formed on the surface of the separator 210,
for example, using one of the 3D printing techniques discussed
above. Thus, 3D structures comprising the disclosed sensors can be
formed using in-situ ultraviolet (UV) light during printing with
the selected 3D printing technique, and thus the material content
is photopolymer-based so that can be instantly cured with the UV
light. As the optical fiber 220 is 3D printed, FBG sensors are also
created at select locations of the optical fiber 220, again using
the 3D printing technique. Specifically, as seen in the close-up
view of FIG. 2B, a first collection of FBG sensors 230 may be
formed in the optical fiber 220 to function as sensors for
generating data regarding temperature in the cell having the
separator 210, while a second collection of FBG sensors 240 may be
formed at a different location in the optical fiber 220 to function
as sensors for generating data regarding a different parameter for
the cell, such as strain. Likewise, a third collection of FBG
sensors 250 may be formed in the optical fiber 220 to function as
sensors for generating data regarding pressure or other parameter
in the cell. Using this technique, multiple collections of sensors
may be formed in the optical fiber 220 in a manner used to generate
data regarding a measurable parameter of the cell that can be
detected or measured due to its impact of an FBG-based sensor.
[0041] To measure a specific parameter, the FBG sensors detect
changes in the selected parameters being monitored in the cell when
input light from a light source travels through the optical fiber
220 to the various collections of FBG sensors formed in the fiber
220. That input light then interacts with the various sensors. Each
collection of sensors (or a single sensor, if desired) is
specifically configured to reflect a portion of the input light (at
the Bragg wavelength for each sensor) thereby outputting light that
changes in response to changes in a sensed parameter. For example,
the characteristics of each FBG sensors will reflect a narrow
wavelength of light when the cell exhibits a given collection of
parameters. Thus, at a given temperature or pressure or other
measurable parameter, the FBG sensors configured to measure each
such parameter will reflect a given wavelength. However, as any of
these parameters change, the periodicity of the grating and thus
the refractive index of each FBG sensor configured to measure that
parameter also changes, which results in a periodic change in the
wavelength of light reflected by the sensors. The specific
collection of FBG sensors can thus measure parameters such as
temperature, strain, pressure, and displacement based on shifts in
wavelength as each of these parameters changes in each cell during
use of the battery comprising those cells. The output light is
collected as measured to determine which wavelengths of remain. By
determining what wavelengths of light remain in the light output
from the optic fiber 220, changes in the selected parameters can be
determined. Additionally, the printed FBG can measure internal
voltage of the cell by having metal coating around the same
location where the gratings are printed. The metal coating can be
any precious metal inert to the reactive environment of the battery
cell. Examples: platinum (Pt), or gold (Au). Aluminum (Al) could
work as cheaper option too but might decompose at some point so is
not the most reliable long term solution.
[0042] Each of the FBG sensors can be printed as described above by
either of the fabrication processes discussed above, or by any
process either now existing or later developed, and each sensor or
collection of sensors is formed to have a particular Bragg
wavelength as needed to measure a given parameter of the cell in
which the optical fiber 220 is formed. Specifically, for each such
collection of sensors to detect these different parameters, the 3D
fabrication of each FBG comprising each sensor of each collection
is thus altered to adjust the refracted wavelength of light. And
through the disclosed principles, this is done using the same 3D
printing technique used to print the optical fiber 220, allowing
for a unique and quick creation of the entire sensor system on a
cell separator 210, or other layer/component within the batter
cell, capable of measuring multiple parameters used to calculate
cell SOH in a single 3D fabrication process. FIG. 3 is an image 300
taken using a scanning electron microscope (SEM) of an optical
fiber 310 created in accordance with the disclosed principles using
nanoscribe technology. The optical fiber 310 was printed on a glass
substrate, which can be employed as the dielectric material used as
a separator in a Li-ion cell. The disclosed principles allowed the
optical fiber 310 to be 3D printed with just a 10 micron diameter
using a photo polymer-based material. FBG sensors 320 are also
formed in the optical fiber 310 using the same technology for the
3D printing of the optical fiber 310.
[0043] In other embodiments, the fabrication of such an FBG sensor
system in accordance with the disclosed principles may be 3D
printing on a larger scale, if needed. For example, Aerosol Jet
technology may be employed to form the same optic fiber and FBG
sensor structure as described above, but where the optical fiber is
0.25 mm wide. In addition, the various FBG sensors for measuring
various battery cell parameters are again formed within the optical
fiber, but again at a larger scale. More specifically, for such
Aerosol Jet deposition technique, three deposition layers were
made, resulting in about 40 microns in thickness, with a step size
of 50 .mu.m and 5 mm/sec deposition speed. The flow parameters were
set as 3, 1250 and 1300 ccm, with a standoff distance between the
nozzle and substrate of approximately 4 mm.
[0044] In yet other embodiments, for larger scale structures, the
optical fiber and FBGs may be formed using a tape casting method,
with an alternating material approach of two commercially available
optical-based materials (e.g., Norland 71 and 84 produced by
Norland Products, Inc. of New Jersey, USA). These materials each
have a different refractive index, 1.56 for Norland 71 and 1.46 for
Norland 84. Such an approach allows the printing of the FBGs in
sensors measuring different parameters to be substantially the same
for each FBG, but using different material to alter the wavelength
of each particular FBG. Thus, not only do the disclosed principles
allow for fabricating each parameter's sensor in a different
structure from one another, sensor fabrication may be the same for
all such sensors by alternatively changing the material used for
printing each collection. Looking at FIG. 4, illustrated is an
exemplary optical stack structure 400 formed using a tape casting
technique. Three layers 410, 420, 430 equal in length with varying
widths may be deposited on a substrate material, such as glass. In
such embodiments, the first layer 410 on the bottom and the third,
outermost layer 430 on the top may be formed from Norland 71
material, while the second, middle layer 420 is formed from Norland
84. The bottom layer 410 is formed with the largest width of the
three layers, with the middle layer 420 having a lesser width, and
then the top layer 430 having the least width. However, the
difference in widths between the middle layer 420 and top layer 430
is approximately formed at one-half the difference in widths
between the bottom layer 410 and middle layer 420. The deposition
thickness of each layer 410, 420, 430 is kept substantially the
same, and all three layers 410, 420, 430 were UV cured as
deposited. By varying the widths of each layer, the step/grated
pattern found in commercial FBG fibers are created. FIG. 5
illustrates an image 500 of the strong light reflection from the
exemplary optical stack structure 400 of FIG. 4. The image 500
shows three dots of light 510, 520, 530 generated from input light
passing through the three layers of the optical stack 400. The two
dots 520, 530 appearing close together account for the two layers
420, 430 on top being very close in width, while the third dot 510
further away corresponds to the widest layer 410 on the bottom of
the stack 400.
[0045] Turning now to FIG. 6A, illustrated is another exemplary
embodiment of Li-ion cell sensor system 600 constructed in
accordance with the disclosed principles. In this embodiment, the
system 600 again includes optical fiber 610 printed or similarly
deposited onto a dielectric separator 620 of a Li-ion cell. As with
some of the other embodiments discussed above, the separator 620 is
formed as a porous material. However, it should be noted that the
disclosed principles encompass the 3D printing of the disclosed
sensors and sensor systems on any layer or component in a cell, or
even multiple components within the same cell. The optical fiber
610 is formed as a tall U-shape with its input and output ends
reaching one edge of the separator 620. Formed along the optical
fiber 610 are multiple collections of FBG sensors, two of which are
denoted as 630 and 640, formed in the optical fiber core to
function as sensors for generating data regarding cell parameters,
as discussed above.
[0046] Also printed on the separator 620 in accordance with the
disclosed principles are conductors 650 and 660. To form the
conductors 650, 660, each collection of FBG sensors 630, 640 is
partially coated with conductive metal sleeves 650a, 660a using,
for example, a sputtering process, and exemplary metals include
platinum, aluminum or gold because they are inert to lithium-based
environments. By first employing such metals to coat the
collections of sensors 630, 640, the metal coating can provide
voltage measurements across the sensor collections 630, 640.
Electrically coupled to the metal sleeves 650a, 660a are conductive
leads 650b, 660b. These conductive leads 650b, 660b also reach the
edge of the separator 620, and are used to transmit readings from
the sensor collections 630, 640, such as voltage detected, to cell
monitoring equipment. As before, the disclosed 3D printing
fabrication process can thus be employed to embed not only the
optical fiber 610, but also the various sensor collections 630,
640, the metal sleeves 650a, 660a, and the conductive leads 650b,
660b, all within a single 3D printing process. FIG. 6B is an inset,
close-up view of two of the collections of sensors 630, 640. Within
each of the metal sleeves 650a, 660a, the four distinct FBG sensors
630a-d, 640a-d can be seen, although any number of sensors may
advantageously be employed to determine the parameter data needed.
As before, as the input light travels through the optical fiber
610, the various sensor collections formed in the fiber core will
refract the light in various manners, and the refractive index of
the FBG sensors can be selected as discussed above so as to detect
various battery cell parameters, such as temperature, strain,
pressure, or any other cell SOH parameter, either now employed in
BMSs or later employed. The wavelengths of light detected from the
light output from the optical fiber after encountering the various
sensor collections can then be processed by cell monitoring
equipment to determine each of the specific parameters for which
sensors have been printed.
[0047] FIG. 7 illustrates an isometric close-up view of a portion
of another exemplary Li-ion cell sensor system 700 fabricated in
accordance with the disclosed principles. As before, this exemplary
system 700 includes an optic fiber 710 printed onto to a Li-ion
cell separator 720. In this embodiment, the optical fiber 710 is
printed having a semi-circular cross-section, as illustrated. FBG
sensor collections 730, 740 are again formed in the optical fiber
710, and similarly have a semi-circular cross section. Conductive
metal sleeves 750a, 760a are again deposited over the sensor
collections 730, 740, with conductive leads 750b, 760b electrically
coupled to the conductive metal sleeves 750a, 760a. FIG. 8
illustrates an isometric close-up view of a portion of another
exemplary Li-ion cell sensor system 800 constructed in accordance
with the disclosed principles, and similar to the system 700 of
FIG. 7. Specifically, this exemplary system 800 again includes an
optic fiber 810 printed onto to a Li-ion cell separator 820, as
well as FBG sensor collections 830, 840 formed in the optical fiber
810. However, this embodiment differs from that of FIG. 7 in that
the optical fiber 810 and sensor collections 830, 840 are printed
having a fully circular cross-section, as illustrated. The
particular shape of the optical fibers and FBG sensor collections
may be selected based on the size and/or type of separator used for
the cell. Thus, any advantageous shape may be employed, which could
include not only the circular/cylindrical and semi-circular shapes
discussed herein, but also triangular, conic and rectilinear shapes
may also be employed. Conductive metal sleeves 850a, 860a may again
be deposited over the sensor collections 830, 840, with conductive
leads 850b, 860b electrically coupled to the conductive metal
sleeves 850a, 860a. Both sensor systems in FIGS. 7 and 8 may again
be embedded on cell separators using a single 3D fabrication
process as disclosed herein, results in significantly simplifying
and reducing the cost and time of fabricating BMS sensors in
batteries.
[0048] Turning now to FIG. 9, illustrated is one embodiment of a
strain measurement system 900 for a Li-ion battery cell constructed
in accordance with the disclosed principles. In this embodiment, a
strain gauge is again printed onto a cell separator 910, but is not
comprised of FBG sensors. Instead, to determine strain on the
specific cell, the strain gauge is formed by printing a thin, e.g.,
about 1 micron in width, trace 920 on the separator 910. As with
the optical sensors discussed above, the strain gauge may instead
be formed on other appropriate layers or components of the cell as
well.
[0049] To form the strain gauge, the trace 920 is then printed in a
zig-zag pattern of parallel lines across an area of the separator
910 proximate the center and outer edge of the separator 910, as
illustrated, since such strain gauges are more sensitive to strain
put on the separator 910 along the lengths of the trace 920. In
addition, the trace 920 is made electrically conductive by
depositing a metal material over the trace 920. As before,
exemplary metals may include platinum, aluminum and gold, since
these metal are inert in a lithium-based environment. In addition,
terminals 930, 940 are formed at the beginning and end of the
conductive trace 920 using the same techniques. By forming the
conductive trace 920 such that the longitudinal lengths of the
trace 920 run back and forth across an area of the separator 910
that includes its center and near its edge, strain on the separator
in the same direction may be detected. More specifically, as an
electrical current is applied to the conductive trace 920 via the
terminals 930, 940, the longitudinal lines of the trace 920 will
have a given electrical resistance. However, if strain is applied
to the separator 910 such that it begins to bend or other flex, so
to do the longitudinal lines of the trace 920. As the longitudinal
lines of the trace 920 so flex, their resistance will change, and
detecting any such change in resistance of the longitudinal lines
of the trace 920 will allow the measurement of strain on the
separator 910, and thus on the cell. Importantly, the disclosed
principles allow for the combination of such an embedded strain
gauge with 3D printed embedded sensors of the type(s) disclosed
herein. Moreover, the fabrication of both this type of strain gauge
and the embedded sensors disclosed herein may be combined into a
single 3D printing process. Thus, as before, using a single 3D
fabrication process as disclosed herein, results in significantly
simplifying and reducing the cost and time of fabricating BMS
sensors in batteries
[0050] Looking briefly at FIG. 10, illustrated is another
embodiment of a strain measurement system 1000 for a Li-ion battery
cell constructed in accordance with the disclosed principles. In
this embodiment, a strain gauge is again printed onto a cell
separator 1010. However, in this embodiment, the separator 1010 is
a rectangular separator 1010, rather than the round separator 910
illustrated in FIG. 9 typically employed in coil style cells.
Despite the printing of the strain gauge on a differently shaped
separator 1010, the strain gauge is formed in the same manner as
discussed above. In this embodiment, the conductive trace 1020 is
again formed to cover an area of the separator 1010 that again
includes coverage proximate to its center as well as proximate to
its edge. Electrical terminals 1030, 1040 are again formed on the
separator 1010 as well, to provide the electrical current to the
strain gauge. Also as before, a single fabrication process may be
employed as disclosed herein to form both the strain gauge and one
or more embedded sensors on the same separator, significantly
simplifying and reducing the cost and time of fabricating BMS
sensors in batteries
Implementation in Battery Management Systems
[0051] Referring now to FIG. 11, illustrated is a block diagram of
a battery management system 1100 implementing sensor systems
fabricated in accordance with the disclosed principles. The system
1100 may be configured to provide both SOH and SOC information for
every individual cell within a battery or battery pack with the
disclosed embedded sensors. Battery management is thereby
simplified and made interactive for a user through the use of a
graphical user interface (GUI) receiving parameter data from
embedded sensors 3D printed as disclosed herein.
[0052] The battery management system 1100 includes a battery 1105
being monitored, as described above. While a single battery 1105 is
illustrated, it should be understood that multiple batteries may
also be included in a management system implementing embedded
sensors fabricated in accordance with the disclosed principles. The
battery 1105 itself is comprised of multiple cells 1110, and again
although only four cells 1110 are illustrated in FIG. 11, an
advantageous feature of the disclosed principles is that any number
cells may be monitored simultaneously and in real-time. To detect
and collect charge and health data from each individual cell 1110,
the dielectric separator 1115 within each cell 1110 is 3D printed
with sensors fabricated as discussed in detail above on the
separator 1115 of each individual cell 1110. Equipment within the
system 1100 is configured to transmit light through the optical
fiber(s) and 3D printing sensor(s) along the fiber(s), and
determine cell parameters based on the shifts in wavelength of the
transmitted light caused by the refractive index(es) of the
sensor(s). The data collected by the received light transmitted
through those embedded sensors can include real-time data regarding
the temperature of each cell 1110, as well as the pressure and
strain placed on each cell 1110. Moreover, the collected data can
include voltage readings on each cell 1110 taken, for example, in
the manner described above, as well as other parameter such as
stress that can affect the SOC or SOH of a cell 1110. The system
1100 would thus include equipment configured to connect to the
metal sleeves formed proximate the sensors along the optical
fiber(s) and take measurements via those electrical interconnects.
The detected and collected data from each of the cells 1110 may be
gathered in a recorder 1120. The recorder 1120 may be comprised as
a single or even multiple pieces of equipment, which may comprise
both hardware and software. In some embodiments, the recorder 1120
may include a database for holding and storing the collected data,
if desired, for later use in addition to the real-time use
discussed herein.
[0053] Once the data is collected by the recorder 1120 from each of
the sensors embedded in each of the cells 1110, that data may then
be provided to an Analysis System 1125 in real-time. The Real-Time
Analysis System 1125 is configured to compile the collected data
1130, and thereby determine the measurements for each applicable
parameter of the cells 1110. More specifically, in this illustrated
embodiment, the Analysis System 1125 is configured to determine,
for each individual cell 1110, four SOH and SOC parameters 1135.
For this embodiment, these include the temperature,
voltage/current, charge capacity, and pressure for each cell 1110.
Each of these parameters 1135 are continuously determined in
real-time for each of the cells 1110 using the disclosed embedded
sensor(s), and collectively they are used for health monitoring of
the battery 1105. During such real-time measuring and determining
of the parameters 1135 for each of the cells 1110, if any of the
parameters 1135 for any particular cell 1110 is determined to be
outside of a predetermined threshold for that parameter, the
Analysis System 1125 may be configured to generate alarms 1140 to
be provided to a user. Exemplary techniques for compiling the
collected data to determine the parameters 1135 for each of the
cells 1110 are discussed in further detail below.
[0054] A monitoring user 1145 may gain access to the results of the
Analysis System 1125 via a host terminal 1155, which may be
directly connected to the Analysis System 1125 or may be connected
via a computer network, such as the Internet. In one such
embodiment, the results provided by the Analysis System 1125 may be
transmitted to the host terminal 1150 as data 1155 via the Internet
or any type of data or computer network. The received data 1155 may
then be displayed to the user on the host terminal 1150 using a
GUI. As the information regarding the various parameters 1135, as
well as any SOH or SOC information, are displayed on the GUI, the
user may then interact with that information using the GUI. For
example, using big data computing the user can be notified by the
display on the GUI of early alert/warning sign(s) of degraded/risky
cell then the user can shut down the system until the cell is
repaired/replaced. To provide detailed information on the SOH of
each of the cells 1110, the Analysis System 1125 provides the
various parameter 1135 data determined for each cell 1110 to the
host terminal. Traditionally, capacity and resistance have been
used as the features to determine the SOH and SOC of lithium-ion
batteries. In conventional approaches, influences such as
temperature, stress/strain, vibration, and un-foreseen usage
profiles inside the battery cell have been used to generate
uncertain SOH predictions. In contrast, the disclosed principles
provide for mathematical algorithms that use the parameter data
generated by the presently disclosed embedded sensors to create a
robust SOH model that will evaluate the health of each individual
battery cell. For example, capacity, resistance, the length of time
of a constant current, the length of time of a constant voltage,
temperature over time, and strain over time may all used as
additional indicators of SOH. Moreover, the accuracy of the SOH
model(s) created using embedded sensors fabricated according to the
disclosed principles increases with the increased number of
measured parameters and calculated factors taken in consideration,
in addition to the ability to gather data from every single cell.
The collected parameter data and equations may then be integrated
into a program for use with the user GUI, which accepts the data,
processes the data using mathematical equations and models, and
then generates the SOH status for each cell for display to the
user.
[0055] Exemplary equations used in the advanced SOH prediction
algorithm(s) that may employ data for the embedded sensors
fabricated as disclosed herein are as follows. The SOH may be
characterized by the Beta function with parameters .alpha. and
.beta.:
f c ( SOH ; .alpha. , .beta. ) = SOH .alpha. - 1 ( 1 - SOH ) .beta.
- 1 B ( .alpha. , .beta. ) ##EQU00001##
The parameters .alpha. and .beta. are then updated by equating the
mean of the Beta function to the weighted mean of the observed
features:
.alpha. .alpha. + .beta. = i = 1 : 6 w i F i i = 1 : 6 w i .alpha.
c = i = 1 : 6 w i c F i c .beta. c = i = 1 : 6 w i c ( 1 - F i c )
##EQU00002##
where the feature vector is:
F.sub.i.sup.c
and where c is the cycle number and i is the feature index. Then
after each cycle, the weights are updated based on each feature's
error from the previous SOH measurement:
w.sub.i.sup.c+1=w.sub.i.sup.c+(1-|SOH.sub.c-F.sub.i.sup.c|)
[0056] From these equations, an advanced modeling of the SOH of
each cell may be created. For the constant current charging (CCCT)
stage and capacity, which typically decrease as cycle number
increases, the SOH is given by:
SOH = F k F avg ( 1 : 5 ) ##EQU00003##
For the constant voltage charging (CVCT) stage and resistance,
which generally increase as cycle number increases, the SOH is
given by:
SOH = ( F k F avg ( 1 : 5 ) ) - 1 ##EQU00004##
The capacity, the resistance, the time spent in the CVCT stage, and
the time spent in the CCCT stage, are all extracted for the data
after a full charge/discharge cycle. FIG. 12 illustrates a plot
1200 of the SOH across charging cycles for each of capacity, CVCT,
resistance and CCCT. Note that the resistance and CVCT are inverted
to ensure features are illustrated as degrading with increased
cycling. The data is then fused to provide an estimated Final SOH
for each battery. Specifically, the Final SOH prediction for each
cell is taken as the value with the highest probability in the Beta
distribution:
SOH.sub.c=argmax(f.sub.c(SOH;.alpha.,.beta.))
Using this Final SOH prediction equation, FIG. 13 illustrates a
plot 1300 of the Final SOH across the cycle curves for three sample
batteries having embedded sensors in each cell as disclosed herein.
However, using the disclosed 3D printing technique for embedding
sensors in each cell separator, more accurate data is provided over
conventional systems that measure less than all of the cells of a
battery, or that measure merely the external parameters of a
battery (i.e., surface temperature). Even as compared to
conventional systems that attempt to provide sensors in each cell
of a battery, the disclosed technique for embedding sensors is
capable of obtaining the same amount of, or even more, data from
each such cell since multiple sensors measuring or detecting
multiple parameters can easily be provided by the disclosed
fabrication technique. Moreover, such advantages are provided at a
fraction of the cost and weight, and in a far less complex
approach, than such conventional approaches.
[0057] In addition to the use of resistance, capacity, voltage and
current parameters to generate the SOH models using the above
equations, temperature and strain parameters may also be employed
in developing SOH models. For example, with regard to strain on
each cell, during each cycle the maximum, minimum, and range of
strain data is collected. This data may also then be processed for
used as a feature for SOH estimation:
f 1 = ( max k avg ( max 1 : 5 ) ) - 1 f 2 = ( range k avg ( range 1
: 5 ) ) - 1 ##EQU00005##
Absolute max strain increases with age, so as before, the plot is
inverted to illustrate a downward trend. The range decreases with
age as the electrode(s) within the cell become unable to cycle as
much lithium during each cycle. Similar equations may be developed
for integrating temperature parameters as a feature for SOH
estimation. The temperature follows continues increase trend as
cycle number increases so it will use this equation:
SOH = ( F k F avg ( 1 : 5 ) ) - 1 ##EQU00006##
[0058] As such, as additional parameters are added to the SOH
modeling technique disclosed herein to build an even more robust
estimation of the SOH of cells and batteries.
[0059] In sum, the principles disclosed herein provide for the
fabrication of compact and robust 3D printed sensing technology on
the separator within each individual battery cell, and
significantly reduce manufacturing steps for the embedding of FBG
and other sensors and gauges inside one or more layers of the cells
without any major hardware modifications. By embedding such sensors
into each cell as disclosed herein, parameter and thus health
monitoring of every cell of a battery pack is provided, versus the
monitoring of a group of cells as found with conventional
approaches. This is the case for even battery packs comprised of
hundreds of cells. The benefit of an embedded sensor or collection
of sensors in every cell is that it allows every cell to be
monitored without having to provide a connection to all the battery
terminals, which is impractical in battery packs consisting of
hundreds of cells. Also, even as compared with conventional systems
that attempt to provide sensors in each cell of a battery, by
simply printing and depositing multiple sensors and gauges
configured to measure a variety of SOH parameters directly on the
Li-ion separators or other advantageous component as disclosed
herein, provide additional parameter data over systems that may
measure every cell of a battery, but are limited in what parameters
can be monitored for each cell by the size, cost and/or weight of
conventional sensors or sensor systems. And the cost for providing
such additional monitoring of every cell of an embedded sensor
system as taught herein is a fraction of the cost for conventional
battery management systems no matter how many cells such
conventional sensor systems can monitor. Moreover, although every
cell in a battery pack will have health monitoring using the
printed sensors and gauges of the disclosed principles, almost any
weight added to the overall battery pack will typically be
negligible. Only the weight of the printed materials used to form
the sensors and gauges is added to the pack, which is only a
marginal increase in overall pack weight. Still further, monitoring
and maintenance of every cell in accordance with the disclosed
principles is done in real-time, and allows for the calculating, as
well as the modeling for presenting to a user, of not only the SOH
of each individual cell, but also the Final SOH of the battery pack
comprising those cells. By determining the SOH of cells and battery
packs in the disclosed manner, faults can be mitigated and
flammability of battery eliminated with minimal to no uncertainty
since every cell is monitored individually, and this is done so in
a much simpler, faster, less expensive, and with less weight than
the same determination of SOH by conventional systems.
Silica-Based Ink
[0060] In addition to the disclosed technique of embedding 3D
printed sensors on one or more layers within battery cells, there
may still be issues that arise with 3D printing with such cells.
Specifically, some of the problems that can arise with such
printing of embedded sensors include the highly volatile
environment that often occurs within lithium-ion cells. In
addition, lithium-ion battery cells need to be hermetically sealed
for good performance, and in most implementations the surface
area(s) suitable for the 3D printing of the disclosed embedded
sensors is quite small. Each of these factors weigh on not only the
type of 3D printing technology that may be employed in accordance
with the disclosed sensor embedding technique, but also the type of
ink that may be used for this 3D printing of sensors.
[0061] As discussed above, aerosol jet technology can provide 3D
printing of disclosed sensor components on the order of just a few
microns in size. However, the volatile nature inside the battery
cells remains a concern. In accordance with the principles
disclosed above, optical based sensors are embedded on one or more
of the layers within the battery cells since optical-based sensors
have inert properties that will not react with the internal cell
environment. However, conventional inks suitable for aerosol jet
printing technology do not have sufficiently viable optical
properties for use in creating the embedded optical-based sensors
disclosed herein. Moreover, aerosol jet 3D printing is a
non-contact process capable of printing nano-ink patterns on
conformal and flexible surfaces. Aqueous or solvent nano-inks are
pneumatically atomized by the flow of nitrogen gas. The flow of
atomizing gas into and out of the cup leads to evaporation and
removal of volatile solvent(s). As the solid loading fraction of
the ink increases, the rheological changes can lead to
instabilities and non-uniformity in the print output. Therefore,
the quality of the deposition highly depends on the quality of the
ink in addition to the optimization of printing parameters.
[0062] To address these concerns of nano-size patterns and the
deficiencies of conventionally available 3D printing inks, the
disclosed principles further provide a silica-based ink comprising
silica (SiO.sub.2) powder that can be used in the manufacturing
process of the disclosed optical sensors and any other embedded
components that not only require inert properties, but that
provides a sufficient level of optical properties so that the
embedded sensors can sufficiently function as optical sensors.
While a variety of different materials can be 3D printed with the
aerosol jet deposition technology, for good quality deposition
specific for use as optical sensors as disclosed herein, the ink
must be optimized before used in the sensor manufacturing
process(es) discussed herein. For example, conventionally available
nano-inks on the market and capable of deposition using aerosol jet
technology include metal-, non-metal-, dielectric-, adhesive-, and
semiconductor-based inks. However, none of these inks provide the
sufficient optical properties for use with the embedded sensors of
the disclosed principles, while maintaining high quality deposition
detail.
[0063] Moreover, in order to build the 3D optical-based structures
disclosed herein with aerosol jet additive manufacturing technology
in-situ during the battery cell manufacturing process, UV curing of
the 3D deposited material is an advantageous property. Therefore,
in the development of the disclosed inks one of the requirements
was to include a photopolymer based solvent that allows in-situ
curing of the deposition to be very fast, as well as provide
optical properties needed for the 3D printed optical fibers and
sensors disclosed herein. Indeed, selected photopolymer solvents
for use in silica-based inks according to the disclosed principles
ideally should have greater photo properties than polymer based
properties.
[0064] An exemplary ink mixture according to the disclosed
principles contains silicon dioxide (SiO.sub.2), also called
"silica," added to the photopolymer solvent. It is commonly known
that silica is used to form glass and other objects that have
excellent optical properties, as needed for the optical-based
sensors disclosed herein. However, while the optical properties of
an ink entirely made from silica would certainly be advantageous
from an optical property view, silica alone is not readily
deposited using any 3D printing technology, and furthermore does
not cure in an in-situ process. This is the case because in its
natural state, silica exists as a solid powder. Thus, a solvent is
added to the disclosed silica-based ink recipes to permit 3D
printing with the mixture, as well as in-situ curing of the printed
optical elements disclosed above. However, simply adding a
photopolymer solvent is not sufficient. More specifically, for use
in aerosol jet 3D printing equipment, a specific viscosity for the
ink is preferred and advantageous at the range between about 75-100
cP (centipoise). Although aerosol jet printing equipment may
typically handle viscosities up to 1000 cP, the disclosed range of
viscosities of the disclosed silica-based ink has been shown to
achieve excellent results within the range of 50-200 cP.
Accordingly, not only must minimum optical properties be maintained
for the printed optical elements to function as sensors as
disclosed herein, but a precise range of viscosity for the ink must
be maintained while also permitting in-situ curing of the printed
structures so as not to overly delay the battery cell manufacturing
process when the disclosed sensors are embedded.
[0065] In one embodiment of a silica-based ink, the disclosed
principles combine about 2% weight by volume of silica with 98%
photopolymer solvent having an individual viscosity of about 30-55
cP (typically a measured average of 45 cP). For example, in one
exemplary mixture, 49 g of commercially available solvent NOA 84
was combined with 1 g of silica powder. Since silica is a solid
powder, its addition to a solvent will raise the solvent's initial
viscosity significantly. In this exemplary mixture, for each 1 g of
silica powder added to the 49 g of this particular solvent, the
viscosity of the ink mixture was raised to about 86 cP. FIG. 14
illustrates a plot 1400 of viscosity vs. shear rate for both the
NOA 84 solvent alone and a mixture of this photopolymer solvent
with silica powder in these proportions. From the measurements
plotted in FIG. 14, it is demonstrated that even though silica is
introduced to the solution and it doubles the initial viscosity of
the solvent to about 86 cP, the resulting viscosity of this
exemplary ink mixture is viable for 3D printing with the aerosol
jet additive manufacturing process discussed herein. Additionally,
such components can be slightly altered to tailor the final ink
mixture with varying amounts of silica for other applications, but
still useable with aerosol jet deposition equipment by keeping the
ink mixture at a useable final viscosity.
[0066] Sample depositions were made using glass as a substrate for
both the NOA 84 solvent alone and for the disclosed ink mixture
using the same proportion of silica in order to compare the
viability of the two inks. Operating parameters for the aerosol jet
equipment were: step size of 50 .mu.m, 7 mm/s deposition speed,
flow parameters set as 3, 1250, 1300 ccm, standoff distance between
the nozzle and substrate at approximately 4 mm, and a nozzle size
of 200 microns. As an initial distinction, the disclosed
silica-based ink was deposited in three layers, with each of the
three layers UV-cured immediately after deposition in order to
achieve a final thickness of 30 microns. The NOA 84 alone was also
deposited on a glass substrate using same operating parameters, but
was not immediately curable as discussed above. Characteristics of
both depositions were examined and are discussed below.
[0067] FIG. 15A provides a scanning electron microscope (SEM) image
1500 of the NOA 84 deposition alone, which shows the expected
uniform topology of the solvent alone. FIG. 15B provides an
electron dispersive spectroscope (EDS) analysis graph 1550 of NOA
84 deposition alone, which reveals the carbon (C) and oxygen (O)
components of the deposited solvent. However, despite the uniform
topography, the optical properties of the solvent alone is not
sufficient for use as the optical elements disclosed herein. FIG.
16A provides an SEM image 1600 of the disclosed ink mixture of the
NOA 84 with silica powder, again in the proportions discussed
above. Advantageously, this SEM image 1600 reveals the disclosed
ink mixture maintains a uniform topography, although with the
silica powder evenly disbursed throughout the deposition. The
uniform disbursement of the silica within the solvent provides a
uniform increase in the optical properties above the NOA 84 solvent
deposition alone, despite both depositions providing for a uniform
distribution and topography. FIG. 16B provides an EDS analysis
graph 1650 of the disclosed ink mixture of NOA 84 mixed with
silica, and the presence of the silicon (Si) is confirmed by the Si
pick in the EDS scan. It is noted that both EDS analyses (1550,
1650) demonstrate gold (Au) picks, and these are a result of very
thin gold layer deposited on each sample by sputtering technique in
order to be able to view the samples under SEM. However, the
presence of the gold can be omitted as far as sample quality and
content is concerned.
[0068] In other embodiments of silica-based ink mixtures created in
accordance with the disclosed principles, an alcohol-based agent
may be added to the ink mixture. In such exemplary embodiment of a
silica-based ink, the disclosed principles combine 49 g of NOA 84
solvent with 1 g of silica powder, and with the addition of 10 g of
Terpineol as the alcohol. Thus, the alcohol in this embodiment
comprises about 16.67% weight by volume of ink mixture. As
discussed above, the addition of silica to the HOA 84 solvent
raises the solvent's initial viscosity significantly. But then the
further addition of Terpineol, or any other appropriate
alcohol-based agent, will decrease the overall viscosity of the ink
mixture. As a result, the amount of alcohol used in a given
silica-based ink mixture as disclosed herein may be adjusted so as
to adjust the overall viscosity of the ink mixture. In this
exemplary mixture, since the same 1 g of silica powder is added to
the same 49 g of NOA 84 is used, the viscosity of the ink mixture
is about 86 cP before the addition of the alcohol. Then after the
addition of the 10 g of Terpineol, the final overall viscosity of
the resulting disclosed ink mixture is about 65 cP. Stated another
way, in this exemplary ink mixture, the total of 60 g of mixture
comprises about 81.667% NOA 84 (49 g), about 1.667% silica powder
(1 g), and about 16.667% Terpineol (10 g). Such ability to decrease
the viscosity of the final ink mixture in the disclosed manner is
advantageous in cases where processing techniques other than
aerosol jet are employed.
[0069] FIG. 17 illustrates a plot 1700 of viscosity vs. shear rate
for the NOA 84 solvent alone, the above-discussed ink mixture of
this photopolymer solvent with silica powder in the above-mentioned
proportions, and then an ink-based mixture adding 10 g of Terpineol
to the initial silica-based mixture. From the measurements plotted
in FIG. 17, it is demonstrated that the alcohol-based agent added
to the silica-based mixture results in an overall viscosity of
about 65 cP. Additionally, the substantially uniform viscosity of
this alcohol-added silica-based ink mixture across the range of
shear rate is a further advantageous characteristic. Also, the
amount of Terpineol, or other alcohol-based agent, may be adjusted
to again tailor the desired viscosity of the silica-based ink
mixture. For example, if increased optical properties are desired
above the exemplary mixtures discussed above, additional silica
powder may be added to the same photopolymer solvent. However,
while the density of silica disbursed throughout the mixture
increases, thus increasing optical properties, such increase in
silica proportionally increases the overall viscosity of the ink
mixture. Accordingly, the amount of Terpineol may also be increased
to bring the overall viscosity of the ink mixture back down to a
desired level.
[0070] In the numerous embodiments of the inventive subject matter
disclosed herein, such embodiments may be referred to herein,
individually and/or collectively, by the term "invention" merely
for convenience and without intending to voluntarily limit the
scope of this application to any single invention or inventive
concept if more than one is in fact disclosed. Thus, although
specific embodiments have been illustrated and described herein, it
should be appreciated that any arrangement calculated to achieve
the same purpose may be substituted for the specific embodiments
shown. This disclosure is intended to cover any and all adaptations
or variations of various embodiments. Combinations of the above
embodiments, and other embodiments not specifically described
herein, will be apparent to those of skill in the art upon
reviewing the above description.
[0071] It is submitted with the understanding that it will not be
used to interpret or limit the scope or meaning of any claims
issuing from this disclosure. In addition, in the foregoing
Detailed Description, it can be seen that various features are
grouped together in a single embodiment for the purpose of
streamlining the disclosure. This method of disclosure is not to be
interpreted as reflecting an intention that the claimed embodiments
require more features than are expressly recited in each claim.
Rather, as any such issuing claims reflect, inventive subject
matter lies in less than all features of a single disclosed
embodiment.
[0072] The description has made reference to several exemplary
embodiments. It is understood, however, that the words that have
been used are for description and illustration, rather than words
of limitation. Changes may be made within the purview of the
appended claims, as presently stated and as amended, without
departing from the scope and spirit of the disclosure in all its
aspects. Although this description makes reference to particular
means, materials and embodiments, the disclosure is not intended to
be limited to the particulars disclosed; rather, the disclosure
extends to all functionally equivalent technologies, structures,
methods and uses such as are within the scope of any claims issuing
from this disclosure.
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