Abstract

Due to the necessity for flexibility without compromising the Li-ion battery (LIB) state of health (SOH), LIB is a critical challenge for flexible hybrid electronic (FHE) devices. A thin form factor-based LIB with a thickness of less than 1 mm is regarded as the candidate material to suit such demands since it can be folded, bent, and twisted with minimal performance loss. Furthermore, LIB has high specific power (W/Kg) and specific energy (Wh/Kg), as well as a smaller memory effect, making it more appealing for wearable applications. While much research has been done on the chemo-physical effects of repeated charging and discharging LIB, such as solid electrolyte interphase (SEI) development, material deterioration, and so on, but such impacts owing to repeated flexure LIB have not been much studied. The deterioration of the reliability of thin-flexible power sources was investigated in this work under twist, flexing, and flex-to-install to simulate stresses of daily motions of the human body by utilizing motion-control setups in a lab setting. Furthermore, an AI-based regression model has been developed to forecast the SOH of the battery based on many variables such as physical, atmospheric, and chemo-mechanical experimental circumstances that may be difficult to address by manpower. Based on the various variables and their interactions, the generated models are expected to be used to predict battery life and assess the acceleration factors between test circumstances and usage conditions for a range of test scenarios.

References

1.
Hu
,
L.
,
Wu
,
H.
,
La Mantia
,
F.
,
Yang
,
Y.
, and
Cui
,
Y.
,
2010
, “
Thin, Flexible, Secondary Li-Ion Paper Batteries
,”
ACS Nano
,
4
(
10
), pp.
5843
5848
.10.1021/nn1018158
2.
Li
,
N.
,
Chen
,
Z.
,
Ren
,
W.
,
Li
,
F.
, and
Cheng
,
H.
,
2012
, “
Flexible Graphene-Based Lithium-Ion Batteries With Ultrafast Charge and Discharge Rates
,”
Proc. Natl. Acad. Sci. U. S. A.
,
109
(
43
), pp.
17360
17365
.10.1073/pnas.1210072109
3.
Li
,
L.
,
Wu
,
Z. P.
,
Sun
,
H.
,
Chen
,
D.
,
Gao
,
J.
,
Suresh
,
S.
,
Chow
,
P.
,
Singh
,
C. V.
, and
Koratkar
,
N.
,
2015
, “
A Foldable Lithium-Sulfur Battery
,”
ACS Nano
,
9
(
11
), pp.
11342
11350
.10.1021/acsnano.5b05068
4.
Lall
,
P.
, and
Zhang
,
H.
,
2017
, “
Test Protocol for Assessment of Flexible Power Sources in Foldable Wearable Electronics Under Stresses of Daily Motion During Operation
,” 2017 IEEE 67th Electronic Components and Technology Conference (
ECTC
), Orlando, FL, May 30–June 2, pp.
804
814
.10.1109/ECTC.2017.301
5.
Lall
,
P.
,
Abrol
,
A.
,
Leever
,
B.
, and
Marsh
,
J.
,
2018
, “
Effect of Shallow Cycling on Flexible Power-Source Survivability Under Bending Loads and Operating Temperatures Representative of Stresses of Daily Motion
,” 2018 IEEE 68th Electronic Components and Technology Conference (
ECTC
), San Diego, CA, May 29–June 1, pp.
2351
2358
.10.1109/ECTC.2018.00354
6.
Pinson
,
M. B.
, and
Bazant
,
M. Z.
,
2013
, “
Theory of SEI Formation in Rechargeable Batteries: Capacity Fade, Accelerated Aging, and Lifetime Prediction
,”
J. Electrochem. Soc.
,
160
(
2
), pp.
A243
A250
.10.1149/2.044302jes
7.
Jagannadham
,
K.
,
2016
, “
Thermal Conductivity and Interface Thermal Conductance of Thin Films in Li-Ion Batteries
,”
J. Power Sources
,
327
, pp.
565
572
.10.1016/j.jpowsour.2016.07.098
8.
Choi
,
Y.
,
Ryu
,
S.
,
Park
,
K.
, and
Kim
,
H.
,
2019
, “
Machine Learning-Based Lithium-Ion Battery Capacity Estimation Exploiting Multi-Channel Charging Profiles
,”
IEEE Access
,
7
, pp.
75143
75152
.10.1109/ACCESS.2019.2920932
9.
Lall
,
P.
,
Thomas
,
T.
,
Narangaparambil
,
J.
,
Goyal
,
K.
,
Jang
,
H.
,
Yadav
,
V.
, and
Liu
,
W.
,
2020
, “
Correlation of Accelerated Tests With Human Body Measurements for Flexible Electronics in Wearable Applications
,”
19th IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems
, Orlando, FL, July 21–23, pp.
877
887
.10.1109/ITherm45881.2020.9190514
10.
Naoki
,
N.
,
Wu
,
F.
,
Lee
,
J.
, and
Yushin
,
G.
,
2015
, “
Li-Ion Battery Materials: Present and Future
,”
Mater. Today
,
18
(
5
), pp.
252
264
.10.1016/j.mattod.2014.10.040
11.
Lall
,
P.
,
Soni
,
V.
,
Abrol
,
A.
,
Leever
,
B.
, and
Miller
,
S.
,
2019
, “
Effect of Shallow Charging on Flexible Power Source Capacity Subjected to Varying Charge Protocols and C-Rates
,” 18th IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (
ITherm
), Las Vegas, NV, May 28–31, pp.
198
203
.10.1109/ITHERM.2019.8757361
12.
Tan
,
C. M.
,
Singh
,
P.
, and
Chen
,
C.
,
2020
, “
Accurate Real Time on- Line Estimation of State-of-Health and Remaining Useful Life of Li Ion Batteries
,”
Appl. Sci.
,
10
(
21
), p.
7836
.10.3390/app10217836
13.
Marano
,
V.
,
Onori
,
S.
,
Guezennec
,
Y.
,
Rizzoni
,
G.
, and
Madella
,
N.
,
2009
, “
Lithium-Ion Batteries Life Estimation for Plug-in Hybrid Electric Vehicles
,”
2009 IEEE Vehicle Power and Propulsion Conference
, Dearborn, MI, Sept. 7–10, pp.
536
543
.10.1109/VPPC.2009.5289803
14.
Ecker
,
M.
,
Gerschler
,
J. B.
,
Vogel
,
J.
,
Käbitz
,
S.
,
Hust
,
F.
,
Dechent
,
P.
, and
Sauer
,
D. U.
,
2012
, “
Development of a Lifetime Prediction Model for Lithium-Ion Batteries Based on Extended Accelerated Aging Test Data
,”
J. Power Sources
,
215
, pp.
248
257
.10.1016/j.jpowsour.2012.05.012
You do not currently have access to this content.