Fast Charging Strategy Optimization Based
on Electrochemical Model and Dynamic
Programming for a Lithium Ion Battery Cell
Meng Xu, Graduate Student
Xia Wang, Professor
Department of Mechanical Engineering
Oakland University, Rochester, MI
October 4, 2018
Enabling Li-ion Battery Fast Charge?
2
“Range Anxiety” Fast Charge
Challenges of Fast Charge
3
Fast Charge
High temperature Thermal runawayHeat generation
SEI growth Degradation / Capacity fade
Li plating
Charging Strategy Review
4
Constant Current Constant Voltage (CCCV) Charging
A123 26650 LFP Cell Data
Charging Strategy Review
5
• Decrease charging time• Low temperature rise• High charging efficiency
Multistage Constant Current Charging (MCC) (Vo et al. 2014)
Source: T.T. Vo, X. Chen, W. Shen, A. Kapoor, New charging strategy for lithium-ion batteries based on the integration of Taguchi method and state of charge estimation, J. Power Sources 273 (2015) 413-422
Objective
6
• To study the effect of charging protocol on capacity fade and
thermal behavior by developing an electrochemical-thermal-
capacity fade coupled model
• To optimize the charging protocol based on Dynamic
Programming optimization algorithm
Methodology
7
Multi-Step Fast Charging
Protocol
Electrochemical-Thermal-Capacity
Fade Coupled Model
SEI Increase Capacity Fade Li Dendrites Temperature Charging Energy
Efficiency
Dynamic Programming (DP)
Optimization Algorithm
Methodology
8
Model Validation
9
A123 2.3 Ah LFP 26650
MACCOR system 4200
Battery test equipment
Source: T.T. Vo, X. Chen, W. Shen, A. Kapoor, New charging strategy for lithium-ion batteries based on the integration of Taguchi method and state of charge estimation, J. Power Sources 273 (2015) 413-422
15 minutes / 20% ~ 80% SOC Fast Charging Protocols
10
Impact of Cycle Number and Protocol on Capacity Fade
11
• Low-High charging protocols obtain lower capacity fade than High-Low protocols• The 2-step Low-High protocol results in the lowest capacity fade
Dynamic Programming (DP) Optimization
12
0%
32%
48% 48%
64%
16%
32%
64%
80%
48%
Operating Conditions: Charging SOC = 0% ~ 80% Charging time = 30 mins ∆𝑡 = 10 mins Charging step = 3 Charging current
= 0.96C, 1.92C, 2.88C ∆SOC = 16% (0.96C)
Goal: m𝒊𝒏 𝑻(𝟑𝟎𝒎𝒊𝒏, 𝟖𝟎%)
Constrains: 𝑻 < 𝑻𝒎𝒂𝒙, 𝒄𝒆𝒍𝒍
SOC < 80%
𝑻, 𝒕, 𝑺𝑶𝑪𝒊
6 by 4 solution matrix
10 min 30 min20 min0 min
1 2 3 4
1
2
3
4
5
6
𝑻, 𝒕, 𝑺𝑶𝑪𝒊, 𝑺𝑶𝑪𝒊−𝟏
𝟑𝟎𝟓𝑲, 𝟏𝟎, 𝟒𝟖%, 𝟎%
Compare
𝟑𝟏𝟎𝑲, 𝟐𝟎, 𝟒𝟖%, 𝟑𝟐%
𝟑𝟏𝟐𝑲, 𝟐𝟎, 𝟒𝟖%, 𝟏𝟔%
𝑻, 𝟑𝟎𝒎𝒊𝒏, 𝟖𝟎%,64%
Capacity Fade Optimization
13
SEI Potential Optimization
14
Temperature Rise Optimization
15
Optimization at Different Ambient Temperatures
16
Conclusions
17
• An electrochemical-thermal-capacity fade coupled model for a Li-ion battery cell is developed using COMSOL Multiphysics
• The effect of fast-charging protocol on capacity fade with charging-discharging cycles is studied
• A Dynamic Programming Optimization algorithm is developed using COMSOL Livelink - MATLAB to optimize the fast charging protocol
• The cost function include capacity fade, SEI potential, and temperature rise.
Thank you!
Acknowledgement
18
Dr. Benjamin Reichman (BASF Battery Materials - Ovonic)
Enabling Li-ion Battery Fast Charge?
19Source: https://techflourish.com
1% market share
• Cost• “Range anxiety”
Fast charging Li-ion batteries …
Typical Lithium Ion Cells
20
Coin/Button Cell
Cylindrical Cell
Prismatic Cell
Pouch Cell
Load
Positive
Li+
Li+
Lithium Ion Electrochemical Cell
e-
Positive Electrode:
𝐿𝑖𝑥𝐶6𝐷𝑖𝑠𝑐ℎ𝑎𝑟𝑔𝑒
𝒙𝑳𝒊+ + 𝒙𝒆− + 𝐶6
𝐿𝑖1−𝑥𝑀𝑂2 + 𝑥𝐿𝑖+ + 𝑥𝑒−𝐷𝑖𝑠𝑐ℎ𝑎𝑟𝑔𝑒
𝐿𝑖𝑀𝑂2
Negative Electrode:
Separator Negative
e-
I I
I
Cu
rren
t C
oll
ecto
r
Cu
rren
t C
oll
ecto
r 𝐿𝑖𝑀𝑂2
𝐶6
Electrolyte
Al foil
Cu foil
21
Typical Lithium Ion Battery Models
22
Predictability
CP
U T
ime
Li+rprn
Discharge
r
x
x r
P2D Electrochemical Model
23
𝑥𝐿𝑝𝑜𝑠 𝐿𝑠𝑒𝑝 𝐿𝑛𝑒𝑔
𝑥 = 0𝑟 𝑟
e-
Separator Negative Electrode
I
Cu
rren
t C
olle
cto
r
Cu
rren
t C
olle
cto
r
Load
Charge Conservation in x: 𝛻 ∙ 𝒊𝑙 = 𝛼𝑣𝑖𝑙𝑜𝑐𝛻 ∙ 𝒊𝑠 = −𝛼𝑣𝑖𝑙𝑜𝑐;𝛻 ∙ 𝒊𝑠 + 𝛻 ∙ 𝒊𝑙 = 0;
Mass Conservation in x: 𝜖𝑙𝜕𝑐𝑙𝜕𝑡
+ 𝛻 ∙ 𝑵𝑙 =𝛼𝑣𝑖𝑙𝑜𝑐𝐹
Mass Conservation in r:𝜕𝑐𝑠𝜕𝑡
+ 𝛻 ∙ −𝐷𝑠𝜕𝑐𝑠𝜕𝑟
= 0
Electrochemical Kinetics: 𝑖𝑙𝑜𝑐 = nF𝑘0𝑐𝑙𝑐𝑠𝛼𝑎(1 − 𝑐𝑠,𝑚𝑎𝑥)
1−𝛼𝑎 𝐶𝑅𝑒𝑥𝑝𝛼𝑎𝐹𝜂
𝑅𝑇− 𝐶𝑂𝑒𝑥𝑝
−𝛼𝑐𝐹𝜂
𝑅𝑇
∅𝑠(𝑥, 𝑡)∅𝑙(𝑥, 𝑡)
c𝑠(𝑟, 𝑡)c𝑙(𝑥, 𝑡)
𝐿𝑖1−𝑥𝑀𝑂2 + 𝒙𝑳𝒊+ + 𝒙𝒆−𝐷𝑖𝑠𝑐ℎ𝑎𝑟𝑔𝑒
𝐿𝑖𝑀𝑂2
e-e-
Electrolyte
Positive Electrode
𝒊𝒔
e-
Li+Li+e-
𝐿𝑖𝑥𝐶6𝐷𝑖𝑠𝑐ℎ𝑎𝑟𝑔𝑒
𝒙𝑳𝒊+ + 𝒙𝒆− + 𝐶6
e-Li+ Li+
e-
Li+
𝒊𝒍
Li+e- 𝛻 ∙ 𝒊𝑠
𝛻 ∙ 𝒊𝑙
𝑖𝑙𝑜𝑐
𝑟
Thermal Model
24
Capacity Fade Model
25
Source: Ekström, Henrik, and Göran Lindbergh. "A model for predicting capacity fade due to SEI formation in a commercial graphite/LiFePO4 cell." Journal of The Electrochemical Society 162, no. 6 (2015): A1003-A1007.
• In addition to the main graphite-lithium intercalation reaction on the negative electrode, the parasitic lithium/solvent reduction reaction is also included in the model:
15 min 20 ~ 80% SOC Fast Charging Cycles
26
SEI Thickness Increase Cycle 1 – Cycle 3
27
• SEI increases with cycles• Low-High protocols have thinner SEI at cycle 3
Low-High
High-Low
Impact of Cycle Number and Protocol on Capacity Fade
28
• Low-High charging protocols obtain lower capacity fade than High-Low protocols• The 2-step Low-High protocol results in the lowest capacity fade • Utilization range shifts in the negative electrode
Optimization at Different Ambient Temperatures
29
Top Related