1. Dr. Song-Yul Choe
Professor
Auburn University

2. High Resolution Modeling of Lithium Ion Battery and its Applications
Auburn University Mechanical engineering
Advanced Propulsion Research Lab. Song-Yul (Ben) Choe

3. Trend of advanced propulsion systems

4. Energy storage with battery
Nominal Capacity (Amp-hours): 15.7
Nominal Cell Voltage 3.73
Cell Dimensions (mm) 5.27
Cell Dimensions w/ terminals (mm) X 249.6
Maximum Cell Temperature (°C) 75
Positive Lithium Metal Oxide
Negative Carbon
Electrolyte Organic Material
Separator SRS

5. Typical models for battery
Models base on equivalent electrical circuit
Statics: resistors in series to a voltage source
Dynamics: a capacitor connected in parallel to a resistor
Ignored effects :
Electrical behavior of the terminal as a function of SOC , T and material degradation, and OCV as a function of hysteresis and SOC.
Battery calendar life as a function of cycles and load profile
Heat generation as a function of SOC , change of entropy and I (charge and discharge), heat transfer
Various temperature effects caused by gradients of ion concentrations and side reactions

6. Modeling of LiPB cell ce Φe Φs ηSEI T cs Y Separator LixC6 LiyMO2
Current collector (Cu)
Current collector (Al)
Electrolyte
Positive electrode area
Negative electrode area
Electrode particle L T X

7. Principle: Current, Concentration and State of Charge
Current in micro cell
current =
Electron current - + -
Ion current + - +
Credit: huangqing
SOC (state of charge) and cs (concentration in solid) - + - + - +
Low SOC
Medium SOC
charging
High SOC
Credit: huangqing

8. Electrochemical Thermal Mechanical Model
Charging and discharging processes: Heat generation, Elasticity and Degradation
Multi scale and Multi-physics coupled problems

9. Overview of model Single cell model Initial conditions: Initial SOC
Load profile
Initial temperature distribution
Ambient temperature
Cell voltage
Temp. distribution
SOC
Overpotentials
Reaction rate
Concentration
Efficiency
Energy conservation
Heat transfer
Charge conservation
Temperature distribution
Potential distribution
Micro cell model
Micro cell model
Micro cell model
Butler-Volmer
Heat source
Parameters:
Battery geometry
Maximum capacity
Concentration
Activity coefficient
Diffusion coefficient
Change of enthalpy
Conductivity
etc.
Reaction rate
Standard potential
Current
Overpotential
Nernst equ.
Mass balance
In electrolyte
In solid
Concentration

10. Static and dynamic behavior of the battery
Static and dynamic behavior of the battery
Characteristics at different current rates (T=300K and SOC=100%)

11. Transient behavior of ion concentration (Discharging behavior at a step current of 10C)
At 1sec
At 80 sec
At 20 sec
At 180 sec
As lithium ion leaves from negative electrode and deposited in positive electrode, concentration at the interface of the negative electrode drops rapidly when compared with that of inners, while opposite phenomena occurs in the positive electrode.

12. Potentials/Current density at positive and negative current collector

13. Validation of a single pouch cell at 1C/2C/5C discharge/charge

14. Thermal validation – 5C cycle 2D

15. Heat generation using the model and calorimeter

16. Measurement of Thickness
4/10/2017
Measurement of Thickness
The change of battery thickness caused by the volume change of electrodes is calculated by the model.
In experiment, thickness of the battery is measured by measuring both sides of the battery during cycling.

17. Mechanical stress of cells at 0.5C, 1C and 2C cycling
4/10/2017
Mechanical stress of cells at 0.5C, 1C and 2C cycling

18. 4/10/2017
Maximum Stress as a Function of Position during discharge (at one instant)
Separator
Anode current collector
Cathode current collector
The plotted stress at each position is the maximum value of the stress in the local electrode particle.
The highest stress is found in the electrode near the separator.

19. Fracture is Observed near the Separator
4/10/2017
Fracture is Observed near the Separator
Q. Horn and K. White, 2007 [8]
J. Christensen, 2010 [7]
Other researchers took SEM images at the cross-section of cell, where fractures are found in the electrode near the separator [7] [8].
Our simulation shows that the highest stress locates at the electrode near the separator, where fractures are most likely to happen.

20. Block Diagram for battery management system (BMS)
Block Diagram for battery management system (BMS)
Battery
Pack/Module
SENSOR
Current
Voltage
Temperature
Predefined Map
Ri(SOC)
Ri(Charging)
TRAY Temp.
Voc(SOC)
Voc(Charging)
Cooling Control
Thermal Management
Imean
Charging/Discharging Control
Aging Coefficient &
SOC Calculation
Accumulated SOC Error Comp.
HCU
I,V(SOC)
Vaverage &
Temp.
Compensation
Health monitoring & Protection
Temperature
Charging/Discharging power
User
Interface
Voltage Imbalance detection
Diagnosis
Search IVSOC by
IV Voltage MAP

21. Review of models for Battery
High
Intermediate
Low
Improvement of cell designs
Full order of Electrochemical, thermal and mechanical Model (ETMM: FOM): Electrochemical kinetics, Potential theory, energy and mass balance, and charge conservation , Ohm’s law, Empirical OCV and elasticity
BMS Functionalities
Reduced order of Electrochemical thermal Model (ETM: ROM ): Empirical OCV
Polynomial, State space, Páde approx., POD, Galerkin Reformulation and others
Electric equivalent circuit Model (EECM): Randles models with the 1st, 2nd and 3rd order
Empirical Model:
Peukert’s equation
Comp. time
Accuracy
Low Moderate High

22. Reduced order of the model (ROM) for real time applications
Parameters:
Cell geometry
Kinetic and transport properties
Initial conditions:
Terminal voltage
Load profile
Ambient temperature
Cell voltage
Temperature
SOC
Ion concentration in electrolyte Ce
Ion concentration in electrodes Cs
Potentials Φ
SOC estimation
Input:
Output:
Battery :
Steps
Approaches
Results
Order reduction
Ce  State space approach
Cs  Polynomial approach
Φ  Parameters simplification
Higher accuracy with less computational time
Implicit method to solve PDEs
Optimization of the ROM for real time applications

23. Validation of the ROM 1. Test condition: 2. Test condition:
Mode: Depleting
Cycle #: 5
Temperature: 0ºC, 25ºC, 45ºC
Current: 1C, 2C, 5C
Initial SOC: 0%
2. Test condition:
Mode: Depleting
Cycle #: 2
Temperature: 25ºC
Current: 1C, 2C, 5C
Initial SOC: 0%

24. SOC estimation using Extended Kalman Filter
Error of SOC 7-10%
Initial errors of BMS
Feedback controls and real time model
Output:
Battery
Measurement update
Time update with the ROM
SOC calculation
Input:

25. Results of the estimation based on ROM + EKF
Current: Voltage: SOC:
Current: Voltage: Error of SOC:
Test condition:
Mode: JS
Temperature: 25ºC
Initial SOC: 100%
Initial error: 0.2V
(30% SOC)
Test condition:
Mode: Depleting
Temperature: 25ºC
Initial SOC: 0%
Initial error: 0.5V
(6.5% SOC)

26. Health monitoring of battery
SOH
SOHQ
SOHP
Capacity fade
Power fade
Other mechanism
Research interests for SOH
SOH
Current i
Battery pack
ROM Model
&
SOH detection algorithm
Output states value
( V T )
States estimation
(Vt SOC T )
Compare
Aging parameters estimation
( as ɛs )
error

27. 4/10/2017
Estimation of SOHQ
The simulation of Qmax is calculated by the semi-empirical model whose aging parameters are obtained from curve fitting.

28. Fast charging: limiting factors
Fast charging: limiting factors
The reaction on the negative electrode is described as:
When operated improperly, Li-ions are deposited on the anode surface instead of intercalating during charging:
Reference: C. J. Mikolajczak, J. Harmon, From Lithium plating to Lithium –ion cell runaway Exponent [Ex(40)]annual report, 2009
Observed Li plating
Cause of Lithium plating:
Large current rate during charging, especially at high Li ion concentration
Low temperature
Effects of Lithium plating:
Capacity
Irreversible loss of active Lithium
Safety
Dendrites can cause shorting within the electrodes
Heat generation
A mat of dead lithium and dendrites can increase the chances minor shorts will lead to thermal runway

29. Comparison of simulation results and experimental results: Charging
Test condition:
Temperature=25°C
Initial Vt= 2.9V
Charge current: 1C/2C/5C rate
Surface Concentration (mol/cm3)
Terminal Voltage (V)

30. New Charging method - Battery i(t) + ROM Model
Positive Terminal
Estimated concentrations, SOC and temperature + -
ROM Model
Ambient Temperature; T
Terminal Voltage: VT
Charging/Discharging current
Negative Terminal
Reference: Maximum allowed concentrations and temperature, and desired SOC
Pulse generator
Two level or
Three level

31. Experimental Data for Charging at 4C
Qmax by CC and CV charging and the proposed charging method

32. Fast Charging Algorithm
Test conditions:
Benefits:
Less capacity losses after 100 cycles;
0.34Ah by the CC and CV.
0.24Ah losses by the proposing method
Estimate losses at 500 cycles: 0.5 Ah
Less temperature rise
Reduction of charging time
Cell No. 1 2
Ambient temperature (°C) 25
Charging method
CC/CV
Pulse
Charging current (C) 4
Discharging current (C)
Rest time (min) 10
Cycles
100
If there is no significant degradation,
Qmax = Cycle*P1 + P2

33. Diagnosis and Prognosis
Summary
Multi-scale and Multi-physics high resolution electrochemical, thermal and mechanical modeling considering degradations of materials.
Modeling
Design
Diagnosis and Prognosis
Cell design
System design
Series and parallel connection
Cooling systems
Controls
SOC estimation
Temperature controls
Rapid charging and discharging
Health monitoring (Growth of SEI, Change of conductivities, Losses of active materials and others)
Power fade
Capacity fade

34. Dr. Song-Yul Choe
Professor
Auburn University