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Revealing Lithium-Ion Battery Internal Uncertainty through a Combined Electrochemical Based Degradation Battery Model with a Markov Chain Monte Carlo Approach
ISSN: 0148-7191, e-ISSN: 2688-3627
To be published on April 14, 2020 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
The battery electrodes are porous and have complicated microstructures due to irregular sizes and shapes of pores. Electrode design parameters like porosity, thickness, particle size, and conductivity can vary from one local area to another in one cell. Even under the normal operating current, some local areas may experience over-charge/over-discharge, extensive degradation, and rapid heat generation. These local events are not easy to observe or measure at onset and can eventually lead to catastrophic failure of the whole cell if no actions are taken. Battery design parameters are treated as constant values in many electrochemical battery models. However, the uncertainty of these parameters has an adverse effect on the longevity and safety of batteries. To prevent any catastrophic failure, a battery model is needed to predict any potential over-charge/over-discharge and rapid heat generation caused by internal uncertainty. In this work, a new method is developed to simulate random local events and design new control strategies to increase longevity and safety. An electrochemical-based battery degradation model is integrated with Monte Carlo simulation to capture the unknown random design parameters within a cell. Random samples are taken to represent the complex microstructure. The battery model can simulate major side reactions, lithium plating, state of health, and heat generation. This process opens the possibility to predict the uncertainties of batteries without detailed 3D modeling and can also be used for battery design optimization, battery management systems, and state estimations due to its flexibility and reasonable computational cost. The simulation results show that under the normal cutoff voltage range, local areas experience over-charge/over-discharge and high heat generation, which can damage the overall safety and longevity of batteries.
CitationLiu, C., "Revealing Lithium-Ion Battery Internal Uncertainty through a Combined Electrochemical Based Degradation Battery Model with a Markov Chain Monte Carlo Approach," SAE Technical Paper 2020-01-0450, 2020.
Data Sets - Support Documents
|[Unnamed Dataset 1]|
- Liu, C. and Liu, L. , “Optimal Design of Li-Ion Batteries through Multi-Physics Modeling and Multi-Objective Optimization,” Journal of the Electrochemical Society 164(11):E3254-E3264, 2017.
- Yang, X.-G. et al. , “A Look into the Voltage Plateau Signal for Detection and Quantification of Lithium Plating in Lithium-Ion Cells,” Journal of Power Sources 395:251-261, 2018.
- Yang, X.-G. et al. , “Modeling of Lithium Plating Induced Aging of Lithium-Ion Batteries: Transition from Linear to Nonlinear Aging,” Journal of Power Sources 360:28-40, 2017.
- Liu, L. and Liu, C. , “Considering Realistic Microstructure Heterogeneity: Variational Multiscale Modeling of Li-Ion Batteries,” in Meeting Abstracts, 2018, The Electrochemical Society.
- Moradi, M. and Liu, L. , “Towards a More Realistic Model: Variational Multiscale Modeling of Lithium-Ion Battery,” in Meeting Abstracts, 2017, The Electrochemical Society.
- Kehrwald, D. et al. , “Local Tortuosity Inhomogeneities in a Lithium Battery Composite Electrode,” Journal of the Electrochemical Society 158(12):A1393-A1399, 2011, doi:10.1149/2.079112jes.
- Less, G.B. et al. , “Micro-Scale Modeling of Li-Ion Batteries: Parameterization and Validation,” Journal of the Electrochemical Society 159(6):A697-A704, 2012, doi:10.1149/2.096205jes.
- Stephenson, D.E. et al. , “Modeling 3D Microstructure and Ion Transport in Porous Li-Ion Battery Electrodes,” Journal of the Electrochemical Society 158(7):A781-A789, 2011, doi:10.1149/1.3579996.
- Yan, B. et al. , “Three Dimensional Simulation of Galvanostatic Discharge of LiCoO2 Cathode Based on X-ray Nano-CT Images,” Journal of the Electrochemical Society 159(10):A1604-A1614, 2012, doi:10.1149/2.024210jes.
- Hutzenlaub, T. et al. , “Three-Dimensional Electrochemical Li-Ion Battery Modelling Featuring a Focused Ion-Beam/Scanning Electron Microscopy Based Three-Phase Reconstruction of a LiCoO2 Cathode,” Electrochimica Acta 115:131-139, 2014, doi:10.1016/j.electacta.2013.10.103.
- Wiedemann, A.H. et al. , “Effects of Three-Dimensional Cathode Microstructure on the Performance of Lithium-Ion Battery Cathodes,” Electrochimica Acta 88:580-588, 2013, doi:10.1016/j.electacta.2012.10.104.
- Blanquer, G. et al. , “Modeling Investigation of the Local Electrochemistry in Lithium-O2 Batteries: A Kinetic Monte Carlo Approach,” Journal of the Electrochemical Society 163(3):A329-A337, 2016.
- Ramadesigan, V. et al. , “Parameter Estimation and Capacity Fade Analysis of Lithium-Ion Batteries Using First-Principles-Based Efficient Reformulated Models,” ECS Transactions 19(16):11-19, 2009.
- Methekar, R.N. et al. , “Kinetic Monte Carlo Simulation of Surface Heterogeneity in Graphite Anodes for Lithium-Ion Batteries: Passive Layer Formation,” Journal of the Electrochemical Society 158(4):A363-A370, 2011.
- Liu, J. et al. , “Can an Identifiability-Optimizing Test Protocol Improve the Robustness of Subsequent Health-Conscious Lithium-Ion Battery Control? An Illustrative Case Study,” in 2016 American Control Conference (ACC), 2016, IEEE.
- Hu, C. et al. , “Method for Estimating Capacity and Predicting Remaining Useful Life of Lithium-Ion Battery,” in 2014 International Conference on Prognostics and Health Management, 2014, IEEE.
- Doyle, M. and Newman, J. , “The Use of Mathematical-Modeling in the Design of Lithium Polymer Battery Systems,” Electrochimica Acta 40(13-14):2191-2196, 1995, doi:10.1016/0013-4686(95)00162-8.
- Doyle, M. and Newman, J. , “Modeling the Performance of Rechargeable Lithium-Based Cells - Design Correlations for Limiting Cases,” Journal of Power Sources 54(1):46-51, 1995, doi:10.1016/0378-7753(94)02038-5.
- Fuller, T.F., Doyle, M., and Newman, J. , “Simulation and Optimization of the Dual Lithium Ion Insertion Cell,” Journal of the Electrochemical Society 141(1):1-10, 1994, doi:10.1149/1.2054684.
- Doyle, M., Fuller, T.F., and Newman, J. , “Modeling of Galvanostatic Charge and Discharge of the Lithium Polymer Insertion Cell,” Journal of the Electrochemical Society 140(6):1526-1533, 1993, doi:10.1149/1.2221597.
- Liu, L. et al. , “A Thermal-Electrochemical Model that Gives Spatial-Dependent Growth of Solid Electrolyte Interphase in a Li-Ion Battery,” Journal of Power Sources 268:482-490, 2014, doi:10.1016/j.jpowsour.2014.06.050.
- Zhang, X., Shyy, W., and Sastry, A.M. , “Numerical Simulation of Intercalation-Induced Stress in Li-Ion Battery Electrode Particles,” Journal of the Electrochemical Society 154(10):A910-A916, 2007.
- Guan, P. and Liu, L. , “Phase-Field Modeling of Solid Electrolyte Interphase (SEI) Cracking in Lithium Batteries,” in Meeting Abstracts, 2018, The Electrochemical Society.
- Pathak, M. et al. , “Analyzing and Minimizing Capacity Fade through Optimal Model-based Control-Theory and Experimental Validation,” ECS Transactions 75(23):51-75, 2017.
- von Lüders, C., et al. , Modeling of Lithium Plating and Lithium Stripping in Lithium-Ion Batteries. Journal of Power Sources, 2019, 414: p. 41-47.
- Sturm, J. et al. , “Modeling and Simulation of Inhomogeneities in a 18650 Nickel-Rich, Silicon-Graphite Lithium-Ion Cell during Fast Charging,” Journal of Power Sources 412:204-223, 2019.
- Gomadam, P.M. and Weidner, J.W. , “Modeling Volume Changes in Porous Electrodes,” Journal of The Electrochemical Society 153(1):A179-A186, 2006.
- Ramadass, P. et al. , “Development of First Principles Capacity Fade Model for Li-Ion Cells,” Journal of the Electrochemical Society 151(2):A196-A203, 2004.
- Liu, L., Guan, P., and Liu, C. , “Experimental and Simulation Investigations of Porosity Graded Cathodes in Mitigating Battery Degradation of High Voltage Lithium-Ion Batteries,” Journal of the Electrochemical Society 164(13):A3163-A3173, 2017.
- Liu, C. and Liu, L. , “Optimizing Battery Design for Fast Charging through a Genetic Algorithm Based Multi-Objective Optimization Framework, “in Meeting Abstracts, 2017, The Electrochemical Society.
- Liu, C. and Liu, L. , “Optimizing Battery Design for Fast Charge through a Genetic Algorithm Based Multi-Objective Optimization Framework,” ECS Transactions 77(11):257-271, 2017.
- Liu, C. and Liu, L. , “Improving Battery Safety for Electric Vehicles through the Optimization of Battery Design Parameters,” ECS Transactions 69(20):5-15, 2015.
- Liu, J., Li, G., and Fathy, H.K. , “A Computationally Efficient Approach for Optimizing Lithium-Ion Battery Charging,” Journal of Dynamic Systems, Measurement, and Control 138(2):021009, 2016.
- Qi, Y. et al. , “Is There a Benefit in Employing Graded Electrodes for Lithium-Ion Batteries?” Journal of the Electrochemical Society 164(13):A3196-A3207, 2017.
- Ouyang, Q. et al. , “Optimal Multiobjective Charging for Lithium-Ion Battery Packs: A Hierarchical Control Approach,” IEEE Transactions on Industrial Informatics 14(9):4243-4253, 2018.
- Fang, H., Depcik, C., and Lvovich, V. , “Optimal Pulse-Modulated Lithium-Ion Battery Charging: Algorithms and Simulation,” Journal of Energy Storage 15:359-367, 2018.
- Dawson-Elli, N. et al. , “On the Creation of a Chess-AI-Inspired Problem-Specific Optimizer for the Pseudo Two-Dimensional Battery Model Using Neural Networks,” Journal of The Electrochemical Society 166(6):A886-A896, 2019.
- Dawson-Elli, N. et al. , “Data Science Approaches for Electrochemical Engineers: An Introduction through Surrogate Model Development for Lithium-Ion Batteries,” Journal of the Electrochemical Society 165(2):A1-A15, 2018.
- Lin, X. et al. , “A Comprehensive Capacity Fade Model and Analysis for Li-Ion Batteries,” Journal of the Electrochemical Society 160(10):A1701-A1710, 2013, doi:10.1149/2.040310jes.
- Zhao, X. et al. , “Electrochemical-Thermal Modeling of Lithium Plating/Stripping of Li (Ni0. 6Mn0. 2Co0. 2) O2/Carbon Lithium-Ion Batteries at Subzero Ambient Temperatures,” Journal of Power Sources 418:61-73, 2019.
- Shi, D. et al. , “Stress Analysis of the Separator in a Lithium-Ion Battery,” SAE Int. J. Engines 4(1):693-702, 2011, https://doi.org/10.4271/2011-01-0670.
- Cannarella, J. et al. , “Mechanical Properties of a Battery Separator under Compression and Tension,” Journal of the Electrochemical Society 161(11):F3117-F3122, 2014.