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Battery Model Parameter Estimation Using a Layered Technique: An Example Using a Lithium Iron Phosphate Cell
Technical Paper
2013-01-1547
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Lithium battery cells are commonly modeled using an equivalent circuit with large lookup tables for each circuit element, allowing flexibility for the model to closely match measured data. Pulse discharge curves and charge curves are collected experimentally to characterize the battery performance at various operating points. It can be extremely difficult to fit the simulation model to the experimental data using optimization algorithms, due to the number of values in the lookup tables.
This challenge is addressed using a layered approach to break the parameter estimation problem into smaller tasks. The size of each estimation task is reduced to a small subset of data and parameter values, so that the optimizer can better focus on a specific problem. The layered approach was successful in fitting an equivalent circuit model to a lithium iron phosphate (LFP) cell data set to within a mean of 0.7mV residual error, and max of 9.2mV error at a transient.
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Citation
Jackey, R., Saginaw, M., Sanghvi, P., Gazzarri, J. et al., "Battery Model Parameter Estimation Using a Layered Technique: An Example Using a Lithium Iron Phosphate Cell," SAE Technical Paper 2013-01-1547, 2013, https://doi.org/10.4271/2013-01-1547.Also In
References
- Jackey , R. A Simple, Effective Lead-Acid Battery Modeling Process for Electrical System Component Selection SAE Technical Paper 2007-01-0778 2007 10.4271/2007-01-0778
- Jackey , R. , Plett , G. , and Klein , M. Parameterization of a Battery Simulation Model Using Numerical Optimization Methods SAE Technical Paper 2009-01-1381 2009 10.4271/2009-01-1381
- Deland , S. Optimization of Hydroelectric Flow with MATLAB http://www.mathworks.com/company/newsletters/articles/optimization-of-hydroelectric-flow-with-matlab.html MathWorks Dec. 2012
- Huria , T. , Ceraolo , M. , Gazzarri , J. , Jackey , R. High fidelity electrical model with thermal dependence for characterization and simulation of high power lithium battery cells Electric Vehicle Conference (IEVC), 2012 IEEE International March 2012 10.1109/IEVC.2012.6183271
- Chen , M. and Rincon-Mora , G.A. Accurate electrical battery model capable of predicting runtime and I-V performance IEEE Transactions on Energy Conversion 21 2 504 511 June 2006 10.1109/TEC.2006.874229
- Ceraolo , M. , Lutzemberger , G. , and Huria , T. Experimentally-Determined Models for High-Power Lithium Batteries SAE Technical Paper 2011-01-1365 2011 10.4271/2011-01-1365
- Ceraolo , M. New Dynamical Models of Lead-Acid Batteries IEEE Transactions on Power Systems 15 4 1184 1190 2000 10.1109/59.898088
- Ceraolo , M. and Barsali , S. Dynamical models of lead-acid batteries: Implementation issues IEEE Transactions on Energy Conversion 17 1 16 23 2002 10.1109/60.986432
- Huria , T. Rechargeable lithium battery energy storage systems for vehicular applications http://etd.adm.unipi.it/t/etd-04262012-182954/ Ph.D. thesis Department of Energy and Systems Engineering, University of Pisa 2012
- MathWorks Simscape http://www.mathworks.com/products/simscape/ Dec. 2012
- MathWorks Simulink Deisgn Optimization http://www.mathworks.com/products/sl-design-optimization/ Dec. 2012
- MathWorks Optimization Toolbox http://www.mathworks.com/products/optimization/ Dec. 2012