Parameterization of a Battery Simulation Model Using Numerical Optimization Methods 2009-01-1381
Typically, battery models are complex and difficult to parameterize to match real-world data. Achieving a good generalized fit between measured and simulated results should be done using a variety of laboratory data. Numerical optimizations can ensure the best possible fit between a simulation model and measured data, given a set of constraints.
In this paper, we propose a semi-automated process for parameterizing a lithium polymer battery (LiPB) cell simulation model that is able to satisfy constraints on the optimized parameters. This process uses a number of measured data sets under a variety of conditions. An iterative numerical optimization algorithm using Simulink Parameter Estimation was implemented to estimate parameter values by minimizing error between measured and simulated results.
Citation: Jackey, R., Plett, G., and Klein, M., "Parameterization of a Battery Simulation Model Using Numerical Optimization Methods," SAE Technical Paper 2009-01-1381, 2009, https://doi.org/10.4271/2009-01-1381. Download Citation
Author(s):
Robyn A. Jackey, Gregory L. Plett, Martin J. Klein
Affiliated:
The MathWorks, Inc., University of Colorado at Colorado Springs, Compact Power Inc.
Pages: 9
Event:
SAE World Congress & Exhibition
Also in:
Advanced Battery Technology, 2009-SP-2250