In this paper, a methodology for modeling and identification of the electro-thermal dynamic behavior of batteries is developed with an equivalent circuit model for use in automotive applications. The developed model has a simple structure but can capture sufficient dynamics under both temperature and state of charge (SoC) variation, thus making it applicable for use with real-time model-based estimation algorithms (for example, in state of charge and state of health estimation). A systematic procedure is outlined for the data acquisition and identification process, and experimental results are presented for an A123 lithiumion iron phosphate battery.
Volume Subject Area:
Control, Optimization and Identification of Advanced Automotive Systems
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