Modeling and Simulation Research on Lithium-Ion Battery in Electric Vehicles Based on Genetic Algorithm

Abstract:

Based on the genetic algorithm (GA), a novel type of parameters identification method on battery model was proposed. The battery model parameters were optimized by genetic optimization algorithm and the other parameters were identified through the hybrid pulse power characterization (HPPC) test. Accuracy and efficiency of the battery model were validated with the dynamic stress test (DST). Simulation and experiment results shows that the proposed model of the lithium-ion battery with identified parameters was accurate enough to meet the requirements of the state of charge (SoC) estimation and battery management system.

• Periodical: Applied Mechanics and Materials (Volumes 494-495)
• Pages: 246-249
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.494-495.246
• Online since: February 2014
• Authors: Cheng Lin*, Xiao Hua Zhang
• Keywords: Electric Vehicle (EV), Genetic Algorithm (GA), Lithium-Ion Battery, Parameter Identification

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