Abstract
The equivalent circuit model (ECM) has gained popularity as a simplified and computationally efficient battery model. However, an appropriate model is required to accurately calculate terminal voltage, state of charge (SOC), and temperature for high-capacity Li-ion batteries used in hybrid electric and electric vehicles. In this study, we integrate the ECM with an energy balance model to calculate the cell temperature. Furthermore, we propose improved model structures and parameter estimation strategies to effectively characterize high-capacity batteries. First, the actual SOC is calculated considering the actual discharge capacity. Second, as the current increases, the overcalculated resistance is corrected. Finally, ECM parameters are estimated using experimental data and the genetic algorithm (GA). To facilitate the parameter-search process for GA, we employ the dimensionless scale-up method and the Pareto optimal concept. The thermal ECM is validated using experimental data from 57.6 Ah batteries, demonstrating voltage and temperature calculation errors of less than 1.71% and 3.51%, respectively.
Publisher
The Electrochemical Society
Subject
Materials Chemistry,Electrochemistry,Surfaces, Coatings and Films,Condensed Matter Physics,Renewable Energy, Sustainability and the Environment,Electronic, Optical and Magnetic Materials
Cited by
1 articles.
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