电压
无量纲量
电池(电)
荷电状态
等效电路
遗传算法
热的
估计理论
控制理论(社会学)
计算机科学
生物系统
材料科学
电子工程
算法
数学优化
工程类
电气工程
机械
数学
热力学
物理
功率(物理)
控制(管理)
人工智能
生物
作者
Hyeonwoo Cho,Changbeom Hong,Dae-Ki Hong,Se-Kyu Oh,Yeonsoo Kim
出处
期刊:Journal of The Electrochemical Society
[The Electrochemical Society]
日期:2023-08-01
卷期号:170 (8): 080520-080520
标识
DOI:10.1149/1945-7111/acf0ee
摘要
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.
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