电池(电)
荷电状态
图像扭曲
锂离子电池
计算机科学
锂(药物)
材料科学
内阻
模拟
汽车工程
工程类
功率(物理)
人工智能
物理
热力学
医学
内分泌学
作者
Xining Li,Lizhong Xiao,Guangchao Geng,Quanyuan Jiang
标识
DOI:10.1016/j.jpowsour.2022.231441
摘要
Pouch lithium-ion batteries have aroused widespread attention in the field of electric vehicles because of the high energy density and low internal resistance. The available capacity of the battery varies greatly under different temperatures, resulting significant error in state-of-charge (SOC) estimation. An effective approach to relieve this issue is to make full use of the battery surface temperature. This article presents an enhanced Coulomb counting method based on surface temperature characterization to improve SOC estimation accuracy. Theoretical analysis and visualization tests using infrared thermal imager are conducted to identify surface temperature features during battery operation. The feature regions of the pouch lithium-ion battery are initially determined by temperature distribution function and further screened by dynamic time warping (DTW) algorithm. Finally, the screened temperature features are applied to battery available capacity modeling. The experimental results prove that the proposed method can effectively improve the SOC estimation accuracy under various temperature conditions.
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