均衡(音频)
荷电状态
电压
控制理论(社会学)
卡尔曼滤波器
线性化
电池(电)
计算机科学
扩展卡尔曼滤波器
能源消耗
电子工程
工程类
算法
电气工程
非线性系统
物理
功率(物理)
控制(管理)
人工智能
量子力学
解码方法
作者
Chusheng Lu,Jian Hu,Yujia Zhai,H. Hu,Huarong Zheng
标识
DOI:10.1016/j.est.2023.108481
摘要
The lithium-ion battery equalization method with voltage equalization is relatively mature and convenient to implement. However, this equalization method may cause excessive energy consumption. The equalization method with state of charge (SOC) equalization can reduce this kind of energy consumption. To use the equalization method with SOC, we should estimate the SOC first. So this paper proposes a SOC estimation method based on linearization of voltage hysteresis curve (EMBL). This paper linearizes the voltage hysteresis curve of lithium-ion battery and proposes a novel equivalent model of lithium-ion battery based on linear neural network (LEM). The performance superiority of the LEM is verified through the intermittent charging and discharging experiments. Then the SOC estimation method based on linearization of voltage hysteresis curve is constructed. The equalization experiments with voltage equalization and SOC equalization are carried out respectively. And the results prove that the method with SOC equalization can significantly reduce energy consumption compared to the method with voltage equalization, and the EMBL based SOC equalization can slightly reduce energy consumption compared to the extended Kalman filter (EKF) algorithm based SOC equalization.
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