SOC estimation for LiFePO4 battery in EVs using recursive least-squares with multiple adaptive forgetting factors

V. Duong, H. A. Bastawrous, K. Lim, K. See, P. Zhang, S. Dou
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引用次数: 10

Abstract

This work presents a novel technique which is simple yet effective in estimating electric model parameters and state-of-charge (SOC) of the LiFePO4 battery. Unlike the well-known recursive least-squares-based algorithms with single constant forgetting factor, this technique employs multiple adaptive forgetting factors to provide the capability to capture the different dynamics of model parameters. The validity of the proposed method is verified through experiments using actual driving cycles.
基于多自适应遗忘因子的递归最小二乘估计电动汽车磷酸铁锂电池荷电状态
本文提出了一种简单有效的估算磷酸铁锂电池电模型参数和荷电状态(SOC)的新方法。与众所周知的基于递归最小二乘的单一常量遗忘因子算法不同,该技术采用多个自适应遗忘因子来提供捕获模型参数不同动态的能力。通过实际工况试验,验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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