锂离子电池系统的模糊模型辨识

M. F. Samadi, M. Saif
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引用次数: 2

摘要

汽车电气化的趋势要求先进的电池管理系统。BMS的核心是一个精确的模型,在此基础上可以建立控制和监测。准确性和低计算量是在线任务应用模型必须具备的两个重要因素。本文提出了一种基于电压、电流和温度的锂离子电池的Takagi-Sugeo模糊建模方法。利用T-S模型的多模型结构,可以在保持局部模型线性和易于实现的控制/估计算法的同时,适当地考虑电池动力学和相应参数的非线性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Takagi-Sugeno fuzzy model identification of Li-ion battery systems
The trend towards electrification of vehicles demands advanced battery management systems. The core of a BMS is an accurate model upon which the control and monitoring can be established. Accuracy and low-computational load are the two important factors that the applied model for online tasks have to possess. This paper presents a Takagi-Sugeo (T-S) fuzzy-modeling approach toward Lithium ion battery where SoC is estimated using the knowledge of voltage, current and temperature. By the virtue of multiple-model structure of T-S model, the nonlinearities of battery dynamics and corresponding parameters can be appropriately accounted for, while keeping the local models linear and easy-to-implement control/estimation algorithms.
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