A new battery capacity indicator for nickel-metal hydride battery powered electric vehicles using adaptive neuro-fuzzy inference system

被引：24

作者：

Chau, KT ^{[1
]}

Wu, KC ^{[1
]}

Chan, CC ^{[1
]}

Shen, WX ^{[1
]}

机构：

[1] Univ Hong Kong, Dept Elect & Elect Engn, Hong Kong, Hong Kong, Peoples R China

来源：

ENERGY CONVERSION AND MANAGEMENT | 2003年 / 44卷 / 13期

关键词：

adaptive neuro-fuzzy inference system; battery residual capacity; electric vehicles; nickel-metal hydride battery; state of available capacity;

D O I：

10.1016/S0196-8904(02)00249-2

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

This paper describes a new approach to estimate accurately the battery residual capacity, (BRC) of the nickel-metal hydride (Ni-MH) battery for modern electric vehicles (EVs). The key to this approach is to model the Ni-MH battery in EVs by using the adaptive neuro-fuzzy inference system (ANFIS) with newly defined inputs and output. The inputs are the temperature and the discharged capacity distribution describing the discharge current profile, while the output is the state of available capacity (SOAC) representing the BRC. The estimated SOAC from ANFIS model and the measured SOAC from experiments are compared, and the results confirm that the proposed approach can provide an accurate estimation of the SOAC under variable discharge currents. (C) 2002 Elsevier Science Ltd. All rights reserved.

引用

页码：2059 / 2071

页数：13

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