A new battery available capacity indicator for electric vehicles using neural network

被引：101

作者：

Shen, WX ^{[1
]}

Chan, CC ^{[1
]}

Lo, EWC ^{[1
]}

Chau, KT ^{[1
]}

机构：

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

来源：

ENERGY CONVERSION AND MANAGEMENT | 2002年 / 43卷 / 06期

关键词：

battery available capacity; neural network model; electric vehicles;

D O I：

10.1016/S0196-8904(01)00078-4

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

The ability to calculate the battery available capacity (BAC) for electric vehicles (EVs) is very important. Knowing the BAC and, thus, the driving range cannot only prevent EVs from being stranding on the road but also optimize the utilization of the battery energy storage in EVs. In order to determine the BAC, this paper presents a new neural network (NN) model of the lead-acid battery, based on the battery discharge current and temperature. Comparisons between the calculated BAC from the NN model and the measured BAC from experiments show good agreement. Furthermore, this new approach can readily be extended to the calculation of the BAC for other types of batteries. (C) 2002 Elsevier Science Ltd. All rights reserved.

引用

页码：817 / 826

页数：10

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