Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/55109
Title: Adaptive neuro-fuzzy modeling of battery residual capacity for electric vehicles
Authors: Shen, WX
Chan, CC
Lo, EWC 
Chau, KT
Issue Date: 2002
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on industrial electronics, 2002, v. 49, no. 3, p. 677-684 How to cite?
Journal: IEEE transactions on industrial electronics 
Abstract: This paper proposes and implements a new method for the estimation of the battery residual capacity (BRC) for electric vehicles (EVs). The key of the proposed method is to model the EV battery by using the adaptive neuro-fuzzy inference system. Different operating profiles of the EV battery are investigated including the constant current discharge and the random current discharge as well as the standard EV driving cycles in Europe, the US, and Japan. The estimated BRCs are directly compared with the actual BRCs, verifying the accuracy and effectiveness of the proposed modeling method. Moreover, this method can be easily implemented by a low-cost microcontroller and can readily be extended to the estimation of the BRC for other types of EV batteries.
URI: http://hdl.handle.net/10397/55109
ISSN: 0278-0046
EISSN: 1557-9948
DOI: 10.1109/TIE.2002.1005395
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