Adaptive neuro-fuzzy modeling of battery residual capacity forelectric vehicles
Shen, W.X.
Chan, C.C.
Lo, E.W.C.
Chau, K.T.
Dept. of Electr. & Electron. Eng., Univ. of Hong Kong;
This paper appears in: Industrial Electronics, IEEE Transactions on
Publication Date: Jun 2002
Volume: 49,
Issue: 3
On page(s): 677-684
ISSN: 0278-0046
References Cited: 22
CODEN: ITIED6
INSPEC Accession Number: 7295806
Digital Object Identifier: 10.1109/TIE.2002.1005395
Current Version Published: 2002-08-07
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
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