Zhang, Cheng, Yang, Zhile and Li, Kang (2014) Modeling of electric vehicle batteries using RBF neural networks. In: 2014 International Conference on Computing, Management and Telecommunications (ComManTel), , Vietnam., 27-29 Apr 2014 pp. 116-121. doi:10.1109/ComManTel.2014.6825590

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Abstract

Electric Vehicles (EVs) are promised to significantly reduce the consumption of conventional fossil fuels in the transport sector as well as to limit the overwhelming greenhouse gas emissions. An accurate battery model is indispensable for the design of charging and discharging control of EVs. A new Radial Basis Function (RBF) modelling approach, which combines the Levenberg-Marquardt method to tune the non-linear parameters and an input selection approach for confining the number of input variables is proposed to model the batteries of EVs. Experimental results on modelling Li-ion batteries show that the resultant models have achieved high accuracy on training data and desirable generalization performance on unseen data.

Item Type:	Conference Item (Paper)
Divisions:	Faculty of Science > WMG (Formerly the Warwick Manufacturing Group)
Book Title:	2014 International Conference on Computing, Management and Telecommunications (ComManTel)
Official Date:	5 June 2014
Dates:	Date Event 5 June 2014 Published
Page Range:	pp. 116-121
DOI:	10.1109/ComManTel.2014.6825590
Status:	Peer Reviewed
Publication Status:	Published
Conference Paper Type:	Paper
Title of Event:	2014 International Conference on Computing, Management and Telecommunications (ComManTel),
Type of Event:	Conference
Location of Event:	Vietnam.
Date(s) of Event:	27-29 Apr 2014

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