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Mathematical Problems in Engineering
Volume 2014, Article ID 828269, 11 pages
http://dx.doi.org/10.1155/2014/828269
Research Article

A Predictive Distribution Model for Cooperative Braking System of an Electric Vehicle

1National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
2China North Vehicle Research Institute, Beijing 100072, China

Received 10 October 2013; Accepted 19 December 2013; Published 9 February 2014

Academic Editor: Wudhichai Assawinchaichote

Copyright © 2014 Hongqiang Guo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A predictive distribution model for a series cooperative braking system of an electric vehicle is proposed, which can solve the real-time problem of the optimum braking force distribution. To get the predictive distribution model, firstly three disciplines of the maximum regenerative energy recovery capability, the maximum generating efficiency and the optimum braking stability are considered, then an off-line process optimization stream is designed, particularly the optimal Latin hypercube design (Opt LHD) method and radial basis function neural network (RBFNN) are utilized. In order to decouple the variables between different disciplines, a concurrent subspace design (CSD) algorithm is suggested. The established predictive distribution model is verified in a dynamic simulation. The off-line optimization results show that the proposed process optimization stream can improve the regenerative energy recovery efficiency, and optimize the braking stability simultaneously. Further simulation tests demonstrate that the predictive distribution model can achieve high prediction accuracy and is very beneficial for the cooperative braking system.