期刊名称：International Journal of Sustainable Engineering
印刷版ISSN：1939-7038
出版年度：2014
卷号：7
期号：4
页码：352-359
DOI：10.1080/19397038.2014.888488
语种：English
出版社：Taylor & Francis Group
摘要：This paper deals with energy management in hybrid electric vehicles. Use of radial basis function neural network (RBFNN) for the problem of energy management gains importance in the present decade. Use of genetic algorithm (GA) and particle swarm optimization (PSO) as optimization algorithms for parameter estimation is also well known. However, none of the researchers in the area tried to use GA and PSO as training algorithms for the problem. Hence in this paper, we propose two novel methods, based on RBFNN. The difference between RBFNN-based approaches in the literature and those used in this paper is the use of GA and PSO (i.e. optimising algorithms) as training algorithm to train RBFNNs. Interestingly, it is seen that the proposed approaches of this paper outperform RBFNN-based approaches in the literature with traditional training.
关键词：Keywords:enenergy managementhybrid electric vehiclesradial basis function neural networks
