关键词: 电动汽车, 制动意图, 近邻成分分析, 人工蜂群, 支持向量机

Abstract: For the regenerative braking systems of electric vehicles， the corresponding regenerative braking control strategy might be designed according to the different braking intentions of the driver， so as to improve the safety， comfort and economy effectively during the vehicle braking processes. Accurate and fast recognition of drivers braking intentions was the basis of designing control strategy. An on-line recognition method of driver braking intentions was designed based on ABC-SVM algorithm  and implemented to identify the drivers braking intentions accurately and quickly for the electric vehicles with brake-by-wire. Firstly， the braking data were preprocessed， and the effective features were selected by NCA feature selection algorithm， and then the braking intention recognition model was established by the ABC-SVM algorithm， and on-line recognition was carried out finally. Offline verification and online test results show that the NCA algorithm may effectively filter out irrelevant features caused by signal noise. Compared with the fuzzy reasoning， back propagation（BP）， particle swarm optimization support vector machine（PSO-SVM）and genetic algorithm support vector machine （GA-SVM） recognition algorithms， the ABC-SVM algorithm may identify drivers braking intentions more accurately and quickly.

Key words: electric vehicle, braking intention, neighborhood component analysis（NCA）, artificial bee colony（ABC）, support vector machine（SVM）