关键词: 混合动力电动汽车, 控制策略, 行驶工况, 模糊识别, 聚类分析

Abstract:

In this paper , the optimization results of matching and controlling strategies for hybrid electric vehicle ( HEV) in various running cycles are analyzed , It is found that the average power demand and its normal difference in a running cycle have a great impact on the HEV matching optimization , and that different fuel consumptions and constant charge state of the battery power unit can be obtained in the same running cycle with different controlling
parameters. A novel concept of "Cycle Block" is then put forward , According to the new concept , the average vehicle velocity and average running distance are used as characteristic parameters. Based on the classification of representative cycles , the real-time running cycles are analyzed by fuzzy recognition via a fuzzy controller and are taken as one or several known species. Moreover , a clustering analysis method is presented to correctly reflect the real-time running cycles and to further analyze and recognize the relevant species of running cycles , with ten parameters including the running time and distance and the maximum velocity as the characteristic parameters. Thus , a meticulously self-adaptive controlling strategy of HEV based on the real-time running cycle recognition is finally proposed.

Key words: hybrid electric vehicle, controlling strategy, running cycle, fuzzy recognition, clustering analysis