Journal of South China University of Technology (Natural Science Edition) ›› 2007, Vol. 35 ›› Issue (6): 8-13,20.

• Automotive Engineering • Previous Articles     Next Articles

Analysis and Recognizition of Running Cycles of Hybrid Electric Vehicle

Luo Yu-tao1  Hu Hong-fei2  Shen Ji-jun3   

  1. 1. Guangdong Provincial Key l.aboratory of Electric Vehicle Research , South China Univ. of Tech. , Guangzhou 510640 , Guangdong, China;2. College of Mechanical Engineering , Guangdong Univ. of Tech. , Guangzhou 510006 , Guangdong , China;3. Guangzhou Honda AutomolÍve Co. Ltd. , Guangzhou 510700 , Guangdong , China
  • Received:2006-09-04 Online:2007-06-25 Published:2007-06-25
  • Contact: 罗玉涛(1972-)，男，博士，副教授，主要从事系统动力学与电动汽车研究。 E-mail:ctytluo@scut. edu.cn
  • About author:罗玉涛(1972-)，男，博士，副教授，主要从事系统动力学与电动汽车研究。
  • Supported by:

    国家自然科学基金资助项目( 50605020) ;广东省科技攻关项目(2006A10501001 ,2004Al1304001 )

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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