东北大学学报(自然科学版) ›› 2003, Vol. 24 ›› Issue (7): 635-638.DOI: -

• 论著 • 上一篇    下一篇

基于智能递阶结构的HEV控制策略

王大志;王建辉;顾树生   

  1. 东北大学信息科学与工程学院;东北大学信息科学与工程学院;东北大学信息科学与工程学院 辽宁沈阳 110004
  • 收稿日期:2013-06-24 修回日期:2013-06-24 出版日期:2003-07-15 发布日期:2013-06-24
  • 通讯作者: Wang, D.-Z.
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(60274024)·

Hybrid electric vehicle based on intelligent hierarchical structure control strategy

Wang, Da-Zhi (1); Wang, Jian-Hui (1); Gu, Shu-Sheng (1)   

  1. (1) Sch. of Info. Sci. and Eng., Northeastern Univ., Shenyang 110004, China
  • Received:2013-06-24 Revised:2013-06-24 Online:2003-07-15 Published:2013-06-24
  • Contact: Wang, D.-Z.
  • About author:-
  • Supported by:
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摘要: 混合动力电动汽车(HEV)的多能源动力总成控制器是实现多能源最优控制的关键,针对该包含多个子系统的复杂系统,提出了一类多模型方案,并采用了一种智能递阶监督控制策略·在智能递阶结构的上层,利用概率神经网络构成了组织级,对系统的任务进行规划;采用模糊决策控制器构成了递阶控制的协调级,将具体的任务分配给各个子系统·经过仿真研究,其结果表明了该方法的有效性·

关键词: 监督控制, 智能递阶控制, 一类多模型系统, 复杂控制系统, 混合动力电动汽车

Abstract: A plan of a class of multiple models system was put forward, in which there is a kind of intelligent hierarchical supervisory control system(IHSC) that is a supervisor to control the engine subsystems of the multiple energy source assembly control system of the hybrid electric vehicle(HEV). A probability neural network(PNN) made the organizing level of IHSC, which equals to the identification system of HEV processes and indicates the working procedure of HEV, the hidden level function was made of Parzen window kernel function, the identification result depended on the biggest probability value of the output level of PNN. A fuzzy decision-maker, which belongs to the multiple attributes decision and optimizes the working rate between the motor system and engine system according to the results of the organizing level of IHSC, made the coordination level of IHSC. A simulation study of the multiple energy source assembly control system of HEV was given to verify its feasibility.

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