journal6 ›› 2007, Vol. 28 ›› Issue (3): 73-75.

• 物理与电子 • 上一篇    下一篇

基于神经网络的发动机模型辨识

  

  1. (郴州职业技术学院,湖南 郴州 423000)
  • 出版日期:2007-05-25 发布日期:2012-08-27
  • 作者简介:雷云进(1968-),男,湖南郴州人,郴州职业技术学院讲师,硕士生,主要从事汽车新技术研究.
  • 基金资助:

    863计划课题资助项目(2005AA1Z2020)

Study on Model Recognition of Engine on Neural Network

  1.  (Chenzhou Professional and Technical College,Chenzhou 423000,Hunan China)
  • Online:2007-05-25 Published:2012-08-27

摘要:为进一步研究发动机的稳态、空载、动态转矩、燃油消耗模型和万有特性,笔者提出了一种基于神经网络的神经元结构模型和多层前馈网络结构模型并分别进行了数学分析.实践研究表明:在发动机的工作过程中,动态工况占66%~80%,并发现发动机的动力性和经济性指标与稳态工况存在着一定的差异.

关键词: 神经网络, 发动机, 模型辨识, BP网

Abstract: In order to give a further research on steady state and empty carrying dynamic state torque and  fuel consuming model and universal characteristics of engine,this text tries to carry on mathematical analysis respectively on a structure of neural model and many layer forward feedback  network structure models through neural network and make some quests towards model recognition of engine.Practice clarifies that in engine working  process,the dynamic state work condition has occupied 66%~80%,dynamical  and economic capability  signs of engine have certain difference between  the steady state  work condition and the dynamic state work condition.

Key words: neural network, engine, model recognition, back propagation neural Network

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