吉林大学学报(信息科学版)

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车辆起步过程神经网络PID控制研究

高原a,b, 刘奇芳b, 卢晓晖b, 陈虹a,b   

  1. 吉林大学 a. 汽车仿真与控制国家重点实验室; b.  通信工程学院, 长春 130022
  • 出版日期:2013-07-20 发布日期:2013-08-23
  • 作者简介:高原(1990—), 男, 长春人, 吉林大学硕士研究生, 主要从事车辆起步控制研究, (Tel)86-18686698254(E-mail)gaoyuan5232@gmail.com;陈虹(1963—), 女, 长春人, 吉林大学教授, 博士生导师, 主要从事预测控制、 鲁棒控制、 非线性控制和汽车控制研究, (Tel)86-431-85094813(E-mail)chenh@jlu.edu.cn。
  • 基金资助:

    长江学者和创新团队发展计划基金资助项目(IRT1017); 国家自然科学基金资助项目(61034001; 51005093)

Research on Launch Control Strategy for AMT Vehicles Based on Neural Network PID

GAO Yuana,b, LIU Qi-fangb, LU Xiao-huib, CHEN Honga,b   

  1. a. State Key Laboratory of Automotive Simulation and Control; b. College of Communication Engineering, Jilin University, Changchun 130022,China
  • Online:2013-07-20 Published:2013-08-23

摘要:

 针对车辆起步工况的多样性, 笔者设计了神经网络PID(Proportion Integration Differentiation)控制器, 通过对离合器的转速跟踪控制, 在保证发动机不熄火的前提下, 实现了AMT(Automatic Manual Transmission)车辆快速平稳起步的控制目标。为了验证控制器的有效性,建立了中型卡车的传动系模型, 其中包括发动机、 离合器、 变速箱、 主减速器和车轮等, 并且根据实际起步情况, 设置了正常起步、 急起步、 载重起步和坡路起步4种工况, 进行了AMESim-Simulink联合仿真实验。通过与传统PID控制器的控制效果相比较, 分析得出,神经网络PID控制器能在变工况下很好地完成AMT车辆起步控制, 具有良好的自适应性。

关键词: AMT自动变速器, 干式离合器, 起步控制, 神经网络PID

Abstract:

According to the diversity of launch conditions a neural network PID (Proportion Integration Differentiation) controller is designed through the clutch speed tracking control. Keeping the engine running, the controller makes the launch process of the AMT (Automatic Manual Transmission) vehicle smooth and fast. In order to verify the neural network PID controller's effectiveness, a powertrain model of a medium-sized truck about AMT vehicles is established. The model includes the engine, the clutch, the transmission, the main reducing gear and wheels. And simulations are carried out in various working conditions according to the actual situation. Comparing the performance to the traditional PID controller's and analyzing the results of simulations, the neural network PID controller provides the good performance during AMT vehicles launch progress and has good adaptability in various working conditions.

Key words: automatic manual transmission(AMT), dry clutch, launch control, neural network proportion integration differentiation (PID)

中图分类号: 

  • TP273