耦合神经网络轮胎模型EPS自适应控制  

Adaptive Control of EPS of Tyre Model Based on Neural Network

作　　者：黄晨[1] 陈龙[1] 江浩斌[1] 王志忠[1] 夏天[1] 

机构地区：[1]江苏大学汽车与交通工程学院,镇江212013

出　　处：《农业机械学报》2013年第10期47-51,共5页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家自然科学基金资助项目(50875112);江苏省自然科学基金资助项目(BK2010337);江苏省高校自然科学基金资助项目(09KJA580001);高等学校博士学科点专项科研基金资助项目(20093227110013;20103227120011)

摘　　要：建立了基于神经网络的轮胎模型。同时在EPS工况分类的基础上建立了工况推理准则,满足准确的判断要求,进而根据EPS所处的不同工况更改模糊PID的模糊规则,实现了多种助力特性的自适应切换。建立了整车多体动力学模型,进行了蛇形道路下的SIMPACK/Matlab联合仿真,并与基于dSPACE平台的实车试验进行对比分析。结果表明,基于该模型设计的控制策略可以有效降低驾驶员的操纵转矩和提高车辆的回正性能。The tyre model based on neural network was built. Inference rules of working condition were established based on the classification of electric power steering （EPS） conditions, which could lead to a correct judgment. Furthermore, according to the different working conditions of EPS, the fuzzy rules of fuzzy PID were changed to achieve active switching of multi-assist characteristics. The whole multi-body dynamic vehicle model was built. The SIMPACK-Matlab co-simulation was carried out on the snakelike road, and then compared with the car test based on dSPACE. The simulation result showed that the control strategy based on the proposed model could effectively reduce the driver＇ s operating torque and improve the returnability of vehicle.

关 键 词：轮胎 EPS 神经网络 自适应控制 

分 类 号：U461.4[机械工程—车辆工程]