Elman网络在汽车智能换挡判别中的研究

Studies of Elman Network in the Intelligent Shift Discrimination

为了改善汽车行进中的换挡品质,使汽车在相应的环境工作中能够实现自动切换档位,根据人工神经网络和汽车换挡规律的特点,需对汽车的油门开度、速度、加速度进行分析;基于Elman神经网络建立汽车自动变速三参数控制模型,并利用Matlab进行了测试分析和仿真模拟,得出了仿真结果。仿真结果表明,采用Elman神经网络对汽车自动换挡判别时优于BP网络。

Improve the quality of gears shifting and make cars to shift gears automatically in an appropriate environment.Based on neural network which modeling Elman three parameters and the characteristics of car shift which include automobile＇s throttling,speed and acceleration.This paper sets up an automatic variable speed controlled model,tests and experiment via software Matlab.In conclusion,the simulation results show that the Elman neural model summarize an accurate answer compared with Bp neural network.