发动机输出转矩的改进BP神经网络估计

Estimation of engine output torque based on improved BP neural network

针对混合动力汽车控制系统的开发过程,提出一种应用改进BP神经网络对发动机输出转矩进行估计的方法。根据在发动机实验台中所测得的部分样本数据,将传统的BP网络误差函数进行改进,建立了发动机输出转矩估计模型,并利用最优停止法对网络进行训练,避免了过拟合现象。实验结果表明,利用改进的BP网络对发动机输出转矩进行估计,减轻了网络训练负担,降低了网络训练的误差,提高了发动机输出转矩估计的精确度。

According to the development process of the control system for Hybrid Electic Vehicle, the estimation method to the torque of the engine is presented. Based on partial sample experiment result which came from engine experiment frame, the error function of the traditional BP neural network was improved. Then the model of engine torque was built. Meanwhile, optimal stopping rule was used to avoid over-fitting. The experiment results indicated that improved BP neural network not only alleviates burden of the network training, reduces error of the network training but also improves precision of engine output torque estimation.