真空助力器带主缸总成疲劳试验系统辨识

System Identification for Fatigue Test System of Vacuum Booster with Brake Master Cylinder

真空助力器带主缸总成是汽车制动系统的关键增力部件,其气动疲劳试验系统由气动子系统、液压子系统、电控子系统等多个子系统构成,属于复杂的非线性系统。该系统存在众多不确定因素,因此无法直接建立数学模型。为了考察该系统的动态性能,采用递归BP神经网络对该系统进行辨识。试验结果表明,递归BP神经网络能够很好的逼近该复杂非线性系统,在不同时间序列作用下均有较好的泛化能力。

Vacuum booster with brake master cylinder is a key part of automobile braking system. Its pneumatic fatigue test system consists of pneumatic subsystem, hydraulic subsystem, electronic control subsystem, etc. It is one kind of complex nonlinear systems. There are so many uncertain factors that it is impossible to establish the mathematical model. To test the dynamic property, this pneumatic fatigue test system was identified by a recursive BP neural network. The simulation results show that the recursive BP neural network fits this complex nonlinear system well, and the network has good generalization ability under different time series.