基于模糊神经网络控制的汽车辅助再生制动系统研究

将驾驶安全性和制动能量回收相结合,提出了基于模糊神经网络控制的汽车辅助再生制动系统.通过试验数据建立基于驾驶员经验的模糊神经网络,实现根据驾驶车辆与前车的相对距离和相对速度动态调整制动强度;通过计算得到不同的车速和制动强度下,前轮再生制动力,前、后轮摩擦制动力查询表;将模糊神经网络和制动力查询表嵌入配备比例阀的制动系统从而完成辅助再生制动系统的设计.在Simulink下搭建此辅助再生制动系统模型进行仿真实验,结果表明,此再生制动系统可以有效辅助驾驶安全,避免追尾事故发生,并可充分回收制动能量.

Research on the Vehicle Assist Regenerative Braking System Based on the Fuzzy Neural Network

An assist regenerative braking system based on neural network was proposed to combine driving safety and braking energy recovery. An experiments-based fuzzy neural network of the vehicle braking was established to ensure driving safety. The look-up table of the regenerative and friction braking force was achieved through calculation. The fuzzy neural network and the look-up table were inserted in the braking system with a proportion valve to accomplish the assist regenerative braking system. The simulation results in Simulink have shown that the braking system can assist braking effectively, avoid rear-end collision and can adequately recycle braking energy.