基于中值滤波的SBW信号处理及控制策略

Steer-by-Wire System Signal Processing and Control Strategy Based on Median Filter

线控转向(SBW)系统是发展无人驾驶模式的重要组成部分,针对线控转向系统路感电机输出的力矩如何能较好的跟踪传统转向系统目标力矩的问题,研究了转向盘转角和车速对路感力矩的影响。围绕路感电机展开,搭建了路感电机数学模型,分析了路感电机的动力特性。对电压传感器采集的电压信号采用中值滤波算法和最小二乘法做出对比处理,使路感电机进入相对稳压的状态;引入匹配路感电机的模糊PID和模糊免疫PID控制策略,并进行了仿真验证。验证结果证明免疫算法结合模糊PID控制器可以让路感模拟值更准确的跟踪目标力矩,而且具有较强的抗干扰性。表明了在正弦输入信号下,所设计的模糊免疫PID控制器模拟精度更高,帮助驾驶员获得理想的路感。

Steer-by-wire(SBW) system is an important part of the developing driverless mode. Aiming at the problem of how the torque output by road sense motor of SBW can better track the target torque of traditional steering system, the influences of steering wheel angle and vehicle speed on the road-sensing torque were studied. Around the road-sensing motor, the mathematical model of the road-sensing motor was built, and the dynamic characteristics of the road-sensing motor were analyzed. The median filtering algorithm and the least square method were used to compare the voltage signal collected by the voltage sensor to make the road induction motor enter the state of relative voltage stabilization. The fuzzy PID and the fuzzy immune PID control strategy matching the road-sensing motor were introduced at the same time. Two methods were verified by simulation. The simulation results prove that the fuzzy PID strategy which combines immune control can make the road-sensing analog value track the target torque accurately and has strong anti-interference. The conclusion shows the fuzzy PID controller has higher analog accuracy and helps the driver to get the ideal road sense under a sinusoidal input signal.