联合工况下ABS系统轮速信号滤波方法研究

Research on the Filter Technique for ABS Wheel Speed Signals at Combined Slip Condition

常用的ABS系统轮速信号卡尔曼滤波方法中假定系统过程噪声参数为定值,没有考虑车辆运行工况对系统过程噪声的影响。在分析车辆运行工况对轮速信号滤波的影响基础上设计基于RBF神经网络的系统过程参数调节器及相应滤波算法对联合工况下轮速信号进行处理。仿真验证结果表明,该方法能够有效地模拟轮速信号滤波过程中系统过程噪声参数的变化特性,提高了联合工况下轮速信号的滤波精度。

The system process noise parameter of Kalman filter for common ABS wheel speed signalprocessing is assumed to be fixed value,and the influences of operational conditions are ignored.Basedon the analyzing of the influences of operational conditions for wheel speed signals filtering,regulatorbased on RBF neural network for system process parameter and corresponding filtering algorithm aredesigned for the wheel speed processing under combined slip condition.The simulation resultsdemonstrate the proposed method can describe the variation characteristics well and improve the signalaccuracy of wheel speed.