基于区域极点配置理论的高速列车速度估计

Speed Estimation of High-speed Train Based on Regional Pole Assignment Theory

现行高速列车速度通常通过速度传感器获得,然而速度传感器出现问题会引起列车故障,降低系统的可靠性,采用无速度传感器技术的全阶磁链观测器法,在不增加系统结构复杂性的前提下,根据区域极点配置理论,设计具有一定自由度的观测器增益矩阵,并依据Lyapunov稳定性理论推导出牵引电机转速自适应律,提出高速列车速度估计算法,同时给出速度估计对电机参数变化的敏感性分析,数值仿真验证了所提算法的有效性。仿真结果表明,在电机参数偏差较大的情况下,该算法仍能准确估计出列车的速度,具有较强的鲁棒性。

The speed of HST ( high-speed train) is obtained by speed sensors in general.However,the failure of speed sensors can cause train fault and reduce the system reliability.In this paper,the full-order flux observer method based on speed sensorless technology was adopted to estimate the train speed.First,according to the regional pole assignment theory,an observer gain matrix with a certain degree of freedom was designed without increasing the complexity of the system structure.Then,the adaptive law of motor speed was derived based on Lyapunov stability theory,and a speed estimation algorithm for HST was proposed.In addition,the sensitivity analysis of the speed estimation on the motor parameter variation was given.Finally,the validity of the algorithm was verified by numerical simulations.The results show that the proposed algorithm can estimate the train speed accurately and has strong robustness under the condition of clear motor parameter deviation.