Eigenvalue-Distribution-Based Stability Enhancement Strategy of Speed-Sensorless Induction Motor in Low-Speed Regenerating Region
Yang Kai1, Wang Yujie1, Luo Cheng1, Xiong Fei1, Zhan Zhejun2
1. School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan 430074 China; 2. CRRC Yongji Electric Co. Ltd Yongji 044500 China
Abstract：In railway transportation, the induction motor (IM) relies on speed sensors to ensure the system’s accuracy. However, sensor installation and maintenance costs are immense, and the control accuracy is susceptible to environmental influences. In order to improve the reliability of the system and reduce the cost of maintenance, speed-sensorless control is widely used for IMs of rail trains. When the IM operates in a low-speed regenerating region, the speed estimation system becomes unstable, which limits its further application. There are two approaches to solving the above problem: anisotropy and model-based methods. Among them, the adaptive full-order flux observer is widely applied. Considering the eigenvalue distribution of the error coefficient matrix (ECM), the traditional stability improvement method cannot eliminate the unstable eigenvalues. Namely, it is impossible to completely solve the problem of unstable operation in low-speed regenerating regions. Therefore, this paper proposes an eigenvalue-distribution-based stability enhancement strategy (EDBSES) to eliminate the unstable eigenvalues. Firstly, the conventional method, which only takes the stator current as a feedback factor, is analyzed. Based on the determinant of ECM of the conventional method, the existence of unstable eigenvalues in the vicinity of zero synchronous speed is revealed. A multiple error system is established to eliminate the unstable eigenvalues by introducing stator current and rotor flux error to speed adaptive law and the observer. Based on the mathematical model of IM, the relation of actual rotor flux with stator current and slip speed is derived to obtain the rotor flux error. Then, the feedback gains containing the variable k are designed for stable operation. With the eigenvalue distribution method, the value range of k is determined to make all the real parts of the eigenvalues in EMC less than 0. Furthermore, the robustness of the speed-sensorless IM drive system is analyzed by the ratio of the actual to the estimated rotor flux. The analysis shows the amplitude difference between the estimated actual rotor flux is up to nearly 8 times when the k value is small and the slip speed is large with stator resistance mismatches. Therefore, the system is sensitive to stator resistance errors. An increase in the k value can improve the robustness of the system. The effectiveness of EDBSES is proved on a 2.2 kW IM experimental setup. Comparative experiments are conducted under step load torque and speed reversal conditions using zero feedback matrix, conventional feedback matrix, and EDBSES. The results show the EDBSES increases the load capacity in the low-speed regenerating region from 6.8 N·m to 11.9 N·m and effectively suppresses the phase current and speed ripples during speed reversal, which improves the stability of speed-sensorless IM in the low-speed regenerating region. In conclusion, this paper proposes an EDBSES method for enhancing stability in the low-speed regenerating region. Considering the eigenvalue distribution of ECM, a multiple error observer model with new feedback gains is established to eliminate the unstable eigenvalues of a speed-sensorless IM system. The stability and load capability of speed-sensorless IM is enhanced in low-speed regenerating regions.
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