Abstract:With its simple and robust structure and wide speed regulation range, switched reluctance machine (SRM) has a wide range of application scenarios in the fields of multi-all-electric airplanes, electric vehicles, and new energy power generation. However, due to its double-convex pole structure and pulse-powered operation mode, SRM has the shortcomings of large torque ripple and strong vibration during operation, which seriously affects its practical application in the industrial field. In view of the above problems, this paper firstly explores the generation mechanism of vibration noise of SRM, and identifies torque ripple and radial force ripple as the two major causes of motor vibration noise. Based on the idea of model predictive control (MPC), a multi-objective control method of SRM torque ripple and radial force ripple based on the MPC method is proposed along with the control logic of torque predictive control. Based on the magnetic chain waveform planning, the radial force and torque share function (TSF) is constructed, and the torque and radial force waveforms of each phase are planned to realize the simultaneous control of the torque and radial force; considering the changing characteristics of the radial force, the voltage vector table of single-phase conduction area under the MPC is optimized, so that the radial force ripple caused by demagnetization correlation breaks can be reduced; the predicted torque and radial force are taken as the parameters to the cost function, so that the on-line optimization of the switching status of the minimum torque ripple and radial force ripple can be performed. In MPC, the accuracy of the motor electromagnetic characteristic model seriously affects the stability of the control algorithm, in order to improve the stability of the model predictive torque and radial force control (MPTFC) algorithm, and reduce the vibration of the motor, propose a current error compensation method based on the prediction of reluctance. Combined with the operating characteristics of the SRM variable reluctance, from the nonlinear inductance characteristics, according to the parameters of each phase current and voltage, to obtain the relationship between the predicted reluctance and the actual reluctance; combined with the motor state equations, the inverse deduction to obtain a more accurate value of current prediction, to improve the control performance of the MPC algorithm. Finally, a semi-physical experimental verification platform based on a 600 W three-phase 12/8-pole SRM is constructed to experimentally validate the proposed error compensation-based vibration suppression control strategy. Comparisons are made with current chopper control (CCC), PWM control, MPC, model predictive torque control (MPTC), and MPTFC methods at 500 r/min, 1 000 r/min, and 1 500 r/min with a load of 1 N·m and 2 N·m. The experimental results show that, compared with the traditional CCC, PWM and MPTC, the MPTFC strategy has significant suppression effects on torque ripple and radial force ripple, and the vibration acceleration spectrum shows that this method effectively reduces the vibration of the whole machine; the model predictive torque and force control based on current error compensation (CEC-MPTFC) further strengthens the suppression effect, and reduces the torque ripple and radial force ripple by 10.10% and 23.47%, which provides a reference to improve the reliability of the SRM.
葛乐飞, 宋佳赫, 黄佳乐, 樊子祯, 宋受俊. 基于电流误差补偿的开关磁阻电机振动抑制策略[J]. 电工技术学报, 2025, 40(17): 5434-5447.
Ge Lefei, Song Jiahe, Huang Jiale, Fan Zizhen, Song Shoujun. Vibration Suppression Strategy for Switched Reluctance Machine Based on Current Error Compensation. Transactions of China Electrotechnical Society, 2025, 40(17): 5434-5447.
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