基于二维数据插值的开关磁阻电机转矩脉动抑制策略

doi:10.19595/j.cnki.1000-6753.tces.241921

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Abstract The switched reluctance machine (SRM) has become one of the most competitive generator/ starter candidates in the field of electric vehicles and multi-electric aircraft. However, the torque ripple caused by the double-bump structure limits its applications. Realizing effective suppression of the torque ripple has become a research hotspot. Based on the accurate prediction model, model predictive control (MPC) can predict the variation of the target variable under all possible control signals and optimize the control signals online based on a predefined control law. However, the existing research only selects the optimal control signal within a limited set of control signals, which limits the suppression effect and does not fully utilize the flexibility of MPC. Moreover, the artificial setting of the parameters in the cost function affects the effectiveness of the MPC strategy. Thus, this paper proposes a torque ripple suppression strategy for the SRMs based on two-dimensional linear interpolation.
Firstly, PWM control signals are used to replace the three switching states in the conventional predictive control. The predicted optimal control signal can smooth the current and flux-linkage more flexibly under the same calculation frequency, which effectively enhances the accuracy of torque control. Latin hypercube sampling is proposed to divide the duty cycle in the range [-1, 1] into n strata, and one random duty cycle is drawn within each stratum to compose the predicted duty cycle scheme. To convert the predicted optimal duty cycle into the corresponding switching tube control signals, a PWM modulation method for the asymmetric half-bridge power converter is proposed.
Then, the operating region is divided into single-phase and commutation regions by online operating region adjustment, and different predictive control methods are used for each region. In the single-phase region, the deadbeat predictive control calculates the optimal duty cycle for the conduction phase to follow the phase torque reference. In the commutation region, the MPC predicts the optimal duty cycle for the incoming and outgoing phases. The expected duty cycle scheme is determined based on the SRM operation state, and the corresponding predicted torque is obtained using the prediction model. A two-dimensional linear interpolation method is proposed to expand the prediction dataset and find the optimal duty cycle that corresponds to the minimum predicted torque difference.
Experimental verification of the torque ripple suppression effect is carried out on a three-phase 12/8-pole SRM experimental platform. The results show that in the commutation region, the proposed combined predictive control method produces more accurate control signals and prevents the occurrence of a large torque ripple due to the application of PWM control. In the single-phase region, according to the deadbeat predictive control’s fast response, the duty cycle of the conduction phase that minimizes the torque ripple in the next control cycle is accurately calculated, and the output torque can track the reference torque precisely. The proposed method, based on 2D data interpolation, can reduce torque ripple by 40-50% while causing almost no efficiency loss.
The proposed method has the following advantages. (1) By applying PWM signals instead of the conventional finite-set predictive signals, the output optimal control signals are enriched, and the current and torque variations are smooth. (2) The proposed two-dimensional interpolation optimization, instead of the conventional cost function, not only realizes the application of PWM signals in MPC but also avoids the complicated and complex process of parameter tuning.

Key words： Switched reluctance machine (SRM) torque ripple two-dimensional linear interpolation model predictive control (MPC) deadbeat predictive control

Received: 28 October 2024

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TM352

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	Fu Qianrao
	Guo Jixuan
	Song Jiahe
	Ge Lefei

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Fu Qianrao,Guo Jixuan,Song Jiahe等. Switched Reluctance Machine Torque Ripple Suppression Strategy Based on 2D Data Interpolation[J]. Transactions of China Electrotechnical Society, 2025, 40(24): 7949-7957.

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