## 1 Introduction
The DITC strategy is extended in [25] to achieve the four-quadrant operation of the SRM. In [26], a new hysteresis rule for DITC is formulated and the system efficiency is improved by modifying the conduction angles. In order to improve the torque control performance and system efficiency, an online optimization strategy for DITC based on the genetic algorithm is proposed in [27]. In [28], the pulse width modulation (PWM) technology is introduced into DITC to reduce the torque ripple. The model predictive torque control (MPTC) is also an excellent direct method due to its ease of implementation and well-known ability to optimize the multi-objective performance of the SRM [29]. In the MPTC method, the operating modes of the converter are usually divided into finite control sets, and the optimal switching scheme is determined by minimizing the cost function. As can be seen from the application of MPTC in the transformer in [30], it has a well-known ability to deal with nonlinear transformers. The MPTC method is first applied to the SRM drive system in [31] to improve the torque ripple and copper loss. In [32], the performance of the MPTC is improved using the sector partition technique, and the realizability of this method is enhanced by compensating for the computation delay. To further reduce the computational burden of MPTC, a finite control set with only 6 switching states is proposed in [33], and the feasibility of the method is demonstrated experimentally. In addition, the MPTC can also be integrated with TSF [34] and DTC [35] to improve the performance of traditional torque control methods. Nevertheless, in the above MPTC method, the converter state is constant within each control step and the switching frequency is also variable, which leads to a relatively large torque ripple and is not conducive to the filter design. It is pointed out in [9; 36] that the MPTC method with fixed switching frequency is a promising work to be explored. In this paper, a DPTC method using the fixed frequency PWM technique is developed to enhance the torque control performance of the SRM drive. This method enhances the predictive PWM-DITC algorithm published in [36] and solves the problem of uncontrollable current. Additionally, the shortcoming of large torque ripple in the conventional MPTC method is improved. In the proposed method, the attainable range of phase torque is predicted and the torque allocation set is divided directly after modifying the torque boundary. Therefore, each allocation scheme in the torque allocation set is achievable. Afterward, in order to minimize the copper loss, a single-objective cost function is defined. It is worth noting that the torque ripple has been optimized in the torque allocation set, so the optimization objective is only related to the phase current, which avoids the work of setting weight parameters. By minimizing the cost function, the scheme to minimize the copper loss can be found in the torque allocation set. Furthermore, the optimizable speed boundary is also determined to avoid negative torque. Since the proposed method provides the phase reference torque throughout the optimizable region, the effectiveness of the optimization operation is guaranteed. The proposed DPTC method is simulated and experimentally verified on a three-phase 12/8-pole SRM and compared with several existing torque control methods.