Advanced Torque Control Strategies for Switched Reluctance Motor

The growing issue of air pollution, remarkably impacting both climate change and public health, has required the development of novel solutions to diminish pollutants across different industrial sectors. This effort seeks to promote a sustainable transition toward environmentally friendly choices. Within this context, the automotive industry is central in the shift from conventional internal combustion engines to advanced electric motor technologies. This change assures significant reductions in direct emissions from engines while keeping better torque performance. In this work, the focus is on a particular type of electric motor known as the "switched reluctance motor (SRM)". The SRM, notable for its absence of rare-earth materials and outstanding performance, is a suitable alternative for electric vehicles, where the high cost and environmental impact of permanent magnet extraction are serious concerns. Despite these advantages, the SRM suffers from torque ripple and radial distortions (which generate noise) because of its inherent structure. The torque ripple has two main contributions: high-frequency torque ripple, generated by the switching of the inverter’s transistors, and low-frequency torque ripple generated during the commutation between two adjacent phases. In this study, it is explored the employment of advanced control schemes to reduce the effect of the torque ripple across a wide range of speeds, starting by developing a Simulink environment to model the SRM in exam and finally testing the adopted control schemes. Firstly, a distinction between indirect and direct torque control strategies is proposed. The indirect torque control regulates the torque by indirectly controlling the current. Therefore, both current and torque control schemes are designed. Regarding current control, two different schemes are developed: the hysteresis controller (model-independent) and the deadbeat controller (model-dependent), to carry out a performance comparison. The deadbeat has better results in terms of high-frequency torque ripple. Afterward, the torque control is performed by exploiting the "Torque Sharing Function (TSF)" scheme. It employs appropriate mathematical functions to distribute the total reference torque among all the phases of the SRM, to reduce the low-frequency torque ripple. This scheme is further improved, by optimizing specific control variables, to enhance the performance at higher speed. Next, a direct torque control named “Direct Instantaneous Torque Control (DITC)” is evaluated, which regulates the output torque using a three-level hysteresis control. The comparative analysis of the TSF and DITC points out that both can reduce the torque ripple, although the TSF ensures greater performance overall. Finally, a “model predictive controller (MPC)” is introduced. Even if it has a heavy computational burden, it allows to determine the theoretical limits of achievable control performance. The comparison between the MPC and the TSF reveals a minor worsening when using the TSF, ensuring the TSF scheme to be a great option for torque control.