Switched Reluctance Motors (SRMs) have become a popular alternative to replace permanent magnet machines in high-performance emerging applications such as automotive and aerospace. However, its market attractiveness is limited by the difficulty in control given its nonlinear behaviour. Model predictive control (MPC) is a promising solution to deal with this problem as per its notable features to deal with complex systems, nonlinearities and constraints. Still, the applications in SRMs are at an early stage compared to other drives. This paper aims to discuss the recent advancements and challenges in MPC for SRMs and a vision of its future developments and applications. The article describes the main difficulties in SRM control and the different approaches adopted to date by MPC to solve them. It also analyzes the control objectives that should still be considered in SRM drives, their particular challenges and how recent MPC developments in other AC drives can be adapted to the SRM case. The paper then proposes a roadmap of future works to achieve a unified and reliable control strategy that boosts SRM to outperform other drives, relating the control objectives to its potential applications.
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