A Harmonic Optimized Deadbeat Predictive Control Method for Switched Reluctance Machine

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Abstract
In this article, a deadbeat predictive control (DPC) method with low measurement effort and the capability to effectively suppress torque ripple is proposed for switched reluctance machine (SRM). First, to enhance prediction model accuracy, a flux-linkage model based on second-order Bézier curves combined with full-position interval interpolation is proposed. This method only requires determining three parameters—aligned-position incremental inductance, unaligned-position incremental inductance, and unaligned-position saturation inductance to accurately describe flux-linkage characteristics. Next, Varignon’s principle is applied to analyze the mechanism by which phase current harmonics influence torque. On this basis, the beetle antennae search algorithm, which enables rapid optimization, is used to optimize the current waveform, resulting in a novel harmonic-optimized current profile. The developed enhanced DPC methodology incorporating pulsewidth modulation demonstrates significant torque ripple reduction under diverse operating conditions, minimal offline measurement requirements, and high estimation accuracy, thus providing an efficient and practical solution for achieving high-performance SRM control in industrial applications.
Funding Information
  • National Natural Science Foundation of China (52277067)
  • Shaanxi Provincial Science Foundation for Distinguished Young Scholars (2023-JC-JQ-44)

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