Supplementary Materials for: Intelligent Torque Ripple Minimization in Switched Reluctance Motors Using Deep Deterministic Policy Gradient-Based Actor-Critic Reinforcement Learning

This dataset contains both simulation and experimental data generated in support of the manuscript entitled“Intelligent Torque Ripple Minimization in Switched Reluctance Motors Using Deep Deterministic PolicyGradient-Based Actor-Critic Reinforcement Learning”. The data correspond to an 8/6 Switched ReluctanceMotor (SRM) operating under different torque ripple minimization control strategies. All simulations were carried out using MATLAB/Simulink, and the resulting data were exported in MicrosoftExcel format to ensure transparency, accessibility, and reproducibility. In addition to simulation data, the dataset includes experimentally obtained SRM parameters, which are used for practical implementation. The dataset supports the quantitative results, plots, and comparative analyses presented in the manuscript.