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

This dataset contains simulation results generated in support of the manuscript entitled “Torque Ripple Minimization in Switched Reluctance Motor Using Deep Deterministic Policy Gradient (DDPG) Based Actor–Critic Reinforcement Learning Control.” The data correspond to an 8/6 Switched Reluctance Motor (SRM) operating under different torque ripple minimization control strategies. All simulations were carried out using MATLAB/Simulink, and the resulting data were exported in Microsoft Excel format to ensure transparency, accessibility and reproducibility. The dataset supports the quantitative results, plots and comparative analyses presented in the manuscript, including torque ripple characteristics, speed response and control performance under varying operating speed conditions.