Parameter Identification and Model Predictive Torque Control for Flywheel Energy Storage Systems with Permanent Magnet Synchronous Motors

This paper presents a parameter identification technique and a model predictive torque control (MPTC) approach for the flywheel energy storage system (FESS) using a permanent magnet synchronous motor (PMSM). The study addresses the challenges of parameter uncertainties and mismatches, which can impact control performance. A two-step identification method is utilized to overcome the rank-deficient problem in the PMSM model. An adaptive MPTC strategy based on the Recursive Least Squares (RLS) algorithm with a forgetting factor is proposed to enhance system robustness. Simulation results demonstrate the effectiveness of the RLS-MTPC approach in achieving accurate control and mitigating parameter uncertainties.