High-Precision and Robust Control of PMSM-Based Flywheel Energy Storage System Using Fractional-Order Sliding-Mode Strategy with IHAOAVOA-Based Parameter Tuning

PMSM-based flywheel energy storage systems require fast and robust speed regulation in the presence of parameter uncertainty, load disturbances, and measurement noise, while avoiding the cost and reliability limitations associated with mechanical encoders. This paper proposes a sensorless control framework that combines a fractional-order sliding-mode speed controller with a fractional-order sliding-mode observer. To improve dynamic performance, an improved hybrid Aquila Optimizer–African Vulture Optimization Algorithm (IHAOAVOA) is employed to tune the controller parameters, while the observer follows the proposed robust sensorless design. Simulation results show that at the 1000 rpm operating point under a 20 N·m load disturbance, the proposed method limits the startup overshoot to about 0.24%, compared with 8.02% for the PI control and 9.74% for the conventional sliding-mode control. After the disturbance is introduced at t=1.0 s, the speed drop of the proposed method is limited to 2.80%, whereas those of the PI control and conventional sliding-mode control reach 7.20% and 5.60%, respectively. At the 8000 rpm operating point under an 80 N·m load disturbance, the proposed method maintains the same advantage, with an overshoot of about 0.04% and a speed drop of 1.88%, both lower than those of the two benchmark controllers. In sensorless operation, the sensorless scheme with the IHAOAVOA-tuned speed controller also improves transient estimation performance. At the 1000 rpm operating point, the maximum startup speed estimation error is reduced from 41.8 r/min to 34.8 r/min. At the 8000 rpm operating point, the estimation error enters the ±10 r/min band at 0.0671 s, compared with 0.0718 s for the PSO-tuned case. The electromagnetic torque responses further indicate that the proposed tuning strategy improves transient torque smoothness while maintaining comparable steady-state torque behavior. These results demonstrate that the proposed control framework provides an effective balance among fast dynamic response, disturbance rejection, sensorless estimation accuracy, and electromechanical transient smoothness for PMSM-based flywheel energy storage applications.