Dual Closed-Loop Position Observer With Nonlinearity-Decoupled Model for Feature- Flux-Based Sensorless SRM Drives

Abstract

The feature-flux-based sensolress drives is attractive for switched reluctance motor (SRM) because its simple implementation and high reliability. However, its low model-utilization rate inevitably leads to the discrete position estimation manner. As a result, high frequency noise may cause significant estimation errors. For this problem, a position-adaptive dual closed-loop observer is proposed based on the nonlinearity decoupled model. First, a nonlinearity-decoupled flux model is studied to remodel the continuous linearized position-relevant function. Then, the position-adaptation law is designed to force the remodeled function adapt to the actual position. With the real-time regulation in the dual closed-loop structure, the continuous position estimation can be realized with high-frequency noise suppression. Finally, the studied observer is experimentally verified on an 8kW SRM platform.