Sensorless-Based Speed Control of Switched Reluctance Drive using an Artificial Neural Network and Field Programmable Analogue Array for Automotive Applications

Abstract This paper presents a real time verification of an artificial neural network system with the field programmable analogue array (FPAA) control for the sensorless control of switched reluctance motor (SRM) in automotive drives. The rotor position estimation is done using the unsaturated instantaneous flux linkages and the current obtained by measuring the phase current and voltage. The converter analogue control is achieved with FPAA. The SRM automotive applications are currently getting special attention as the SRM has notable advantages such as robustness, low manufacturing cost and good size-to-power ratio. The experimental results for a 400 W 8/6-SRM prototype model are presented and compared with 500 W soft magnetic composite cored SRM.

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