Type-V exponential regression for online sensorless position estimation of switched reluctance motor

The idea of sensorless position sensing of switched reluctance motor (SRM) is attractive to researchers because of the increased reliability, robustness, and cost reduction compared to conventional drives. Sensorless drive is particularly useful in electric transportation applications where the environment is too hostile for physical position sensors, such as inside an electric car or bus. This paper presents a new method to estimate the motor positions during startup or at flying restart. Unlike most of the methods described in the literature, the algorithm, based only on the general magnetic characteristics of an SRM, can provide exact rotor positions without specific motor magnetic information. The calculation is simple and can be implemented easily and efficiently with a microcontroller by users in industry.