On-line estimation of switched reluctance motor parameters

This paper addresses the problem of on-line parameter estimation of switched reluctance motors and provides, to the best of the authors' knowledge, the first result that takes into account the dynamics of both electrical and mechanical subsystems. Based on a widely-used standard model of the motor and establishing a reasonable structure for modeling the unknown load torque, a linear parametric model is derived and a 2-stage identification scheme is proposed and implemented with the recursive least-squares algorithm with forgetting factor. It is assumed that stator voltages and currents and rotor position and speed are available through measurements. Numerical simulations and experimental tests are included for a 3-phase 12/8 switched reluctance motor. The results show a good performance of the proposed methodology, and the estimated parameters are validated through their use in a closed-loop control scheme. Key features of the proposed solution are that it does not rely on locked-rotor tests nor does it assume previous knowledge of the magnetization curves of the motor. The estimation scheme is intended to improve the performance and efficiency of currently available control algorithms, and it is potentially useful for the design of selfcommissioning switched reluctance drives, ie, drives that can automatically adjust the controller parameters for a wide range of motors and loads.