Optimisation of HF signal injection parameters for EV applications based on sensorless IPMSM drives

Abstract

The study proposes a parameter optimisation of the high-frequency (HF) signal injection sensorless algorithm applied to an interior permanent magnet synchronous machine (IPMSM). The latter is intended for electric vehicle (EV) traction applications with dedicated mission profile under specific constraints. This optimisation aims to minimise two conflicting objectives: (i) minimising the position estimation error which impacts the torque accuracy and (ii) minimising torque ripples responsible for additional stress on the motor shaft, causing unwanted noise in the vehicle powertrain. The main contribution of this study is to provide guidelines for the selection of the HF signal injection tuning parameters so as to satisfy these objectives. To do so, a genetic algorithm has been implemented and the optimisation process is based on a reliable simulation model. Using a simulation model is deliberately chosen in order to reflect the behaviour of a motor series. Besides, in order to integrate the specificities of the target application, the optimisation process is based on a typical EV mission profile. A set of non-dominated solutions satisfying the tradeoff between the position error and the torque ripples is obtained, discussed and finally tested with success on an experimental setup.