MRAS-based sensorless control of AFPMSM using minimum current point tracking to reduce multiple parameter variation effects

Abstract

In this paper a novel approach is presented to tune the application of sensorless control strategy based on the model reference adaptive system method (MRAS-based). Thus the influence of multiple parameter variations on the control is balanced. The method was used for speed and position estimation of a field-oriented controlled (FOC) wheel hub drive with an axial flux permanent magnet synchronous motor (AFPMSM). Parameter deviations could be described mathematically as disturbances of the MRAS scheme. Their influences are reduced by an enhancement of the fundamental wave model. The investigated tuning method compensates the mean value of the flux orientation angle error of the sensorless control caused by parameter variations using these occurring disturbances. In order to investigate the proposed method, a model-based system engineering (MBSE) approach was chosen to compare simulation and experimental results. The simulation study of the control strategy was performed using MATLAB®/Simulink®. Further on, the MRAS-based method was implemented on a target system directly from the simulation model using code generation software. A performance evaluation of the tuning application boundaries is focused on accuracy, sensitivity and stability of the control. The dynamic response can be calculated.