MRAS-Based Sensorless Vector Control of Wheel Motors

Traditional vector control needs the installation of mechanical sensors to gather rotor position and speed information in order to enhance the control performance and dynamic quality of electric vehicle wheel motors, which increases system cost and reduces system reliability and stability. On the basis of Popov's super-stability theory, an appropriate adjustable model and reference model are constructed, and the system's reference adaptive law is determined. Furthermore, to solve the problem of the standard PI regulator's poor anti-interference capabilities in speed controllers, the approach of utilizing a sliding-mode speed controller in the speed loop is presented. Finally, a MATLAB/SIMULINK simulation model is created to simulate the motor in three scenarios: no-load start, abrupt speed change, and sudden load change, and a permanent magnet synchronous motor experimental platform is created to validate the control approach. The findings demonstrate that this technique can estimate speed and position data accurately and fast, with strong immunity to interference and robustness, and that it can fulfill the demands of actual wheel motor control performance.