This study proposes a multi-objective finite control set model predictive control (FCS-MPC) for traction motor drive systems in electric/hybrid-electric vehicles. The proposed method seeks to find the most optimal drive with respect to three objectives, i.e., electric power quality, inverter thermal cycling, and motor thermal cycling. Suitable lumped-parameter thermal models are used for the inverter and the motor based on validated methods in the literature to estimate temperatures. The estimated temperatures are integrated into the multi-objective control law to obtain the desired trade-off performances from the drive system. This paper shows that by adding inverter and motor thermal models into the FCS-MPC, thermal cycling can be reduced in the inverter and the motor while maintaining satisfying speed/torque requirements. The proposed methodology is tested via a standard driving schedule for an interior permanent magnet traction motor in a hybrid electric vehicle.
Multi-Objective Finite Control Set Model Predictive Control for Interior Permanent Magnet Motors in Electric/Hybrid-Electric Vehicles
Sae Technical Papers
WCX SAE World Congress Experience ; 2022
2022-03-29
Conference paper
English
British Library Conference Proceedings | 2022
|British Library Conference Proceedings | 2022
|The Optimal Control System of Interior Permanent Magnet Motors for Electric Vehicles
British Library Conference Proceedings | 1996
|RADIALLY WOUND PERMANENT MAGNET MACHINES AS GENERATORS AND MOTORS FOR HYBRID ELECTRIC VEHICLES
British Library Conference Proceedings | 2007
|