Research of parameter self-learning fuzzy control strategy in motor control system for electric vehicles

Based on the vector control method for PMSM, a parameter self-learning hybrid fuzzy controller was implemented to provide the speed control for the EV propulsion system with the purpose to obtain the maximum acceleration during starting and accelerating. A three-term fuzzy controller is implemented by simply using a two-term fuzzy control rule-base without any increase of rules. The method of fuzzy deduction based on phase plane had less computational burden, while the fuzzy inputs could be continuous. The control parameters are self-tuned by introducing a single neuron together with a back-propagation learning algorithm. This method has simpler structure and control algorithms and can be realized online easily. The simulation results and experiment results of 18 kW PMSM for electric vehicle propulsion are given, the experiment results show that the electric vehicle with parameter self-learning hybrid fuzzy vector control system has excellent performances of starting, accelerating and cruising on road.