Research On Control Strategy Of Switched Reluctance Motor System For Solar PV Hybrid Electric Vehicle

With the increasing depletion of fossil fuel resources and severe air pollution,hybrid electric vehicles have received widespread attention in urban transportation.For hybrid electric systems,Switched Reluctance Motor(SRM)is considered as a competitive candidate solution in its application field due to its advantages such as rare earth free,simple and sturdy structure,low cost,high reliability,wide speed range,no winding on the rotor,and good fault tolerance.However,battery technology and the cost of charging station construction have limited the popularity of hybrid electric vehicles in urban transportation.Solar energy,as one of the alternative sources of traditional energy,embraces broad development prospects due to its advantages of environmental protection and sustainable development.Therefore,this thesis conducts research on the control strategy and torque ripple suppression of the switched reluctance motor system for solar PV hybrid electric vehicles.Firstly,this thesis gives an introduction to the working modes and operating states of solar PV hybrid electric vehicles with the energy flow of the system under each working mode was analyzed.Different working modes were assigned based on the operating state of the vehicle.On this basis,combined with the principle of switched reluctance motor,a multifunctional,multi-level drive,and integrated charging capability topology structure of a solar PV hybrid electric vehicle switched reluctance motor system is proposed.The energy flow of the power converter in different working modes and commutation intervals in the proposed topology structure is analyzed.Secondly,to verify the effectiveness of the proposed system topology,current chopping control,voltage chopping control,and angle position control are applied to the proposed system topology,respectively.The simulation and experimental results show that the proposed system topology can effectively implement three control strategies,and its multi-level voltage can accelerate the excitation and demagnetization processes,correspondingly increasing the output torque of the motor.Then,aiming at the shortcomings of the three traditional control strategies,in order to improve the dynamic response and robustness of the system,a direct instantaneous torque control strategy based on improved nonsingular fast terminal sliding mode is proposed and compared with the traditional Sliding mode control strategy.Simulation and experimental results show that the improved nonsingular fast terminal Sliding mode control strategy can effectively improve the system dynamic response and reduce the impact of load changes on the system.Thirdly,in response to the issue of short driving distance for vehicles in pure battery drive mode,based on the proposed system topology,four modes were designed: PV battery charging,generator control unit charging,external DC grid charging,and external AC grid charging.The equivalent circuit of each charging mode was analyzed,and the current path was given.Different control strategies were proposed according to different charging modes.In addition,in the charging mode of the external AC power grid,the gray wolf algorithm was used to optimize the controller parameters to further improve the charging performance of the system.The simulation and experimental results demonstrate the effectiveness of the proposed charging control strategy.Fourthly,the doubly salient structure of switched reluctance motors endows them with highly nonlinear characteristics,resulting in significant torque ripple under traditional control methods.The principle of torque ripple generation in switched reluctance motors was analyzed.Based on the torque allocation function,fuzzy control was introduced to design a fuzzy controller to replace the traditional speed regulator.Simulation and experiments have shown that the proposed method can effectively suppress torque ripple.On this basis,a model predictive torque control strategy based on candidate voltage vector optimization is proposed.The motor’s electrical cycle is divided into 8 sectors through the ideal torque angle characteristics of the motor,and the commutation region of the motor is redefined.The candidate voltage vectors for each control cycle are reduced to 2 or 3,reducing the switching frequency and computational complexity.Simulation and experiments have shown that compared with fuzzy control,the model predictive torque control strategy has better torque ripple suppression effect.