Research On Energy Optimization Control Strategy Of Hybrid Electric Vehicle With Composite Power Supply

Hybrid electric vehicle(HEV)not only takes into account the energy-saving and environmental protection characteristics of pure electric vehicle,but also inherits the advantages of long driving distance of traditional fuel vehicle,which is one of effective scheme in the field of new energy vehicle research.In this paper,taken a parallel hybrid electric vehicle as the RD background,the power system model of the hybrid electric vehicle is constructed.The state of charge(SOC)estimation method of battery based on particle filter(PF)optimized by particle swarm optimization(PSO)is proposed.The power distribution control strategy of the composite power supply based on the wavelet decomposition is designed.The torque distribution control of the whole vehicle energy management is proposed and verified by simulation.The controller of the hybrid electric vehicle based on TMS320F2812 is designed.The control strategy of motor speed based on the optimization of fuzzy rules by genetic algorithm is used and verified by hardware in the loop simulation.According to the power performance requirements of hybrid electric vehicle,the matching calculation and selection of engine,motor and energy storage components are completed in this dissertation.The simulation model of the parallel hybrid electric vehicle is established,including engine model,drive motor model,energy storage component model,transmission model and vehicle driving dynamics model.The composite power supply is designed,which is composed of the power battery,super capacitor and DC-DC power converter.To monitor the SOC of the battery,the recursive least square method with forgetting factor is designed to identify the unknown parameters in the equivalent circuit model.Based on the parameters of charge-discharge multiple,temperature and number of cycles,a real-time SOC estimation algorithm based on PF is designed.For further accurate estimation of SOC,a PF estimation method based on PSO algorithm optimization is proposed.It can effectively solve the problem of uncertain filtering noise in the process of SOC real-time estimation and realize the accurate estimation of SOC state of battery real-time.In order to improve the performance of the vehicle and extend the life-span of the battery,the power splitting control strategy of composite power supply system is designed.The power splitting control strategy based on the logic threshold filter and the power split control strategy based on wavelet transform on basis of cascading and reconstruction of signal are proposed to split the power.They are verified by ADVISOR that the designed power splitting strategy can effectively reduce the required power of the battery and extend the life-span of the battery.Based on the proposed power splitting control strategy of composite power supply system,the motor auxiliary control strategy is established,which takes the engine as the main power source and the motor to supplement the engine torque as the core.In order to improve the average working efficiency of the engine,a T-S fuzzy torque distribution controller based on the optimal torque curve of the engine is designed to keep the engine working in the high efficiency area and maintain the battery charge and discharge balance.A fuzzy torque distribution control strategy based on PSO optimization is proposed and combined with wavelet power split strategy to form a vehicle joint control strategy.The optimized joint control strategy further improves the average work efficiency of the engine.Taking the DSP TMS320F2812 as the main control chip,the development of electronic control system of hybrid vehicle is completed.Through the battery management system test and motor speed control test,the effectiveness of the developed control system is verified.To response the energy distribution control strategy of hybrid electric vehicle engine and motor rapidly,the mathematical model of BLDCM is established.The fuzzy speed controller of BLDCM is designed and the genetic algorithm is used to optimize the fuzzy rules.The optimized control strategy is verified by the rapid prototype experiment platform based on d SPACE and the results show that the speed following performance of the designed speed controller is significantly improved.