Research On Optimizing A New Power System And Control Strategy Of Extended Range Electric Vehicle

In recent years,due to the pressure of the energy crisis and the impact of environmental pollution,governments of various countries have increased their research and development of new energy vehicles and formulated a series of policies to promote the development of the new energy vehicle market.Plug-in hybrid electric vehicles combine the advantages of pure electric vehicles and traditional fuel vehicles.As a plugin electric vehicle,the extended-range electric vehicle has become a new energy vehicle with great market prospects and development potential.In order to overcome the low efficiency of the extended-range electric vehicle under high-speed conditions and make full use of the engine and drive motor,this paper takes a new range-extended electric vehicle as the research object,matches its power system parameters,and proposes the engine three operating point control strategy and front and rear control strategies.Axleindependent drive control strategy.According to different working conditions,the level of power battery SOC,and the size of the required power,the car can freely switch between different working modes;the whole vehicle is modeled and simulated in the simulation software,and used The target genetic algorithm optimizes the performance of the whole vehicle.The specific research content includes:(1)The configuration of a new extended-range electric vehicle power system is introduced in detail.The power system is designed to include an engine,an ISG(Integrated Starter Generator)motor,a drive motor,a power battery,a motor controller,an external plug,and parallel shaft gears.Pair,the first clutch,the second clutch,the first reducer,the second reducer;the parallel shaft gear pair includes: input shaft,first output shaft and second output shaft;therefore,through the separation and coupling of the clutch,the new type increases Programmable electric vehicles can achieve independent driving of the front and rear axles.After analyzing the structure of the power system and the performance requirements of the vehicle,in order to meet the dynamics of the vehicle,the power system is matched with the parameters and the key components are selected,and the drive motor,Power battery,range extender,front and rear axle transmission ratio,ISG motor parameter values,lay the foundation for vehicle energy management strategy and power system modeling.(2)The basic principle of rule-based energy management strategy was studied,and the three-point control strategy was proposed.Three efficient working points were selected from the engine fuel economy optimal working area,and the low-load working point,high-load working point and medium-load working point were selected according to the required power.The structure of the power system is optimized.By adding parallel shaft gear pair and clutch,the engine can be mechanically connected at high speed to drive the rear shaft directly.An energy management strategy based on the deterministic rule is proposed,which determines the start and stop of the engine based on the required power and the size of the SOC,and determines the operating point of the engine based on the four threshold values of the proposed speed.According to different working conditions and the status of the vehicle power system,the working modes can be divided into pure electric drive mode,engine direct drive mode,engine and ISG motor range extension mode,engine rear drive range extension mode,drive motor front drive engine range extension mode,engine rear drive vehicle charging mode,hybrid four-wheel drive mode.Finally,the energy flow of different working modes is analyzed.(3)After determining the basic principles of the energy management strategy,in order to reduce the development cost of the vehicle and speed up the research progress,the proposed dynamic system simulation model of the front and rear axle independent drive was established on the Matlab /Simulink simulation platform,and the switching threshold and mode selection of the control strategy were realized by the function function.The model includes power battery model,engine model,main drive motor model,driver driving model,vehicle dynamics model,energy management model,front and rear drive axle model and ISG motor model.The control strategy proposed in this paper is simulated based on the NEDC working condition,so as to verify the accuracy of the power system parameter matching,verify the feasibility of the three operating points of the engine,and verify the rationality of the control strategy,which provides a reference for the optimization of control strategy and power system parameters.The simulation results show that the simulation speed can well follow the change of the target speed,which indicates that the parameters of the power system can meet the demand of dynamic performance,and the control strategy proposed in this paper can respond to the change of working conditions.(4)The power system parameters and energy management strategies are optimized based on multi-objective genetic algorithm.Taking the comprehensive energy consumption of the vehicle per 100 kilometers as the objective function,the power consumption of the vehicle is equivalent to the fuel consumption.Under NEDC operating conditions,the first threshold of vehicle speed,The second threshold of vehicle speed,the third threshold of vehicle speed,the fourth threshold of vehicle speed,the engine power at engine operating point one,the engine power at engine operating point two,the engine power at engine operating point three,the reduction ratio of the first reducer,The reduction ratio of the second reducer is an optimized variable.The range of the optimized variable is calculated through theoretical calculations,and the range of the optimized variable is used as a constraint condition to obtain the optimized fuel consumption value and the optimal combination of parameters,and optimize the previous 100-kilometer integration The fuel consumption is 5.6279L/100 KM.After optimization,the comprehensive fuel consumption per 100 kilometers is4.0236L/100 KM.Compared with the optimization before,the fuel consumption level is reduced by 28.51%.Analyzing the operating point of the engine and the driving motor,it can be found that its working performance is average.After the optimization,the operating points in the high-efficiency zone are compared with those before the optimization.After optimization,there are more operating points in the high-efficiency zone,which is an increase of 15% compared to before the optimization.The change curve of the power battery SOC is analyzed,and the optimization can be obtained.The SOC decline curve of SOC is slower.These simulation results verify the feasibility of the optimization method,and further conclude that the extended-range electric vehicle with independent driving of the front and rear axles proposed in this paper has good power performance and fuel economy.