Research On Energy Management Strategy Of Electric Vehicle Based On Driving Condition Prediction

Power battery technology has made great progress in recent years,but the energy density development of which has encountered bottlenecks,resulting in limited driving mileage.Therefore,how to improve the energy efficiency of electric vehicle has become the primary problem in the development process of electric vehicle.The specific cycle conditions are usually used as input,and the driving intention is considered to achieve the adjustment and distribution of output power to improve the energy utilization of electric vehicle under current energy management strategy for electric vehicle.However,this method has poor adaptability to complex driving conditions.Therefore,single power electric vehicle is taken as the research object in this paper.When the driving electric load is directly affected by the driving conditions and the load disturbance of the electric air conditioner exists,in order to improve the self-adaptive adjustment ability of the energy management strategy to the uncertainties of the driving conditions,the energy management strategy based on the driving prediction is studied using multiple variables and constraints as input conditions.Specific contents are as follows:(1)The driving conditions are predicted and analyzed in the light of the typical driving conditions of electric vehicle.The combined driving conditions are constructed,and the features parameters of driving conditions are clustered.Four driving conditions are obtained,including urban central area,urban residential area,urban suburbs,highway.On this basis,the actual driving condition of vehicles is predicted and analyzed based on Markov theory,which provides a basis for energy management strategy based on driving condition prediction.(2)The model of electric vehicle energy management system is established.On the basis of the working characteristic test curves of power battery and motor,the battery model and motor model are built by using experimental data modeling as the main method.The model also includes vehicle dynamics model,air conditioning system model,driver model,driving prediction model and vehicle energy consumption model.(3)The energy management strategy based on condition prediction is studied.Based on the model of energy management system and the prediction results of driving condition,firstly,the logic threshold strategy based on condition prediction is analyzed.Then,a fuzzy controller of energy management based on fuzzy control is constructed.The driving condition category,SOC and temperature of battery and pedal opening are determined as input variables of the fuzzy controller,and the power distribution coefficient and motor output torque are taken as output variables.Next,the fuzzy control rules based on driving condition prediction are obtained.Finally,the simulation results of fuzzy control strategy based on condition prediction are compared with logic threshold strategy based on condition prediction under NEDC,UDDS and WLTC conditions.The battery energy consumption rate under three typical conditions is reduced by 8.14%,9.31% and 10.54% respectively.The results show that the fuzzy control strategy based on condition prediction can better exert the energy saving potential of electric vehicle.(4)The energy management strategy based on rapid prototyping development platform is tested and validated.The hardware in the loop test system platform and the energy management strategy algorithm are built,and the hardware in the loop test of the fuzzy control strategy based on condition prediction is completed under NEDC and UDDS conditions.In addition,the fuzzy control strategy based on driving condition prediction is verified by the drum test under NEDC condition.The results indicate that the proposed strategy can significantly realize the energy management of electric vehicle and ameliorate the energy efficiency of electric vehicle.