Research On Energy Management Strategy Of Hybrid Energy Storage Electric Vehicle Considering Battery Performance Decay

Under the dual pressure of environmental pollution and energy shortage,pure electric vehicles have been favored by all sectors of society with their green,low-carbon,and energy saving.At present,as the mainstream energy source of pure electric vehicles,lithium batteries still have problems such as energy density and power density that cannot be taken into account,and the life span of cycling is short.As a power storage component,supercapacitrate has the advantages of high power density and long cycle life,which can make up for the lack of lithium batteries.Therefore,the combination of lithium batteries and supercapacitors into the structure form of a composite energy storage system came into being.The energy management control strategy is directly related to the effectiveness of the composite energy storage system.If the performance attenuation of the lithium battery performance is not considered during energy management design,it will cause lithium batteries to often work under bad conditions such as"frequent charging and discharge"and"high power charging and discharge".Instead,the performance of the battery is accelerated.This article uses composite energy storage electric vehicles as the research object.It aims to study the performance attenuation of lithium battery performance and formulate improved adaptive rules control strategies.The specific content is as follows:(1)Complete the performance attenuation experiment of lithium iron phosphate battery performance,and at the same time established a model attenuation model.By analyzing the consequences of the influencing factors of battery performance attenuation,evaluation indicators and capacity recession to the performance of the car,the lithium battery has designed the life of the current condition of the lithium battery in the constant charging and discharging conditions Attenuation time is equivalent to the settlement time of the constant charging and discharge model,as a method to establish a cycle life model of lithium iron phosphate battery.(2)A composite simulation model is built based on the Matlab/Simulink software.First of all,the topology structure of the composite energy storage system was analyzed,and the semi-active configuration method of the super electricity side was determined;secondly,on the basis of analyzing the vehicle dynamic model,the drive motor was selected and the parameter matching was selected according to the performance indicators of the vehicle.Then,by analyzing the condition of the motor power of the vehicle and the motor power of the composite energy storage system,based on the continuous power-energy(CPE)function,the supercapacitance is selected and parameter based on the continuity.Car models mainly include driver models,control system models,lithium battery models,super capacity models,DC/DC efficiency models,motor models,etc.(3)Design improvement of rules and energy management strategies based on the dynamic planning algorithm.First of all,the control target of reducing the performance attenuation of lithium battery performance.Then,based on the working mode of the composite energy storage system,the traditional logical retardation strategy is formulated,and the wavelets of battery performance degradation-fuzzy strategies are formulated based on the theory of blurring and wavelet control.In the end Taking the energy loss of the composite energy storage system as the target function,by introducing the proportion factor k_ato adjust the proportion of supercapacitor energy loss,a global optimal strategy model has been established,the global optimal energy management strategy distribution characteristics are analyzed,New York City Cycle(NYCC),Urban Dynamometer Driving Schedule(UDDS),and Highway Fuel Economy Test Cycle(HWFET)rules control strategy parameters of the type of operating conditions are calibrated.(4)Adaptive control and simulation verification of the energy management strategy of improved composite energy storage system rules.First of all,according to the speed and work conditions information,determine the characteristic parameters and divide the sample block online.Then use the gray wolf algorithm to optimize the minimum daily support vector machine,and in UDDS,HWFET and Chinese passenger cars under the comprehensive operating conditions of the species,the accuracy rate of the working conditions recognition model can reach 98.4%.Finally,an adaptive rules control strategy model is established,and the logical retrieval control strategy,the wavelet-blur control strategy are in the comprehensive operating conditions.The simulation comparison analysis was performed below.The simulation results show that the energy consumption of the vehicle’s energy consumption ratio of the vehicle is reduced by 6.62%and 2.5%,respectively,and the decay of lithium batteries by 12.6%and 8.9%,respectively.Therefore,the adaptive rules designed in this article can effectively reduce the attenuation of the lithium battery capacity,which will delay the life cycle of lithium batteries.