Research On Battery Charge And Discharge Management And Key Technology Of Electric Vehicle

As an emerging industry that the country focuses on development,electric vehicles are the key to changing the energy structure.As the power core of electric vehicles,power batteries have become a key factor restricting electric vehicles.The battery management system can increase the cruising range,improve the battery life,and give the driver an accurate battery running status,including the battery’s basic current and voltage parameters,battery charge status and equilibrium status.This thesis takes the ternary lithium battery as the research object,mainly studies the battery SOC algorithm optimization and battery pack balance.Comparing a variety of lithium battery equivalent models,this thesis uses a second-order RC equivalent circuit model,and based on the actual test data of the battery’s mixed pulse power characteristic(HPPC),combined with the SOC-OCV curve,the model is identified online and offline.Based on the two identification results,an equivalent circuit model is built,and the actual test data is compared.The simulation results show that the accuracy of the offline model and the online model is not much different,but because the online identification model can be updated in real time according to different working conditions,this uses dissertation the online identified model.Based on the established equivalent circuit model,the principle of adaptive unscented Kalman filter algorithm(AUKF)estimation is analyzed.Aiming at the problem of relying on offline model parameters in the algorithm,which leads to large model error estimation,the least square method with forgetting factor is introduced to update the model parameters in real time,and the AUCF algorithm is used to perform SOC estimation to improve the SOC estimation accuracy.The data compares and analyzes the AUKF algorithm and the joint algorithm.The simulation results show that the joint algorithm can effectively improve the accuracy of the SOC estimation compared to the AUKF algorithm.For the problems of low balance efficiency,too many components and complicated control strategies in the current circuit balance topology,this thesis adopts an active balance circuit scheme based on inductance.This topology has the characteristics of fewer components and high efficiency.Through the principle analysis of the balanced topology,the relationship between the balanced current and the inductance value and the product of the switching frequency is inversely calculated quantitatively,and the maximum value of the duty ratio of each equalizer is calculated.The simulation of the two states of charging and discharging of the equalization circuit.The simulation results show that the topology has a faster and more stable equalization speed compared with the traditional inductive balance topology.In order to verify the correctness and feasibility of the SOC algorithm and equalization circuit,this thesis designs and builds a BMS hardware experimental platform,uses the STM32 chip as the main control chip to build a hardware experimental platform and conducts battery pack SOC estimation experiments based on the built hardware experimental platform and Balanced experiment.Carry out constant current discharge test and variable current condition test on the battery pack,and at the same time estimate the SOC of the battery pack,compare the theoretical value of SOC with the estimated value of SOC,and verify the validity and accuracy of the joint algorithm SOC estimation.In the state of charge and discharge,the battery pack is subjected to an equilibrium control experiment.The battery terminal voltage is used as the equilibrium judgment condition for battery balancing.The terminal voltage of the battery before and after balancing is compared to verify that the balancing topology can effectively achieve battery balancing.