Research And Verification Of SOC Estimation Method For Power Batteries Based On FUKF

With the development of environmental problems,countries around the world have reached a consensus on the development of alternative fuel automobiles,and China has listed it as one of the strategic emerging industries.Among alternative fuel automobiles,electric automobiles are in the spotlight.As the core components of electric automobiles,Battery and Battery Management System(BMS)directly restricts the development of electric vehicles.Among them,SOC estimation,as the core technology of BMS,is a hot issue in current research.Based on a ternary lithium ion battery made in China,this paper studies the problem of battery charge state estimation,and mainly does the following work:Firstly,the structure and working principle of lithium ion battery are deeply understood,and the advantages and disadvantages of existing lithium ion battery models are summarized.Thevenin equivalent circuit model,which can accurately simulate the external characteristic curve of the battery under charging and discharging,is selected.Thevenin equivalent circuit model,which can accurately simulate the external characteristic curve of the battery under charging and discharging,was selected.The important factors affecting the accuracy of the battery model,such as temperature,cycle life,charge/discharge ratio and so on,are analyzed.Then,relevant experiments are carried out to obtain the parameters of the equivalent circuit model selected in this paper.Then,the model accuracy was verified by charging condition,HPPC condition and ECE condition,and the experimental results showed that the model accuracy was good.Secondly,the principle,shortcomings and progressive improvement process of kalman filter algorithm are introduced.The EKF and UKF models are built and their accuracy is compared.The UKF algorithm with better accuracy is selected as the basic algorithm.The estimation process and principle of UKF algorithm are introduced in detail,and fuzzy control is introduced to adjust Rk value,so as to speed up UKF's correction of initial value and reduce the error of estimation process.Then,three working conditions were applied to verify the convergence speed and estimation accuracy of the improved FUKF algorithm.The verification results show that FUKF can correct the initial value faster than UKF and stabilize the estimation error in a small range.Then,the software and hardware design of the algorithm verification platform is described.The overall hardware scheme is based on MC9S12XDP512 as the main control chip,using ACS712 and ADS1115 to collect the current,and AD7280 A to collect the voltage and temperature.For the software,the general idea is to collect the voltage and current of the battery after initialization,and then use the collected data as the algorithm input to obtain the SOC estimated output,and then upload the output to the upper computer for reciprocating operation.In the algorithm part,Simulink automatic code generation technology is used,and the fuzzy control in the algorithm is simplified considering the computing power of single-chip microcomputer.Finally,a battery testing platform was built and the charging condition,pulse discharge condition and ECE condition were designed to verify the performance of the algorithm in the embedded system.The experimental results show that the performance of FUKF algorithm in embedded system differs little from the simulation,with good stability and high estimation accuracy.