Research On State Of Charge Estimation And Intelligent Balance Management Technology Of Lithium Battery Pack

As an emerging industry in China,lithium battery new energy,especially power lithium battery,is an important measure to deal with the challenges of environmental pollution and energy depletion and accelerate the transformation of energy supply mode.Compared with traditional batteries,lithium batteries have high specific energy and no memory effect.However,the current application requirements of new energy vehicles can not be fully met.The existing problems include the limitation of manufacturing process,the failure of battery group application technology to achieve absolute safety,and the difficulty in measuring the residual capacity and service life of batteries.Therefore,in practical application,we need to design battery management system(BMS)to estimate the state of charge(SOC)of lithium battery and balance the battery pack.Under the premise of ensuring the safety of the battery pack and not shortening the battery life,the maximum utilization of its capacity can be realized.The research focuses on the SOC estimation and battery balance management in BMS.The contents are as follows:(1)Taking 18650 ternary nickel cobalt lithium manganate battery as the research object,the problems of internal resistance,nonlinearity and inconsistency of battery pack which have great influence on SOC estimation are studied.(2)Based on Thevenin’s first-order equivalent circuit model,the static and dynamic experiments are designed.The parameters of the battery model in different SOC stages are identified by using the least square method.Then the accuracy of the battery model is measured by Simulink simulation,which provides the battery model for the following SOC estimation algorithm.(3)The SOC estimation method of battery is studied.Based on the time-saving integration method,the unscented Kalman filter(UKF)and Lebesgue sampling(LS)algorithm are constructed.The SOC of the battery is corrected by sections and verified by simulation.In order to prove the superiority of the proposed algorithm,the estimation accuracy,robustness and computational complexity of the traditional algorithm and 1s-ukf algorithm are compared and analyzed.(4)The method of battery equalization is studied.Based on the existing equalization circuit,the design of the dual equalization circuit includes two parts:layered strategy and multi criteria.The main principle is to use inductors to transfer energy.According to the location of the battery and the equalization sub unit,different equalization paths,equalization frequency and equalization threshold are formulated.By adjusting them,the balanced sub unit is controlled to realize the cell monomer Module equalization.Ensure that in the process of battery charging and discharging,under the premise of preventing battery overcharge and overdischarge,maximize the utilization rate of battery capacity.Compared with the traditional method,the binary equalization circuit has the advantages of convenient control,high equalization efficiency,small energy loss and flexible expansion.