Research On State Of Charge Estimation And Equalization Strategy Of Lithium Battery In Electric Vehicle Used In Cold Area

At present,the demonstration operation and marketing promotion of electric vehicles in the temperature moderate area have achieved good results.However,there are lots of obstacles to the application in cold areas.This is due to the harsh temperature environment in these areas.At low temperature,the performance of lithium batteries will decline dramatically.Therefore,it is necessary to carry out an efficient and reasonable management of battery packs in wide temperature range.State of charge(SOC)is one of the important parameters in the battery management system.Ambient temperature will have a serious impact on the cell characteristics,so that the existing SOC estimation algorithms can not be accurately estimated.With the popularization of electric vehicles in cold areas,the algorithm of SOC estimation is urgently needed to solve the problem of high precision,wide temperature range and multi temperature condition.The equalisation strategy is one of the most important components of the equalisation management technology.However,the inconsistency of the characteristic parameters of the battery will lead to the error of the existing equalization criterion,which will lead to the problem of over equalization.With the development of active equalization technology,it is urgent to reduce the degree of over equalization and improve the accuracy of equalization strategy.The purpose of the subject is to solve the problem of the accurate SOC estimation in the wide temperature range,and the precision of the battery pack equalization strategy considering the inconsistency of parameters.It provides the key technology and theoretical basis for the application of electric vehicles in cold areas.The main contents of this subject are as follows:To improve the accuracy of battery model at different temperatures,the temperature charateristics of lithium batteries are studied.A battery experimental and the battery experimental content are developed.To provide the basis for widening the temperature scope of Ampere-hour counting,the influence of temperature and current on capacity and coulombic efficiency are analyzed qualitatively.Open-circuit Voltage(OCV)is an important characteristic in SOC estimation.Through comparing the SOC-OCV curves under constant and alternated temperatures,the cause of OCV migration under different temperature paths are achieved,which provide the theoretical basis for accuracy SOC estimation.Analyzing the relationship between the model parameters and temperature,the results show that the temperature will affect the dispersion of the model parameters,which increases the misjudgment of the equalization strategy.Aiming at accurate SOC estimation in the wide variable temperature range,SOC estimation based on multi-temperature path OCV and extended ampere-hour counting method is proposed.By establishing the model of OCV-SOC under the multi-temperature path,the accurate estimation of the SOC initial value is realized.The applicable temperatre range of traditional ampere-hour counting is broaden through the model establishment between capacity,coulombic efficiency and temperature,and the construction of SOC transfer equation among different temperatures.The experimental results show that the SOC estimation accuracy is higher under the variable temperature condition than the constant temperature condition.When the temperature increases from-30℃ to 40℃,the maximum error(ME)is 2.3%,and the root mean square error(RMSE)is 1.0% for lithium titanate(LTO)battery.Compared with the traditional OCV and ampere-hour counting method,the ME is reduced by 8.0%,and the RMSE is reduced by 3.3%.Aiming at online estimation of battery model parameters and SOC in the wide constant temperature range,SOC estimation based on parametric estimation-based OCV(OCVPE)under variable temperatures is proposed.Using the new information sequence to update the system and measurement noise covariance in real time,the accuracy and stability of the online estimation of the state and parameters of the battery model based on the joint extended Kalman filter is improved.By establishing the relationship of OCVPE,SOC and temperature,the SOC system error based on OCVPE is reduced.Experimental results show that the SOC estimation accuracy is higher under the constant temperature condition than the variable temperature condition.Under-30℃ constant temperature,the ME is 3.9%,and RMSE is 1.2% for LTO battery.Compared with the traditional coulomb titration OCV based method,the ME and RMSE is reduced by 9.7% and 8.0%,respectively.Aiming at the precision of equalization strategy under the condition of inconsistent parameters in battery pack,equalization strategy based on fuzzy thermodynamics SOC is proposed.Through the establishment of equalization criterion based on the thermodynamic SOC,the equalization destination of real state consistency can be achieved.Based on the SOC error,fuzzy control theory is used to cut down over-equalization.The experimental results show that the maximum voltage difference of the balanced battery is reduced to 0.008 V at the initial maximum voltage difference(MVD)0.059 V for 5 series battery pack.Compared with the voltage based equalization strategy,the MVD is reduced by 0.024 V.