| Lithium-ion batteries(LIBs)are widely used in the civil aviation field due to their high energy density and high cycle life and play a key role in the electrification of civil aviation aircraft.The application of LIBs in civil aviation faces the extreme environment of high temperature and low pressure,and LIBs have many problems such as low specific capacity,serious attenuation,poor cycle rate performance and potential safety hazards.Therefore,the development of efficient battery management systems(BMS)is essential for LIBs in the development of civil aviation.The state of charge(SOC)of the battery is one of the most critical parameters in the BMS.In this study,lithium titanate batteries(LTBs)were taken as the research object,and experiments and estimation methods were carried out on the estimation of the SOC of LTBs in high and low temperature and low pressure environments through research literature and reference to relevant standards:(1)Aiming at the direct estimation method of battery SOC,the ampere-hour integral method is studied in depth,its shortcomings are analyzed,and corresponding improvement measures are proposed.According to the discharge characteristics of LTBs at different temperatures and rates,an extended Peukert equation is proposed to improve the ampere-hour integral method.The extended Peukert equation considers the influence of temperature and magnification on the estimation of the SOC and reduces the initial error and the accumulation of errors in the estimation process.At the same time,the influence of Coulomb efficiency and battery aging on ampere-hour integral estimation was also corrected.The verification shows that the maximum error of the improved ampere-hour integration method is 6%.(2)Given the more advanced and comprehensive battery model estimation technology in BMS,this thesis carries out the research on the equivalent circuit modeling(ECM)of LTBs in high and low temperature,and low-pressure environments.In this thesis,a third-order Gaussian equation of SOC-OCV suitable for high and low temperature,and low pressure environments is proposed,and the ECM of LTBs is established.The influence of equivalent circuit modeling of LTBs in high and low temperature,and low-pressure environments was discussed,and the performance test of batteries at different temperatures and different ambient pressure environments was carried out to obtain key data required for equivalent circuit modeling.The equivalent circuit model has a maximum root mean square error of0.06.(3)Aiming at the estimation of SOC of high and low temperature,and low pressure LTBs based on the model,this thesis combines the ECM of high and low temperature and low pressure environment of LTBs and uses the extended Kalman filter(EKF)algorithm and the unscented Kalman filter(UKF)algorithm to estimate the SOC.According to the characteristics of the estimation process of the Kalman filter algorithm,to solve the noise covariance of the model and measure the covariance,the particle swarm optimization(PSO)algorithm is introduced to optimize the covariance matrix.Verified by the SOC estimation of lithium titanate battery under different current working conditions in high,low temperature and low pressure environments,it can be seen that the maximum estimation error after optimization is 0.2%.The SOC estimation of LTBs in high and low temperature,and low pressure environments studied in this thesis improves the accuracy and practicability of the algorithm by correcting and improving the ampere-hour integral method.In the estimation based on the battery model,the SOC-OCV equation based on the high and low temperature,and low pressure environment is proposed,which solves the problem of parameter identification and model accuracy.At the same time,the optimization of the covariance matrix improves the estimation accuracy of the algorithm.This thesis has engineering application and reference significance for the safe and efficient application of LTBs in civil aviation and the improvement of the BMS. |
PDF Full Text Request