Study On The Algorithm Of SOC Estimationfor Lithium-ion Power Battery With LiNi_0.5Co_0.2Mn_0.3O₂ Cathode Materials

The state of charge?SOC?of the battery is an important parameter in the battery management system.The accurate SOC estimation can improve the safety and service life of the battery.In this paper,it takes lithium-ion batteries with LiNi_0.5Co_0.2Mn_0.3O₂ cathode materials as the research object.On the one hand,the impact of discharge cut-off voltage on the battery performance has been researched to regulate the use of the battery,and improve the service life of the battery;on the other hand,in order to obtain an estimation method with high efficiency and accuracy,the SOC estimation algorithms for the 18650 type lithium ion battery have been studied.The details are as follows:?1?A series of experiments are designed to study the effect of discharge cut-off voltage on the performance of lithium ion battery.The experimental results show that the most suitable discharge cutoff voltages of the battery in the current density 0.1,0.2,0.5,1.0,1.5 and 2.0C are 3.6,3.4,3.4,3.4,3.4 and 3.2V,respectively.In this case,the battery has a high discharge capacity,discharge capacity retention rate,discharge mid-point voltage retention rate and a smaller degree of deterioration of materials.In addition,the improvement of the discharge cut-off voltage can effectively improve the rate performance of the battery,and the discharge capacity of the battery under the current density of 2.0C increased from 56.4mAh/g to 111.6mAh/g.?2?On the one hand,two equivalent circuit models are established based on the charge discharge test data and the AC impedance test data.On the other hand,two working conditions?condition 1 and condition 2?are designed based on the most commonly used two car test conditions ECE_EUDC and UDDS,and corresponding to mountain road and highway,respectively.Finally,the simulation models of two equivalent circuits are built by using MATLAB,and the accuracy of the two models in the two conditions is verified.Test results show that the model 1 is more applicable to complex and variable conditions,and the model 2 is more suitable for more stable conditions.?3?Four algorithms with smoother are designed for SOC estimation,which include extended Kalman filter + model 1?EKF_1G?,sliding mode observer + model 1?SMO_1G?,extended Kalman filter + model 2?EKF_2G?and sliding mode observer + model 2?SMO_2G?.SOC estimation results show that the EKF_1G algorithm has better robustness and estimation performance but it takes a long time;the estimation performance of EKF_1G algorithm and SMO_1G algorithm are similar,but the SMO_1G algorithm takes less time and robustness;the estimation performance of SMO_2G algorithm in stable condition?condition 3?can basically meet the requirements,and the computation time is less than 1/7 of the SMO_1G algorithm;while the EKF_2G algorithm is not suitable for practical use.Finally,this paper designed a composite algorithm?FH?based on the previous experimental results,and compared with the EKF_1G algorithm and SMO_1G algorithm.The test results show that the FH algorithm shows the best performance in the composite condition?condition 3?with the minimal root mean squared error?0.0223?,the minimum calculation time?less than 1/3 of SMO_1G algorithm?and the smaller average absolute error?0.0185?,and compared with other two algorithms has great superiority.