Research On SOC And SOP Estimation Algorithm For Lithium Ion Batteries Of Electric Vehicles

Accurate State of Charge(SOC)and State of Power(SOP)of lithium-ion batteries are the keys to electric vehicles stable operation,and also the core issues and technical difficulties of battery management system.In order to full play performance of lithium battery and make the vehicle power battery BMS system work safely and reliably,State of Charge and sustained peak discharge State of Power are used as important indicators to judge battery performance.For the good of accurately obtain the lithium-ion battery model parameters and internal state estimate.this thesis establishes the second-order RC equivalent circuit model,the lithium battery SOC estimation and multi-parameter constrained SOP estimation algorithm based on the double-cubature kalman filter(D-CKF)are designed.On the basis of analyzing the structure and working principle of lithium-ion batteries,the dynamic capacity tests,open-circuit voltage tests,rapid pulse discharge conditions and EPA urban dynamic conditions(UDDS)tests were carried out,dynamic capacity modeling and SOC-OCV curve calibration are completed.The second-order RC equivalent circuit model is established,the artificial bee colony algorithm is used to model parameters initial optimal solution calibration,which provides reference for the initialization of model parameter identification;The double-cubature kalman filter algorithm is used to concurrence lithium battery model parameter identification and SOC estimation.Design a lithium batteries multi-parameter constrained SOP estimation method based on SOC,which can achieve optimal BMS configuration and prolong battery life;Calculate the peak discharge current based on SOC,terminal voltage and single maximum peak current constraints,according to multi-parameter constraint peak discharge current calculate peak discharge power of different duration.The hardware-in-the-loop simulation system and lithium battery test system are combined,under rapid pulse discharge conditions and UDDS conditions,the accuracy of SOC estimation algorithm and SOP estimation method under multi-parameter constraints is verified by rapid control prototype(RCP).The test results show that whether is constant current discharge or complex alternating current discharge,the D-CKF algorithm is used to identify lithium battery model parameters,which can improve model terminal voltage prediction accuracy.Under rapid pulse discharge conditions and UDDS conditions,the model parameter identification based on D-CKF algorithm terminal voltage average errors separately for 0.0067 and 0.0066.The D-CKF algorithm for lithium battery SOC estimation can quickly correct initial error and has strong tracking convergence ability.Under rapid pulse discharge conditions and UDDS conditions,the average error of SOC estimation based on the D-CKF algorithm remains at about 0.01,compared with the traditional CKF algorithm separately for decreases 34.7%and 41.9%.The designed lithium battery multi-parameter constraint SOP estimation can improve the battery utilization rate and ensure system security within the defined continuous discharge time.Under rapid pulse discharge conditions and UDDS conditions,the average error of the battery SOP estimation is about 4W,the peak current constraints in different SOC intervals are different,if only single constraint is used to peak SOP estimation,peak current discharge will be too large at a certain interval,which battery service life will shorten.