| Ternary lithium-ion batteries are widely used as power batteries for new energy vehicles because of their high specific capacity.The State of Charge(SOC)of the batteries,which serves as the "fuel meter" function of the new energy vehicle,is not only the core indicator in the battery management system,but also an important basis for the vehicle’s range prediction,the charge and discharge protection of the battery.Therefore,it is of great significance to estimate SOC accurately.In this study,a coupling approach based on open-loop voltage was proposed for ternary lithium-ion battery,and a double filter algorithm was designed to estimate both SOC and model parameters,which improved the accuracy of SOC,algorithm convergence performance and robustness.The main work is as follows:(1)According to the reaction principle of ternary lithium-ion batteries,a second-order Thevenin equivalent circuit model was established to describe the external characteristics of the batteries.The mathematical derivation of the model was carried out,and the joint parameters were proposed and defined.The relationship between the model parameters and the battery state was linearized to facilitate the design of the algorithm.The model parameters were identified by Hybrid Pulse Power Characterization(HPPC)and Particle Swarm Optimization algorithm,respectively,and verified by HPPC,Dynamic Stress Test and Federal Urban Driving Schedule.(2)Based on Kalman Filter(KF),Extended Kalman Filter(EKF)and Particle Filter(PF),the PFEKF-KF algorithm combining the advantages of EKF-KF and PF-KF is proposed,and was improved from three aspects: model parameters online identification,improvement of convergence performance and the reduction of computing time.It has been proved that this algorithm not only maintains the same accuracy as PF-KF,but also reduces the computing time to the same level as EKF-KF.(3)A new coupling approach based on open-loop voltage is proposed.The existing two coupling approach based on time scale and estimated voltage cannot evaluate the on-line identification parameter accuracy well.In this study,an open-loop equivalent circuit model is proposed to be added to the double filter algorithm,the model is the same as the battery model in the algorithm,which only takes the measured current as the input,and its output is the open-loop voltage,and the voltage is used to evaluate the accuracy of the on-line identification parameters.Finally,a PFEKF-KF algorithm based on open-loop voltage coupling approach is proposed and designed.(4)The proposed algorithm is verified based on simulation and hardware platform.The measured data of soft package ternary lithium-ion battery as the experimental object and the open-source data of 18650 cylindrical ternary lithium battery from the CALCE group of the University of Maryland were used for simulation respectively.The operating conditions,the initial SOCs of the algorithm,the initial SOCs of the algorithm and the ambient temperatures were taken as variables to verify the algorithm effect,the computing time was also analyzed.Using PFEKF-KF algorithm as the carrier,the coupling approach based on open-loop voltage was compared with the double time scale approach,unilateral and bilateral estimated voltage approach,respectively.The results show that the proposed algorithm maintains the highest SOC estimation accuracy and the strongest robustness without increasing the computational effort.Finally,the algorithm is transplanted to the hardware platform based on TMS320F28335,and the18650 cylindrical ternary lithium battery is taken as the object.The online estimation of SOC and model parameters is realized under two test conditions designed by ourselves.Meanwhile,the results of the algorithm are monitored and recorded online in the upper computer visualization platform.The results show that the error of estimation SOC is always kept within 1%,and the proposed algorithm has high practical value. |
