State Of Health Diagnosis And Lifetime Prediction Method Of LiCoO₂/MCMB Lithium Ion Batteries

Effective and reasonable models of life prediction and state of health diagnosis are essential to the evaluation of lithium-ion battery?LIB?life and health state,and are the key technologies to ensure the LIB work efficiently and reliably.In this paper,life prediction methods and state of health diagnosis methods of LiCoO₂/MCMB LIB are investigated.Multiple models have been developed,including simulation model for battery degradation mode diagnosis,multi factor life prediction model with wide applicability,life prediction model to avoid misjudgment,dynamic equivalent circuit model for state of health diagnosis and efficient real-time state of health diagnosis model for LIBs.Degradation mode of LiCoO₂/MCMB LIBs has been investigated.The degradation mode of cathode includes the capacity loss caused by state of charge?SOC?offset,the cathode polarization,structure degradation of cathode material.It has been demonstrated that the cathode SOC offset is the primary reason for the cathode degradation at any number of cycles.The degradation mode of anode includes the capacity loss caused by SOC offset,the anode polarization,anode structure degradation and interfacial blocking layer?IBL?effect.The main capacity degradation of anode is attributed to the IBL on the anode surface that impedes the intercalation and de-intercalation of lithium ions.Since the capacity of full battery is limited by the cathode during aging,the cathode SOC offset is the most important reason for the full battery capacity loss.The capacity of aged LIBs can be recovered to a relative high level after adding the electrolyte,rather than the solvent.This recovery is attributed to the relief of cathode SOC offset and the dissolution of anode IBL.Based on the degradation mode of the battery,the diagnosis model of the battery degradation has been developed,and the charge discharge curve of the battery is simulated.The simulation results are in good agreement with the experimental results,and the accuracy is higher than 95%.The degradation mode diagnosis model based on battery degradation mode can extend the life and improve the electrochemical performance of LIB,which can provide guidance for the development of life prediction model and state of health diagnosis model.Systematic orthogonal experiments have been carried out to extract the key factor of capacity loss for LiCoO₂/MCMB LIBs.A general multi-factor model has been developed based the main degradation mode of battery.The physicochemical significance of the life prediction model is interpreted by electrochemical analysis and the life prediction of the LIB can be achieved.The accuracy of life prediction for 4000 cycles based on the 1500 cycle data is higher than 95%.Current prediction methods of end-of-life?EOL?by extrapolating the early degradation behavior often result in significant errors.It indicates that open circuit voltage?OCV?is an effective criterion for the judgment of battery EOL.A new EOL threshold prediction model with highly improved accuracy was developed based on the OCV drifts and their evolution mechanism,which can effectively avoid the misjudgment of EOL threshold?the accuracy of the model is as high as 95%?.Electrochemical impedance spectroscopy?EIS?at different SOC and EIS at same SOC after different cycle numbers of LIBs are investigated.Three-electrode LIBs have been designed for EIS investigation of individual electrode,which implies both the cathode and anode contribute to the increase of LIBs impedance at any SOC and cycling stage.Interestingly,inductive loop phenomenon is observed in anode EIS.Dynamic and novel equivalent circuits?ECs?are constructed firstly based on EIS changes along with aging and anode inductive loop for SOH model parameters identification.A modified equivalent circuit model?ECM?with high fidelity as validated by experimental results for battery SOH estimation is developed based on dynamic ECs and OCV offset.The accuracy of the model is higher than 95%.Impedance and OCV parameter identification is the key technology for SOH diagnosis of LIB in an ECM.A new real-time and nondestructive method is developed to identify dynamic impedance parameter for SOH diagnosis ECM?SDEM?of LIB.This method can identify ohmic impedance and charge transfer impedance from internal impedance and realize the transformation of Warburg diffusion impedance from frequency domain to time domain.Fast determination method of OCV was proposed based on the short-time and low current pulse to realize real-time measurement and identification of the OCV.Dynamic update of the all parameters is conducted based on least squares method?LSM?.SDEM with new developed impedance and OCV parameter identification method is validated with high accuracy.The accuracy of the model is higher than 95%.