Research On On-line Identification And SOC Estimation Of Lithium Battery Parameters For Electric Vehicles

Lithium batteries with its energy density,high security and low cost,which is widely used in the field of electric vehicles.Electric vehicle energy storage system charge and discharge management strategy according to the health status of lithium batteries for dynamic planning,otherwise it will cause security risks.Therefore,accurate estimation of lithium battery charge status,online identification of lithium battery equivalent circuit model parameters,help to help develop energy storage system management strategy to ensure its use of security and reliability.In this paper,the nickel-cobalt-manganese three-element lithium battery,which is widely used in household electric energy storage system,is used to study the charge and discharge characteristics of lithium battery and its degradation,the equivalent circuit model construction and its parameter identification and on-line estimation method of charge state.Firstly,the electrochemical mechanism of the nickel-manganese-manganese three-element lithium battery was analyzed,and the typical charging and discharging circuit and strategy were given.The characteristics of the current and current characteristics of the charge and discharge process and the degradation trend were analyzed.Charge and discharge cycle and aging test method and test program.The relationship between voltammetric characteristics,internal resistance characteristics,open circuit voltage and capacity characteristics,open circuit voltage and charge state of lithium battery was studied.Secondly,the time-domain volt-ampere characteristic equation of the typical equivalent circuit model of lithium battery is established,and the model is selected from the perspective of structural complexity,voltammetric performance and application range.The model is selected for the identification of on-line parameters and on-line parameter identification.The calculation method of the equivalent circuit model under the HPPC test condition is carried out to identify the internal resistance,internal resistance and polarization capacitance of the equivalent circuit model,and model validation under different working conditions.Then,under the DST dynamic test condition,the polarization resistance,polarization capacitance,ohmic resistance and open circuit voltage of the second-order Theveninequivalent circuit model of lithium battery are identified and verified by the forgetting least squares method of forgetting factor Identify the accuracy of the results.Finally,BP neural network is used to estimate the state of charge of lithium battery.According to the experiment and simulation process,the optimal network structure,hidden layer neuron number and training algorithm are selected,and BP neural network model is constructed on simulation platform.The training set continually optimizes the training and evaluates the charge state of the test sample to verify the accuracy of the estimation results.