Research On Modeling And State Estimation Of Vehicles LiFePO₄ Batteries

The power battery system is one of core components for electric vehicles.The battery management system plays an irreplaceable role in connecting the driver between the battery packs,battery packs between vehicle management system.To safely and rational use energy in battery packs,a good power battery management system is needed to be developed.Based on establishment of a reasonable battery mechanism model,the characteristics of power batteries can be effectively understanded,and the accuracy of the state estimations and practicality can be improved.Power battery state estimation is the core technology of battery management systemsas the basis of energy distribution strategy and other algorithms.The state estimation of the power battery mainly includes State of Charge?SOC?Estimation and State of Health?SOH?Estimation.Reasonable and accurate state estimation can develop a reasonable usage strategy of batteries to take full advantage of the battery energy and extend the power battery usage life.In this dissertation,LiFePO₄ power batteries were used as the research object,the key technologies of power battery system modeling and state estimation were studied.The main research contents and results were as follows:Firstly,according to the different battery materials,the performance indicators of the existing power battery were analyzed,and the mechanism model of the lithium-ion battery rated capacity loss was established by combining the charge and discharge characteristics of the lithium-ion battery material.Combined with the model,the factors such as self-discharge loss,low-temperature loss,and cycle attenuation that cause the rated capacity loss of the power battery were quantitatively analyzed,and the analytical formula for the available energy calculation of the lithium-ion power battery under rated capacity loss was given.At the same time,according to the energy balance circuit and the voltage response circuit,the model structure and parameter identification were analyzed.The equivalent circuit model of the power battery that reflects the rated capacity loss characteristics was given and its parameter identification was studied.In addition,the experimental verification of the equivalent circuit model under different conditions?different temperatures and different charge-discharge rates?showed that the accuracy of the model was high.Secondly,the SOC estimation was studied,and the difficulty of the SOC estimation was analyzed.The internal and external factors influencing the SOC estimation were explored in details.The mathematic basis and the operation process of the standard Particle Filter algorithm were expounded in principle,and then the Particle Filter algorithm based on parameter optimization was proposed for the dynamic estimation of SOC.Based on redesigning the resampling process of Particle Filter algorithm in SOC estimation,the total particle number and effective particle threshold in the SOC estimation process were compared and calculated,and the computational speed of the system was optimized by combining the calculation of the algorithm.At the same time,based on the parameter-optimized particle filter algorithm,the experimental verification of the accuracy of different working conditions was performed.Thirdly,the SOH estimation was carried out.Based on the the SOH estimation of the power battery,the deterioration principle of the battery including the the relationship between SOH and some factors such as rated capacity,ohmic resistance,charge and discharge current,charge and discharge depth were analyzed quantitatively.Based on the existing SOH estimation method,the SOH estimation algorithm combined with gray system theory and Markov chain theory was proposed,which was validated by experiments.Finally,the inconsistency of battery pack was explored.The causes of the inconsistency and the significance of the inconsistency management of the battery pack were analyzed,meanwhile the criteria and management difficulties of the battery inconsistency were discussed.As a result,the evaluation standard of the battery pack equilibrium management system was put forward.It was pointed out that the design of the battery pack equilibrium management system should focus on the time efficiency and energy efficiency.