Study Of Ni-MH Battery Modeling And SOC Dynamic Estimation In Full HEV

With the continuous improvement of environmental protection and energy saving requirements of automobiles,the Full HEV are becoming more and more popular because of the good performance of both energy-saving effect and driving experience.Full HEV is mainly equipped with Ni-MH battery,and the battery management system?BMS?is one of the key components and has an important impact in the performance of vehicle and battery.The estimation of state of charge?SOC?is one of the most significant function in BMS,because only when the SOC of battery is clear and accurate,the settings of charging and discharging of Full HEV can be accurate,and the space of battery are not wasted.In particular,the charging and discharging state of the Full HEV is uncertain and changes frequently which put forward higher requirements for the prediction accuracy of SOC.In addition,the Ni-MH has significant polarization effect which also makes it difficult to estimate SOC.Therefore,based on the 863 project and the project of Shanghai Municipal Commission of Economy and Informatization,this paper focuses on the establishment of model,parameter dynamic identification and SOC dynamic estimation of Ni-MH battery model in Full HEV.The characteristics of charge-discharge and Full HEV operation condition are analyzed in this paper.The equivalent circuit model,Ah integration algorithm,set membership filter?SMF?algorithm,extended EMF algorithm,and weighted factor method,are combined to achieve the dynamic identification of battery model and the dynamic SOC estimation.The main research contents and innovation are as following:?1?On the basis of the research on the condition of Full HEV and the charge-discharge characteristics of Ni-MH battery,a scalable equivalent RC model with 2^nd-order is adopted.And the model proved to be precision enough by applying static parameters.?2?By using the basic principle of the model and the cumulative change concept,the model parameters are updated with state and time,and realize dynamic parameter identification with UD decomposition.The method is aligned with the Full HEV condition more than static parameter identification.?3?Based on the experimental study of Ni-MH battery and the established model,the scopes of various common SOC estimation algorithms are compared.With combining the EMF method,Ah integration method and SMF method,the applicable weighted scope and engineering experience,the SOC estimation method is proposed,where the Full HEV operation condition is considered.?4?Based on the static method and emptying method,the problem thatthe true SOC is difficult to obtain in Full HEV Ni-MH battery has been solved,and a specific test is successfully designed to verify the parameter identification and SOC estimation algorithm.To test the accuracy of algorithm,the point inspection is applied.To test the stability,the random Full HEV condition is applied.The experimental results show that the error of 2^nd RC model identification is less than 2%and the algorithm error is less than 3%.In summary,the parameter identification and SOC estimation method in this paper are applicable to the Ni-MH battery in Full HEV.The research obtained an accurate weighted SOC estimation method,it is benefit for the extension of the SOC estimation model,and it also establishes a precision test structure for the dynamic SOC algorithm of Full HEV.