Study On Life Cycle Balancing Strategy Of Lithium-ion Power Battery Pack

With the rapid development of the global economy,energy consumption is increasing rapidly,while environmental pollution is also becoming more and more serious.Thus,national governments are vigorously promoting the advancement of key technologies for new energy vehicles in order to slow down energy consumption and reduce environmental pollution.Among the current new energy vehicles,the related technologies of lithium-ion power batteries are the most mature.In practical applications,in order to meet the power demand of electric vehicles,many cells need to be connected in series and in parallel to form a battery pack.On the other hand,there are ofteninconsistencies between battery cells due to uncertainties in manufacturing and use.This inconsistency not only affects the performance and longevity of the entire battery pack,but also creates a safety hazard.Therefore,it is especially necessary to implement balancing management for the battery pack.Balancing strategy is one of the important components in balancing management.In the existing literature,there is no balancing strategy that considers minimizing aging rate of battery pack as the target.Aiming at this problem,this paper proposes a model to describe the aging rate of the battery,and uses the established first-order resistive capacitor(RC)equivalent circuit model as the prediction model to design a full life balancing strategy based on model predictive control.The balancing strategy aims to minimize the aging rate of the battery pack.Finally,considering the necessity of balancing maintenance in the future,this subject proposes a balancing maintenance strategy that considers maintenance costs in order to solve the user's choice at which time to perform the maintenance.The main contents of this subject are as follows:Firstly,the battery experiment platform is built and the experimental process including battery cell characteristic test and aging cycle test was designed.Further,each battery cell is described by a RC equivalent circuit model.Based on the recursive least squares algorithm,the model parameters were identified by the obtained experimental data,and the accuracy of the model was further verified.Secondly,based on the aging curve of the battery cells in different SOC cycle intervals,and considering the different Depth-of-Discharge(DOD)of the battery,a battery aging rate model is established.Furthermore,using the first-order RC model as the prediction model and considering the six battery cells in series,the battery pack balancing control strategy that minimizes aging rate of the battery pack is designedbased on the basic principle of model predictive control.At the same time,by comparing the balancing strategy with SOC as the balancing target in the existing literature,the effectiveness of the proposed equalization strategy in mitigating the aging rate of the battery pack is verified under three different operating conditions.Finally,considering the cost of balancing maintenance in practice,a balancing maintenance strategy that minimizes maintenance costs is proposed.Firstly,based on the obtained battery cell aging data,the empirical formula of battery aging is established,and the capacity fade data of the battery pack composed of 96 series batteries is obtained under mixed conditions.Secondly,considering the labor cost and equipment loss cost in maintenance,the objective function of battery pack's balancing maintenance cost is established.Further,in the battery pack aging simulation process,the battery packs were separately balanced at seven different time points.The results show that the proposed balancing strategy can improve the battery capacity recovery degree.Finally,according to the seven capacity recovery data,a function of the cycle time and the capacity increment throughbalancing maintenanceat different time points is fitted.According to this function,the optimal balancing maintenance time point is recommended.