Capacity Estimation And Consistency Screening Of Retired Batteries Based On IC Curve

The growing attention to energy and environmental issues has made new energy vehicles become a development trend of the future automobile manufacturing industry However,as an important part of new energy vehicles,the performance of the battery will decay with use.When the performance drops to 80%,it will be replaced because it cannot meet the performance requirements of the vehicle.Although the replaced retired batteries no longer meet the performance of the original electric vehicles,after screening,they can be used in occasions with low battery performance requirements,such as power storage,low-speed sightseeing vehicles,etc.Through the cascaded utilization,the service life of the battery can be prolonged and the value of the battery can be fully utilized,which is of great significance for promoting the sustainable development of the new energy automobile industry.However,how to quickly and accurately identify the performance parameters of retired batteries and re-select the batteries with better consistency is a major obstacle restricting the cascaded utilization of retired batteries,and it is also a difficult problem in the cascaded utilization industry.Aiming at the capacity test and consistency screening effect and efficiency of retired batteries,a set of rapid battery screening models was established by using the incremental capacity curve of retired batteries.The main work and conclusions are as follows:possibility of using the curve under high current to estimate the capacity under low current,and also provides guidance for faster screening in the future.(1)The rate characteristics and aging characteristics of incremental capacity curve of the battery were analyzed.Through the curves under different current rates,it is determined that the characteristics of the curve under 1000 m A current are obvious and the efficiency is high;on this basis,by testing the incremental capacity curve under different cycles of aging,it is found that the curves behave differently under different aging conditions,and the capacity of the battery can be estimated according to the curve changes.(2)A partial curve battery capacity estimation model is proposed.The quantitative relationship between the characteristic parameters of the incremental capacity curve and the capacity is established through the BPNN optimized by AGA,and the battery capacity estimation is realized.Compared with other algorithms,AGA-BPNN shows good performance.The maximum error of estimated capacity is only 2.9776%,and the model determination coefficient also reaches 0.9443.And because the data required by the algorithm is only a part of the battery charging curve,the test time is reduced by 60% to 70% compared with the traditional test method with the same current.The article also confirmed the possibility of using the curve at a large current to estimate the capacity at a small current,which also provided guidance for faster screening in the future.(3)In order to improve the efficiency of battery consistent screening,a battery consistent screening strategy based on incremental capacity curve was proposed.When the batteries with similar curves were divided into the same group,the batteries screened by this method also had good consistency in aging degree and aging mechanism.Moreover,the distance between the points in the cluster and the center of the cluster was significantly reduced by K-means ++ and Romanov criterion,and the average sum of squares in the cluster in the group with the best effect was reduced by 74.65%.(4)In order to improve the efficiency of the consistency screening of the battery,a rapid test method for the incremental capacity curve of parallel discharge and series charge is proposed.In the case of 8 batteries connected in series in this experiment,the incremental capacity curve of 8 batteries can be tested at the same time.This method effectively improves the test efficiency of the curve(8 times),and the structure is simple and easy to implement.