| With the wide use of power batteries in new energy vehicles,many problems are eager to solve,such as battery failure diagnosis and retired battery evaluation,and so on.Evaluating the State of Health(SOH)has become a significant topic in the power battery field.This paper studies the battery SOH evaluation algorithm from the two aspects of battery charging and discharging by using the data set containing the driving data of electric vehicles and Lithium-ion battery charge-discharge data.Based on the research results,a battery SOH evaluation method is proposed,suitable for electric vehicle driving data.In addition,a battery health evaluation system integrating the above evaluation algorithm is designed and developed.The main contents of this paper are as follows:Firstly,in order to avoid the inaccurate evaluation results caused by the incomplete charge and discharge process in the data set,a capacitance estimation method based on a piecewise linear regression model is proposed in this paper.Based on the statistical analysis and experiment of the data set,this method improves the existing capacitance calculation method.It uses the fragment data of battery charging to model and restores the complete charging process of the battery through the model to estimate the capacity of the battery.Secondly,to comprehensively evaluate the battery health,this paper abstracts an index MPs to measure the battery discharge performance from the actual working condition of the battery.Based on MPS,a method is presented to evaluate battery discharge performance.On the basis of the analysis of Lithium-ion battery discharge data during driving,it is confirmed that the index MPS is related to battery health and can be used to evaluate battery health.Considering the characteristics of fragmentation in the discharge process during the driving of the real vehicle and the uneven electricity in different SOC sections,a weighted average MPS discharge performance evaluation method between zones is proposed.Experiments show that the method is effective and accurate.Finally,the evaluation indexes extracted by the two methods are summarized into an evaluation framework to support the application and expansion of the battery health evaluation.Combined with the expert model,a multi-angle comprehensive health evaluation is given for the battery.Moreover,an evaluation system for power battery health integrating with the evaluation framework is designed and developed,which solves the problem that the traditional evaluation methods are difficult in the practical application.The system can evaluate the health of batteries for users,regularly monitor the health of batteries managed in the system,and support users to customize personalized health evaluation templates. |
