Industrial Lithium Battery Degradation Model Research And Application Based On Stochastic Process

Lithium ion batteries have been widely used in the field of handset,because of high energy density,long cycle life,and low self discharge rate.Although the lithium battery has been widely used in the new energy car,aerospace and other fields,the reliability and safety of lithium ion battery has become the key problem in industrial applications due to the lithium battery safety accident.Study on lithium battery RUL prediction occupy a larger proportion in PHM International Conference,the degradation process of lithium batteries become the key parts of PHM Technology.In this paper,the battery capacity is chosen as the characteristic quantity to study the remaining service life of the lithium battery.Analysis of the dataset of lithium battery in NASA database,summary of domestic and foreign research results about the dataset,analysis of the lithium battery degradation characteristic variables,applying the data driven viewpoint to study the statistical characteristics of lithium battery,summarize the research methods for the data.Study on ARIMA algorithm model,introduces the basic theory and application method of ARIMA model,and establishes the ARIMA prediction model based on the capacity degradation of lithium battery.Study on stochastic process model.The aging of the lithium battery is caused by many reasons,such as aging of the positive and negative materials,and the membrane and the electrolyte.On the micro scale this is the result of a large number of particle interactions,On the macro scale,it is a dynamic nonlinear degradation process.Based on the central limit theorem,a stochastic degradation process model is established.The residual life prediction model of lithium battery is established by using the stochastic process model with drift Wiener process.Finally,design and implement the industrial lithium battery PHM system by using LabVIEW and MATLAB mixed programming technology.The performance of the model is tested,indicating that the ARIMA model has a high accuracy and strong feasibility in the short term,but it is not suitable for long-term prediction and can’t give the confidence value.the drift Wiener process can not only predict the remaining useful life,but also describe the confidence level of the predicted value.