Research And Application Of Intelligent Battery Fault Diagnosis System

With the increasing intensification of global environmental pollution and tight resources supply, governments of all countries put more and more attention to the exploration and utilization of new energy sources.Lately, Electric Bicycle, Hybrid Electric Vehicle(HEV), Electric Vehicle(EV),Fuel Cell Vehicles(FCVS) and etc, has become a hot topic of concern in the market. Not a few of study and results indicate that lots of countries support for onboard battery EV experiment in the form of government, and many companies also independently conduct research work. Currently, lithium battery has been widely used not only in portable devices, such as cell phones, laptops, but also in high-power vehicle, such as E-bike and EV.As a research field, automotive batteries are in full swing.As the development trend of automobile industry, EV era is ahead. Electric vehicle is a complicated system with a variety of electromechanical equipments, such as driven motor, speed controller, power battery and car charger. The actual phenomenon of its malfunction is diverse, and many complex fault scenarios are often fuzzy, random, compositional and etc. As the power supplement of EV,auto batteries is the main location that failure occurs, and it is also the focus of fault diagnosis.Therefore, as the core-block of battery protection and management, the intelligent battery fault diagnosis system is in the tight combination with on-board battery of EV.Starting with the present situation and progress of research at home and abroad on EV battery management system and fault diagnosis system, the principle of working, charging and discharging characteristics, and the main problems encountered in practical applications of the EV battery are analyzed and studied.This article analyzes and investigates the features and the content of battery failure in detail based on a great deal data, and then presents a prototype of fault diagnosis system based on B/S combined with the existing expert system theory and method, which can analyze and deal with the relevant data about battery status obtained by the web server, and then diagnose the breakdown with computer. According to the diagnostic results, corresponding control commands and processing information are transferred to the related modules, battery health status and maintenance of information are given, the experimental results show that it meet the operation requirements of EV battery fault diagnosis.Most important among these is data analysis and diagnosis reasoning mechanism, especially the knowledge acquisition and question classification. Application of the system verified the feasibility and effectiveness of the method.