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Reserch On Fault Diagnosis And Health Management Of Battery Management System For Hybrid Electric Vehicle

Posted on:2016-04-19Degree:MasterType:Thesis
Country:ChinaCandidate:P Y QingFull Text:PDF
GTID:2272330476954843Subject:Vehicle Engineering
Abstract/Summary:PDF Full Text Request
Environmental pollution and energy shortage are the two major challenges facing today’s auto industry. In order to solve these two problems and respond to the national strategy of sustainable development, scientific research units and the major car manufacturers are putting much effort on new energy vehicles like hybrid vehicles. Hybrid vehicles in the process of maintenance and repair are inseparable from the fault diagnosis research. In this paper, in order to conduct fault diagnosis of battery management system for hybrid electric vehicle, faults and fault reasons are studied through the use of fault tree analysis, vehicle modeling and simulation, pattern recognition and other theories.Firstly, based on hybrid car prototype, this paper collected and reorganized common fault features of the battery management system for hybrid electric vehicle(HEV), finished fault tree analysis, drew the fault tree of the battery management system for hybrid electric vehicle(HEV), and set up the connection between fault phenomenon and fault reasons.Secondly, based on fault tree and fault characteristic, using the MATLAB/Simulink software as the simulation platform, this paper established the simulation model of the battery management system, and then simulated different fault conditions of the battery management system of hybrid electric vehicle and analyzed the system’s response.Finally, pattern recognition theories and methods were used to conduct fault diagnosis. Related conditions data generated by the simulation model of the battery management system, and analysis of data characteristics, extracting the signal characteristics of different sensors and pattern recognition of fault feature vector is established. Using artificial neural network technology, designing and establishing the BP neural network and finished the pattern recognition for three kinds of fault patterns, thus achieved fault diagnosis. And the diagnostic function can be applied to actual battery management system of HEV.
Keywords/Search Tags:Hybrid Electric Vehicle, Fault diagnosis, Battery Management System, Health Management, Pattern recognition, BP Artificial neural network
PDF Full Text Request
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