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    • Research on Fault Diagnosis of Diesel Electric Hybrid Based on Support Vector Machine
    DOI：10.13949/j.cnki.nrjgc.2022.01.012
    Key Words:diesel electric hybrid system  support vector machine  fault diagnosis  real-time simulation
    Author NameAffiliationE-mail
    HAN Yaohui* School of Mechanical Engineering，Beijing Institute of Technology， Beijing 100081， China hanyaohui2019@163.com 
    LIU Bolan* School of Mechanical Engineering，Beijing Institute of Technology， Beijing 100081， China liubolan@bit.edu.cn 
    WANG Wentai School of Mechanical Engineering，Beijing Institute of Technology， Beijing 100081， China  
    LIU Fanshuo School of Mechanical Engineering，Beijing Institute of Technology， Beijing 100081， China  
    ZHANG Junwei School of Mechanical Engineering，Beijing Institute of Technology， Beijing 100081， China  
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    Abstract:The system level fault diagnosis of diesel electric hybrid power was studied. A real-time vehicle model was built by using the GT-Suite software to meet the accuracy requirements， and the diagnosis framework of diesel electric hybrid system based on support vector machine（SVM） was constructed. The one-verse-one（OVO） method was used to construct multiple classifiers， and the accuracy of fault recognition was 98%. The real-time simulation platform of diesel electric hybrid system fault diagnosis was constructed， and the fault diagnosis real-time simulation of diesel electric hybrid system based on SVM was carried out. Results show that the diagnosis algorithm based on support vector machine can effectively realize the multi fault concurrent mode diagnosis of hybrid system in real-time environment.
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