Welcome to Journal of Automotive Safety and Energy,

Journal of Automotive Safety and Energy ›› 2020, Vol. 11 ›› Issue (4): 529-537.DOI: 10.3969/j.issn.1674-8484.2020.04.013

• Automotive Energy Efficiency and Environment Protection • Previous Articles     Next Articles

Fault diagnosis algorithm of diesel engine cooling system based on physical model and support vector machine

ZHU Guanhong(), SONG Kang, XIE Hui*(), CHEN Tao, QIAN Zhenhuan   

  1. State Key Laboratory of Combustion of Internal Combustion Engines, Tianjin University, Tianjin 30072, China
  • Received:2020-07-09 Online:2020-12-30 Published:2021-01-04
  • Contact: XIE Hui E-mail:zhuguanhong@tju.edu.cn;xiehui@tju.edu.cn

Abstract:

An intelligent fault diagnosis algorithm was developed by using synchronous operating physical model and small sample data-driven to effectively monitor and accurately diagnose the faults of the cooling system of diesel engine with strong coupling, large time scale and few variables to be monitored. A simplified physical model that based on the physical principle of cooling system was built in the algorithm. The support vector machine (SVM) was used to classify the fault information based on the residual of actual water temperature of the engine and the predicted water temperature of the synchronous operating model to identify the cause of the fault. The algorithm was tested on a precisely calibrated GT-Power diesel engine model and a real bus with fault. The results show that the identification accuracy of the algorithm is above 97%, and the diagnosis time is within 45 s after fault occurred; the algorithm has good monitoring ability and accurate identification potential for cooling system faults.

Key words: diesel engine, cooling system, fault diagnosis, physical model, support vector machine (SVM)

CLC Number: