A Real-time Fault Detection Method for the Air-fuel Ratio of Gasoline Engine Based on the Trend and Correlation Analysis of Dataflow

Publication Type:
Journal Article
Qiche Gongcheng/Automotive Engineering, 2017, 39 (4)
Issue Date:
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© 2017, Society of Automotive Engineers of China. All right reserved. According to the features of air fuel ratio fault in gasoline engine, a real-time fault detection method based on the abnormality of data flow trend and correlation analysis is proposed in this paper. For enhancing accuracy and operation efficiency, modifications are made based on the algorithm of cumulative sum of error, with rapid estimation on the correlation between data flows, to enable the whole system operates on on-board platform relatively sensitive to resources. The results of test on the engine of Chang-an vehicle show that compared with traditional fault detection method based on support vector machine and neural network, the method proposed can obtain better results of fault detection with lower resource consumption.
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