International Journal of Automotive Engineering
Online ISSN : 2185-0992
Print ISSN : 2185-0984
ISSN-L : 2185-0992
Volume 11, Issue 1
Displaying 1-2 of 2 articles from this issue
Technical Paper
Research Paper
  • Dinh Anh Tuan Tran, Huong Nguyen Thi Cam, Quoc Minh Phan
    2020 Volume 11 Issue 1 Pages 9-13
    Published: 2020
    Released on J-STAGE: February 07, 2020
    Accurate and incipient fault detection of air conditioning systems is highly demanded in a car to prevent energy waste and high maintenance cost. However, most fault detection techniques require experiences of drivers which are usually unavailable. In this study, a novel hybrid method is proposed to detect faults for AC systems in car. Two typical faults in AC system are adopted to investigate. An AC fault detection and diagnosis framework is introduced by combining the RBFNN model and the EWMA. The results show that the proposing algorithm detects typical air conditioning faults in a car with high accuracy.
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