International Journal of Automotive Technology

, Volume 20, Issue 1, pp 99–108 | Cite as

Misfire Fault Diagnosis of Range Extender Based on Harmonic Analysis

  • Xiaowei Xu
  • Zhenxing Liu
  • Jiangdong Wu
  • Jiaming Xing
  • Xiaoqing WangEmail author


For an Extended-Range Electric Vehicle (E-REV), the misfire failure of the range extender can result in working condition deterioration, mileage decrease, vibration and noise increase, and other adverse consequences. The relationship of the shaft instantaneous angular speed (IAS) signal and the misfire fault of the range extender was studied by harmonic analysis. Based on the theory of shafting torsional vibration, the range extender dynamics model was developed to analyze the changing trend of the shaft IAS theoretically. Then, the shaft IAS signal under different working conditions was simulated using a developed range extender rigid-flexible hybrid multi-body dynamics model. It is found that the 0.5-order harmonic phase and the amplitude of range extender IAS can be used as the characteristic parameters in misfire fault diagnosis, which has been verified by experiments on an engine bench.

Key words

Electric vehicles Fault diagnosis Harmonic analysis Power system dynamics 



cylinder number


harmonic frequency


fault degree


magnitude of simple harmonic excitation torques


amplitude of vibration displacement


phase angle between excitation torque and vibration displacement


sum vector of relative amplitudes


firing interval of each cylinder


amplitude of harmonic excitation torque


total work for the excitation torque on the system


phase difference


number of cylinder



extended-range electric vehicles


auxiliary power unit


instantaneous angular velocity


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  1. Azadfar, E., Sreeram, V. and Harries, D. (2015). The investigation of the major factors influencing plug-in electric vehicle driving patterns and charging behaviour. Renewable and Sustainable Energy Reviews, 42, 1065–1076.CrossRefGoogle Scholar
  2. Badr, W. S., Fanni, M., Abdel-Rahman, A. K. and Rasoul, S. A. (2016). Dynamic simulation and optimization of rhombic drive stirling engine using mac adams software. Procedia Technology, 22, 754–761.CrossRefGoogle Scholar
  3. Ball, J. K., Bowe, M. J., Stone, C. R. and Mcfadden, P. D. (2000). Torque estimation and misfire detection using block angular acceleration. SAE Paper No. 2000-01-0560.Google Scholar
  4. Bianchi, N., Bolognani, S. and Chalmers, B. J. (2000). Salient-rotor PM synchronous motors for an extended flux-weakening operation range. IEEE Trans. Industry Applications 36, 4, 1118–1125.CrossRefGoogle Scholar
  5. Borghi, M., Mattarelli, E., Muscoloni, J., Rinaldini, C. A., Savioli, T. and Zardin, B. (2017). Design and experimental development of a compact and efficient range extender engine. Applied Energy, 202, 507–526.CrossRefGoogle Scholar
  6. Chambon, P., Curran, S., Huff, S., Love, L., Post, B., Wagner, R., Jackson, R. and Green, J. (2017). Development of a range-extended electric vehicle powertrain for an integrated energy systems research printed utility vehicle. Applied Energy, 191, 99–110.CrossRefGoogle Scholar
  7. Chen-Yang, A. O., Huo, B. Q., Yao, Z. Y., Chen, X. Z. and Zhang, J. J. (2016). Research on diesel engine drive gear fault mechanism and monitoring methods based on dynamic simulation. Ship Engineering 38, 6, 14–16.Google Scholar
  8. Chen, B., Wu, Y. and Tsai, H. (2014). Design and analysis of power management strategy for range extended electric vehicle using dynamic programming. Applied Energy, 113, 1764–1774.CrossRefGoogle Scholar
  9. Chen, J. and Bond Randall, R. (2015). Improved automated diagnosis of misfire in internal combustion engines based on simulation models. Mechanical Systems and Signal Processing, 64-65, 58–83.CrossRefGoogle Scholar
  10. Devasenapati, S. B., Sugumaran, V. and Ramachandran, K. I. (2010). Misfire identification in a four-stroke fourcylinder petrol engine using decision tree. Expert Systems with Applications 37, 3, 2150–2160.CrossRefGoogle Scholar
  11. Du Canyi, D. K. and Zhijian, Y. (2012). Feature extraction of engine misfire fault based on finite element and multibody dynamics simulation. J. Vibration and Shock 31, 9, 18–23.Google Scholar
  12. Du, J. and Ouyang, D. (2017). Progress of Chinese electric vehicles industrialization in 2015: A review. Applied Energy, 188, 529–546.CrossRefGoogle Scholar
  13. Eriksson, D., Eriksson, L., Frisk, E. and Krysander, M. (2013). Flywheel angular velocity model for misfire and driveline disturbance simulation. IFAC Proc. 46, 21, 570–575.CrossRefGoogle Scholar
  14. Franke, T. and Krems, J. F. (2013). What drives range preferences in electric vehicle users?. Transport Policy, 30, 56–62.CrossRefGoogle Scholar
  15. Hooshang, M., Askari Moghadam, R. and AlizadehNia, S. (2016). Dynamic response simulation and experiment for gamma-type Stirling engine. Renewable Energy, 86, 192–205.CrossRefGoogle Scholar
  16. Hu, C. Q., Li, A. H. and Zhao, X. Y. (2011). Multivariate statistical analysis strategy for multiple misfire detection in internal combustion engines. Mechanical Systems and Signal Processing 25, 2, 694–703.CrossRefGoogle Scholar
  17. Hu, Y., Zhou, R. P. and Yang, J. G. (2009). Research on the fault diagnosis technology of diesel engine based on the instantaneous speed. Key Engineering Materials, 413-414, 547–552.CrossRefGoogle Scholar
  18. Janssens, K. and Britte, L. (2012). Comparison of Torsional Vibration Measurement Techniques. Advances in Condition Monitoring of Machinery in Non-Stationary Operations. Springer-Verlag Berlin Heielberg. Heidelberg, Germany.Google Scholar
  19. Jia, J.-D., Tong-Min, G. E., Yang, W. C., Zhang, L. L., Zhou, B. and Jiang, W. (2013). Research on diagnosis of diesel engine misfire fault based on non-stationary cycle feature enhancement. Chinese Internal Combustion Engine Engineering 34, 1, 67–70.Google Scholar
  20. Li, J., Wang, Y., Chen, J. and Zhang, X. (2017). Study on energy management strategy and dynamic modeling for auxiliary power units in range-extended electric vehicles. Applied Energy, 194, 363–375.CrossRefGoogle Scholar
  21. Li, Z., Guo, Z., Hu, C. and Li, A. (2017). On-line indicated torque estimation for internal combustion engines using discrete observer. Computers and Electrical Engineering, 60, 100–115.CrossRefGoogle Scholar
  22. Liu, B., Zhao, C., Zhang, F., Cui, T. and Su, J. (2013). Misfire detection of a turbocharged diesel engine by using artificial neural networks. Applied Thermal Engineering 55, 1–2, 26–32.CrossRefGoogle Scholar
  23. Ma, J., Jiang, Z.-N. and Gao, J.-J. (2012). Diesel engine fault diagnosis method based on instantaneous angular speed fluctuation ratio. J. Vibration and Shock 31, 13, 119–124.Google Scholar
  24. Puchalski, A. (2015). A technique for the vibration signal analysis in vehicle diagnostics. Mechanical Systems and Signal Processing, 56–57, 173–180.CrossRefGoogle Scholar
  25. Qian, S. C., Yang, X., Xiao, X. Y. and Wang, X. Q. (2013). Application of gammatone filter bank to vibration characteristics analysis of engine cylinder head. Chinese Internal Combustion Engine Engineering 34, 6, 36–42.Google Scholar
  26. Qu, X., Wang, Q. and Yu, Y. B. (2013). A study on the control strategy for APU in a extended-range EV. Automotive Engineering 35, 9, 763–768.Google Scholar
  27. Rezvani, Z., Jansson, J. and Bodin, J. (2015). Advances in consumer electric vehicle adoption research: A review and research agenda. Transportation Research Part D: Transport and Environment, 34, 122–136.CrossRefGoogle Scholar
  28. Sioshansi, R. and Denholm, P. (2009). Emissions impacts and benefits of plug-In hybrid electric vehicles and vehicle-to-grid services. Environmental Science and Technology 43, 4, 1199–1204.CrossRefGoogle Scholar
  29. Smart, J. and Schey, S. (2012). Battery electric vehicle driving and charging behavior observed early in the EV project. SAE Int. J. Alternative Powertrains 1, 1, 27–33.CrossRefGoogle Scholar
  30. Thor, M., Bo, E., Mckelvey, T. and Andersson, I. (2014). Using combustion net torque for estimation of combustion properties from measurements of crankshaft torque. Control Engineering Practice, 26, 233–244.CrossRefGoogle Scholar
  31. Ulatowski, A. and Bazzi, A. M. (2016). A combinationallogic method for electric vehicle drivetrain fault diagnosis. IEEE Trans. Industry Applications 52, 2, 1796–1807.Google Scholar
  32. Wang, X., Ge, Y., Zhang, C., Tan, J., Hao, L., Liu, J. and Gong, H. (2016). Effects of engine misfire on regulated, unregulated emissions from a methanol-fueled vehicle and its ozone forming potential. Applied Energy, 177, 187–195.CrossRefGoogle Scholar
  33. Wang, X., Xiang, Y., Guo, Z., Xia, X., Shi, Y., Xue, P. and Wu, S. (2014). Research on experimental measurement of acoustic resistance and major accuracy influencing factors analysis. J. Mechanical Science and Technology 28, 4, 1219–1227.CrossRefGoogle Scholar
  34. Xie, S. B., Liu, X. B., Wang, J. and Wei, L. (2014). Powertrain match and simulation for extended-range electric sanitation truck. J. Highway and Transportation Research and Development 31, 9, 145–153.Google Scholar
  35. Xu, X., Wang, H., Zhang, N., Liu, Z. and Wang, X. (2017). Review of the fault mechanism and diagnostic techniques for the range extender hybrid electric vehicle. IEEE Access, 5, 14234–14244.CrossRefGoogle Scholar
  36. Zhao, X., Cheng, Y. and Ji, S. (2017). Combustion parameters identification and correction in diesel engine via vibration acceleration signal. Applied Acoustics, 116, 205–215.CrossRefGoogle Scholar

Copyright information

© The Korean Society of Automotive Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Xiaowei Xu
    • 1
  • Zhenxing Liu
    • 1
  • Jiangdong Wu
    • 1
  • Jiaming Xing
    • 1
  • Xiaoqing Wang
    • 2
    Email author
  1. 1.School of Automobile and Traffic EngineeringWuhan University of Science and TechnologyWuhanChina
  2. 2.Department of Applied EngineeringJacksonville State UniversityJacksonvilleUSA

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