Hongtao Xue This email address is being protected from spambots. You need JavaScript enabled to view it.1, Jiawen Zhou1, Man Wang1, Zhongxing Li1 and Hong Jiang2

1School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, P.R. China
2School of Mechanical Engineering, Jiangsu University, Zhenjiang 212013, P.R. China


Received: April 11, 2018
Accepted: February 21, 2019
Publication Date: June 1, 2019

Download Citation: ||https://doi.org/10.6180/jase.201906_22(2).0012  


In-wheel motor is a power source of distributed drive system for electric vehicles,which has the exclusive advantages in dynamic performance, handling stability and energy saving. In-wheel motor’s working condition is related to vehicle driving safety. Aiming at the common faults of in-wheel motor, a novel method based on rotating speed is presented to monitor fault detection, which is called “order self-separation method (OSSM)” in the paper. Firstly, the signal of rotating speed is processed to extract the speed fault signal which is the abnormal fluctuation components of the rotating speed when a fault occurs. Secondly, the speed fault signal is translated into angle-domain signal from time domain signal. Finally, the orders of the speed fault signal are analyzed to extract the fault features. In the paper, the phase leakage fault of permanent magnet brushless DC motor is taken as an example to verify the effectiveness of the proposed method. And the order characteristics of rotating speed under different leakage degree and working conditions are analyzed. Experimental result shows that the OSSM can effectively identify the leakage faults of in-wheel motor under different conditions.

Keywords: Rotating Speed Monitoring (RSM), Order Self-separation Method (OSSM), Fault Diagnosis, In-wheel Motor (IWM)


  1. [1] Lu, D., M. Ouyang, J. Gu, and J. Li (2012) Torque distribution algorithm for a permanent brushless DC hub motor for four-wheel drive electric vehicles, Journal of Tsinghua University - Science and Technology 2012(4), 451456.
  2. [2] Matej,B.,G.Gorazd, M.Damijan,and Z.Samo(2015) Mechanical failure mode causes of in-wheel motors, Strojniski Vestnik 61(1), 7485.
  3. [3] Sato, M., G. Yamamoto, D. Gunji, T. Imura, and H. Fujimoto (2016) Development of wireless in-wheel motor using magnetic resonance coupling, IEEE Transactions on Power Electronics 31(7), 52705278. doi: 10.1109/TPEL.2015.2481182
  4. [4] Kim, C., A. M. Ashfaq, S. Kim, S. Back, Y. Kim, S. Hwang, and J. Jang (2015) Motion control of a 6wd/ 6ws wheeled platformwith in-wheel motors to improve its maneuverability, International Journal of Control Automation & Systems 13(2), 434442. doi: 10.1007/ s12555-014-0039-y
  5. [5] Hajihosseinlu, A., S. Filizadeh, G. Bistyak, and E. Dirks (2015) Electronic differential design for a vehicle with four independently controlled in-wheel motors, Electric Vehicle Conference, 17.
  6. [6] Tashakori, A., and M. Ektesabi (2013) Fault diagnosis of in-wheel BLDC motor drive for electric vehicle application, IEEE Intelligent Vehicles Symposium Gold Coast, QLD, Australia, 925930. doi: 10.1109/IVS. 2013.6629585
  7. [7] Tian, S., Z. Lan, and W. Xu (2014) Failsafe drive performance of EVs with four in-wheel motors, Journal of Jiangsu University 35(2), 144148.
  8. [8] Akar, M. (2012) Detection of a static eccentricity fault in a closed loop driven induction motor by using the angular domain order tracking analysis method, Mechanical Systems & Signal Processing 34(12), 173-182. doi: 10.1016/j.ymssp.2012.04.003
  9. [9] Hu, W., L. Gao, and L. Fu (2013) Research on motor fault detection method based on optimal order hidden markov model, Chinese Journal of Scientific Instrument 34(3), 524530.
  10. [10] Sapena-Baño, A., M. Pineda-Sanchez, R. PuchePanadero, J. Perez-Cruz, J. Roger-Folch, M. RieraGuasp, and J. Martinez-Roman (2015) Harmonic order tracking analysis: a novel method for fault diagnosis in induction machines, IEEE Transactions on Energy Conversion 30(3), 833841. doi: 10.1109/TEC. 2015.2416973
  11. [11] Yang, W. (2016) Research on the Online Diagnosis for the Winding Turn-to-turn Fault of Permanent Magnet Synchronous Motor, Ph.D. Desertation, Hunan University, Hunan, China.
  12. [12] Xue, H., H. Wang, P. Chen, K. Li, and L. Song (2013) Automatic diagnosis method for structural fault of rotating machinery based on distinctive frequency components and support vector machines under varied operating conditions, Neurocomputing 116,326–335.doi: 10.1016/j.neucom.2012.02.048
  13. [13] Xue, H. T., Z. X. Li, H. Q. Wang, and P. Chen (2014) Intelligent diagnosis method for centrifugal pump systemusing vibration signal and support vector machine, Journal of Shock and Vibration 2014, article ID 407570, 14 pages. doi: 10.1155/2014/407570
  14. [14] Wang, H., Y. Ke, L. Song, G. Tang, and P. Chen (2016) A sparsity-promoted decomposition for compressed fault diagnosis of roller bearings, Sensors 16(9), 1524. doi: 10.3390/s16091524
  15. [15] Xue, H., Z. Li, Y. Li, H. Jiang, and P. Chen (2016) A fuzzy diagnosis of multi-fault state based on information fusion from multiple sensors, Journal of Vibroengineering 18(4), 21352148. doi: 10.21595/jve.2016. 16712
  16. [16] Xue, H., M. Wang, Z. Li, and P. Chen (2017) Sequential fault detection for sealed deep groove ball bearings of in-wheel motor in variable operating conditions, Journal of Vibroengineering 19(8), 59475959. doi: 10.21595/jve.2017.18413
  17. [17] Cui, L. L., J. Wang, and S. C. Lee (2014) Matching pursuit of an adaptive impulse dictionary for bearing fault diagnosis, Journal of Sound and Vibration 333(10), 28402862. doi: 10.1016/j.jsv.2013.12.029
  18. [18] Cui, L., X. Gong, J. Zhang, and H. Wang (2016) Double-dictionary matching pursuitf or fault extent evaluation of rolling bearing based on the Lempel-Ziv complexity, Journal of Sound and Vibration 385, 372388. doi: 10.1016/j.jsv.2016.09.008
  19. [19] Xue, H., M. Wang, Z. Li, and P. Chen (2017) Fault feature extraction based on artificial hydrocarbon network for sealed deep groove ball bearings of in-wheel motor, 8th IEEE Prognostics and System Health Management Conference, Harbin, China. doi: 10.1109/ PHM.2017.8079189
  20. [20] Cui, L. L., J. F. Huang, and F. B. Zhang (2017) Quantitative and localization diagnosis of a defective ball bearing based on vertical-horizontal synchronization signal analysis, IEEE Transactions on Industrial Electronics 64(11), 86958705. doi: 10.1109/TIE.2017. 2698359
  21. [21] Cui, L., J. Huang, H. Zhai, and F. Zhang (2016) Research on the meshing stiffness and vibration response of fault gears under an angle-changing crack based on the universal equation of gear profile, Mechanism and Machine Theory 105, 554567. doi: 10.1016/j. mechmachtheory.2016.07.022
  22. [22] Parvini, Y., and A. Vahidi (2015) Maximizing charging efficiency of lithium-ion and lead-acid batteries using optimal control theory, American Control Conference, Chicago, IL, USA, 317322. doi: 10.1109/ ACC.2015.7170755
  23. [23] Cui, L., Y. Zhang, F. Zhang, J. Zhang, and S. Lee (2016) Vibration response mechanism of faulty outer race rolling element bearings for quantitative analysis, Journal of Sound and Vibration 364, 6776. doi: 10. 1016/j.jsv.2015.10.015
  24. [24] Suneeta, R. Srinivasan, and R. Sagar (2016) Co-simulation of BLDC motor commutation by using MATLAB simulink and xilinx system generator, International Journal of Engineering & Technology 8(2), 899905.
  25. [25] Rajubhai, P. M., and D. Kumar (2015) Modeling and Simulation of Photovoltaic Array with PMDC Motor in MATLAB/SIMULINK, Esrsa Publications.