Fault-tolerance and noise and vibration aspects of electrical drives
: Application to wind turbines and electrical vehicle traction

  • Yves Mollet ((PhD) Student)

Student thesis: Doctoral Thesis


The awareness of the human responsibility in global warming has led to various private and public initiatives to reduce the emission of greenhouse gases, up to international level. In this context the development of renewable technologies in two sectors having an important ecological footprint, i.e. production of electricity and transportation, is targeted.In the firstly mentioned sector, the progression of wind energy is at present the most rapid among all renewable energies. But wind turbines still suffer from a global lack of reliability and accessibility compared to classical power plants, leading to potentially important production losses and repair costs. The first part of the present work focuses on the improvement of the electrical chain reliability by the combination of an estimator and a fault-detection algorithm to achieve sensor-fault tolerance, taking benefit from the already available measurement redundancies on doubly-fed-induction-machine (DFIG) drives.Estimators and sensor-fault detection and isolation (FDI) in DFIGs have been the object of many research papers. However, most of them only consider one unique type of measurement and only a few works consider magnetic saturation. A new combination of a closed-loop observer with a cumulative-sum-based FDI technique, considering magnetic saturation and using limited computational resources is proposed here to estimate electromagnetic torque, rotor currents and position for sensor-fault detection and tolerance. This algorithm is then validated in steady state and in case of moderate transients, unbalanced conditions and misestimation of DFIG parameters. The estimator can also start on the fly during the start-up process of the generator.In the transportation sector, new hybrid and full-electric vehicles start to be visible on the roads, but still need important technological improvements in terms of autonomy, performances, but also produced noise and vibrations. The objectives of the second part of this doctoral thesis are related to this last challenge and consist of the experimental investigation of noise, vibration and harshness (NVH) aspects of an 8/6 switched-reluctance machine (SRM) designed for an electrical vehicle (EV).The NVH issues of SRMs, limiting their usage in automotive and other domains, have been the subject of various papers. However, most of them focus on modal analysis or detailed phenomena, while a global evaluation of NVH aspects of SRMs in normal working conditions is rarely made, as well as the use of reproducible sound metrics. A global and relatively fast experimental method to assess the evolution of noise and vibration is proposed. Tests are performed in transient regime, using continuously varying working conditions when possible, for the excitation of a large band of frequencies. The resulting current, radial vibration and acoustic noise are presented as spectrograms for an easy distinction of affected and unaffected frequencies and compared with the associated loudness and sharpness.Furthermore, the implementation of a new faster-sampled current-hysteresis controller has allowed to improve the quality of the control and of the acoustic noise by reducing the current-ripple amplitude and the excitation of resonances. The various tests show that the switching frequency has to be high enough to avoid exciting the ovalization mode of the SRM, but not too high to avoid producing a too sharp noise. The ripple amplitude also has to be considered to limit the loudness. Therefore, soft chopping, or a reduced DC-bus voltage at low speeds, has to be preferred with a relative small hysteresis bandwidth. Finally, the case of an open-phase fault has been investigated showing amplified even current orders in the vibration and acoustic-noise plots.
Date of Award6 Nov 2017
Original languageEnglish
Awarding Institution
  • Université libre de Bruxelles
Sponsorsla Région Wallonne & Marie Skłodowska-Curie IAPP
SupervisorJohan Gyselinck (Promotor), Jean-Claude Maun (Jury), Michel Kinnaert (Jury) & Philippe Lataire (Jury)


  • Fault tolerance
  • Fault detection and isolation
  • Sensorless control
  • Wind energy generation
  • Switched-reluctance machine
  • Noise & vibration
  • Spectrogram
  • Doubly-fed induction generator
  • Electrical vehicle

Cite this