Analysis of vertical strip wound fault-tolerant permanent magnet synchronous machines

This paper investigates the behavior of a vector- controlled, fault-tolerant, permanent magnet motor drive system adopting a vertically placed strip winding (VSW) which can limit inter-turn short-circuit (SC) fault current to its rated value regardless of the position in the slot containing the shorted turns. The drives’ dynamic behavior is simulated using a per-phase equivalent circuit model with the winding inductances and resistances analytical calculated based on the machine geometry and fault location. A simplified thermal model is also grafted into the system model to effectively simulate the dynamic behavior of the machine during healthy, inter-turn SC fault and post-fault controlled scenarios. The SC fault current limiting capability, the additional losses and thermal behavior of the winding are studied and compared with conventional winding adopting round conductors winding (RCW). The proposed winding design is verified with Finite Element (FE) analysis and then validated experimentally. Results show that the VSW inherently limits the SC current, reduces its dependence on the position of the fault within the slot but results in an increase in AC losses

Fault detection of electric vehicle motor based on flux performance using FEM

This paper presents the early faults detection in electric vehicle motor based on flux performance examination in defective electrical machine using finite element methods (FEM). Depend on time step, the proposed technique has been designed and examine to produce efficient method under high accuracy and short time to detect the faults in Electric Vehicle motors. To decrease the probability and time of electric motor faults, the early detection of these faults will give enough time to prevent many problems during the motion. The different waveforms timing of motor torque in every situation associated with the waveforms of stator current provide spreading in the proposed method. The results show fast fault detections and a Novel technology was established to extort the fault of induction motor

Detection and classification of turn fault and high resistance connection fault in permanent magnet machines based on zero sequence voltage

Health monitoring and fault detection are becoming more and more important in electrical machine systems due to the increasing demand for reliability. Winding turn fault is a common fault in permanent magnet machines which can cause severe damages and requires prompt detection and mitigation. High resistance connection (HRC) fault which result in phase asymmetry may also occur but does not require immediate shutdown. Thus, apart from the fault detection, the classification between the two faults is also required. In this paper, a new technique for detecting and classifying turn fault and HRC fault by utilizing both the high and low frequency components of the zero sequence voltage is proposed. The dependence on the operating conditions is minimized with the proposed fault indicators. The effectiveness of fault detection and classification has been verified by extensive experimental tests on a triple redundant fault tolerant permanent magnet assisted synchronous reluctance machine (PMA SynRM). The robustness of the turn fault detection in transient states and under no load conditions has also been demonstrated

Breakdown Resistance Analysis of Traction Motor Winding Insulation under Thermal Ageing

Stator inter-turn faults are among the most important electric motor failures as they progress fast and lead to catastrophic motor breakdowns. Inter-turn faults are caused due to the windings’ insulation degradation. The main stress which deteriorates the insulation is the thermal one. Proper understanding of how this stress influences the electrical properties of insulation over time may lead to reliable prognosis and estimation of the motor’s remaining useful life. In transport applications where reliability and safety come first it is a critical issue. In this paper, extensive experimental testing and statistical analysis of thin film insulation for traction motor windings has been performed under fixed thermal stress. The results indicate that for high thermal stress the electrical properties of the insulation material present a non-monotonic behavior thus proving the well-known and established Arrhenius law inadequate for modelling this type of problems and estimating the remaining useful life of thin film insulation materials

Impact of PWM Voltage Waveforms in High-Speed Drives: A Survey on High-Frequency Motor Models and Partial Discharge Phenomenon

The insulation system’s dielectric of the electric motor is very often subjected to severe electrical stress generated by the high dv/dt seen at the machine’s terminals. The electrical stress and high reflected wave transient overvoltage are even more evident in case of high-speed machines fed by high-frequency (HF) converters featuring very fast wide-bandgap devices. They are promoting the occurrence of partial discharges and consequently accelerate ageing. As this is serious issue and the main cause of the drive failure, it is important to analyse and characterise the surges at the motor terminals. Several HF models of motors have been proposed in the literature for this purpose. This article presents a survey on HF motor models, which is crucial in understanding and studying the most critical parameter identification and overvoltage mitigation techniques. Moreover, it offers a comparison of the models’ main features as well as a comparison with the experimental voltage waveform at motor terminals. A general overview of the partial discharge (PD) phenomenon is also provided, as it is favoured by HF operation and together with HF motor modelling provides key insights to the insulation ageing issue. In particular, an analysis of the effects of PWM waveform affecting insulation is given, as well as useful methods for developing strategies for the inspection and maintenance of winding insulation

Advances in the Field of Electrical Machines and Drives

Electrical machines and drives dominate our everyday lives. This is due to their numerous applications in industry, power production, home appliances, and transportation systems such as electric and hybrid electric vehicles, ships, and aircrafts. Their development follows rapid advances in science, engineering, and technology. Researchers around the world are extensively investigating electrical machines and drives because of their reliability, efficiency, performance, and fault-tolerant structure. In particular, there is a focus on the importance of utilizing these new trends in technology for energy saving and reducing greenhouse gas emissions. This Special Issue will provide the platform for researchers to present their recent work on advances in the field of electrical machines and drives, including special machines and their applications; new materials, including the insulation of electrical machines; new trends in diagnostics and condition monitoring; power electronics, control schemes, and algorithms for electrical drives; new topologies; and innovative applications

Characterization of Stator Winding Short-Circuit Faults in Interior Permanent-Magnet Motor-Drive Systems

This thesis contains a comprehensive analysis of experimental data collected from a case-study interior permanent-magnet electric machine experiencing winding short-circuit faults of varying severity. The experimental data collected from the faulted machine is from both motoring operation energized by a PWM sensorless ac drive as well as generating operation driven by the test bed dynamometer with a resistive winding load. For both modes of operation a complete set of three-phase voltage and current signals was recorded and analyzed. The three fault diagnosis techniques applied and compared regarding their ability to diagnose and prognosticate a winding fault in an interior permanent-magnet machine are motor current spectrum analysis (MCSA), negative sequence components analysis utilizing a symmetrical components transformation, and the space-vector pendulous oscillation method. The applicability of these diagnosis techniques to this case-study experimental interior permanent- magnet machine demonstrate that motor current spectrum analysis is inconclusive in diagnosing a winding fault when the machine is operated as a motor, but useful for diagnosing a winding fault when the machine is operated as a generator. Negative sequence components analysis successfully diagnoses the winding fault in both the motor operation and the generator operation cases. Finally, the space-vector pendulous oscillation method results are inconclusive for both the motor operation and the generator operation test cases

Proton exchange membrane fuel cell degradation prediction based on Adaptive Neuro-Fuzzy Inference Systems .

International audienceThis paper studies the prediction of the output voltage reduction caused by degradation during nominal operating condition of a PEM fuel cell stack. It proposes a methodology based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS) which use as input the measures of the fuel cell output voltage during operation. The paper presents the architecture of the ANFIS and studies the selection of its parameters. As the output voltage cannot be represented as a periodical signal, the paper proposes to predict its temporal variation which is then used to construct the prediction of the output voltage. The paper also proposes to split this signal in two components: normal operation and external perturbations. The second component cannot be predicted and then it is not used to train the ANFIS. The performance of the prediction is evaluated on the output voltage of two fuel cells during a long term operation (1000 hours). Validation results suggest that the proposed technique is well adapted to predict degradation in fuel cell systems