Stator turn fault detection by 2nd harmonic in instantaneous power for a triple redundant fault-tolerant PM drive

Fast and reliable detection of stator faults is of key importance for fail-safe and fault tolerant machine drives in order to immediately trigger appropriate fault mitigation actions. The paper presents a detailed analytical and experimental analysis of the behavior of a closed loop controlled permanent magnet machine drive under inter-turn fault conditions. It is shown that significant 2nd harmonic components in the dq voltages, currents, instantaneous active power (IAP) and reactive power (IRP) are generated during turn fault conditions. The analyses further show that the increase of the 2nd harmonic in IAP and IRP during fault conditions is comparatively higher than that of voltage and current, making them ideal candidates as turn fault indicators. A turn fault detection technique based on 2nd harmonic in IAP and IRP is implemented and demonstrated for a triple redundant, fault tolerant permanent magnet assisted synchronous reluctance machine (PMA SynRM) drive. The effectiveness of the proposed detection technique over the whole operation region is assessed, demonstrating fast and reliable detection over most of the operating region under both motoring and generating mode

Multiphase electric drives for "More Electric Aircraft" applications

Advances in power electronic and machine control techniques are making the inverter-fed drives an always more attractive solution. Because of the number of inverter legs is arbitrary, also the number of phases results as a further degree of freedom for the machine design. Therefore, the multiphase winding is often a possible solution. Due to the increasing demand for high performance and high power variable speed drives, the research on multiphase machines has experienced a significant growth in the last two decades. Indeed, one of the main advantages of the multiphase technology is the possibility of splitting the power of the system across a higher number of power electronic devices with a reduced rating. A similar result can be obtained by using multi-level converters. However, the redundancy of the phases leads to an increased reliability of the machine and to the introduction of additional degrees of freedom in the current control and the machine design. This work aims to study and analyze the highly reliable and fault tolerant machines. It proposes innovative solutions for multiphase machine design and control to meet the safety-critical requirements in “More-Electric Aircraft” (MEA) and “More Electric Engine” (MEE) in which thermal, pneumatic or hydraulic drives in aerospace applications are replaced with electric ones. Open phase, high resistance and short circuit faults are investigated. Fault tolerant controls and fault detection algorithms are presented. Radial force control techniques and bearingless operation are verified and improved for various working scenarios. Fault tolerant designs of multiphase machines are also proposed

High frequency voltage injection based stator inter-turn fault detection in permanent magnet machines

An inter-turn short-circuit fault in the stator winding of an electric machine, denoted as turn fault, has been recognized as one of the most severe faults in permanent magnet machines which requires swift and reliable detection, in order to implement appropriate mitigations. The asymmetry brought by a turn fault is widely used for the fault detection. However, similar features also emerges in a less severe high resistance connection (HRC) fault, which may led to incorrect fault identification. In this paper, a more exclusive turn fault detection method with the ability to differentiate from the HRC fault is proposed. It injects high frequency square wave voltage signals and makes use of the difference in high frequency impedance under the two fault conditions. The sensitivity to HRC fault is largely reduced. The proposed turn fault indicator is independent of operating conditions and robust with respect to state transients. This method is validated in a fault tolerant permanent magnet assisted synchronous reluctance machine drive

Current residual based stator inter-turn fault detection in permanent magnet machines

Inter-turn short circuit fault, also known as turn fault is a common fault in electric machines which can cause severe damages if no prompt detection and mitigation are conducted. This paper proposes a turn fault detection method for permanent magnet machines based on current residual. After the impact of the turn fault is firstly analyzed on a simplified mathematical machine model to assess the fault signature, a finite element (FE) model is developed to obtain healthy machine behavior. The residual between the measured and estimated currents by the model with the same applied voltages contains mainly the fault features. The quality of the fault detection can be improved because the fault signatures are enhanced, and the impact of the current controller bandwidth on fault signature is minimized. The dc components in the negative sequence current residuals are extracted through angular integration and their magnitude is defined as the fault indicator. The robustness of the fault detection against transient states is achieved. The effectiveness of the proposed method is validated on a triple redundant fault tolerant permanent magnet assisted synchronous reluctance machine (PMA SynRM)

Low-cost, high-resolution, fault-robust position and speed estimation for PMSM drives operating in safety-critical systems

In this paper it is shown how to obtain a low-cost, high-resolution and fault-robust position sensing system for permanent magnet synchronous motor drives operating in safety-critical systems, by combining high-frequency signal injection with binary Hall-effect sensors. It is shown that the position error signal obtained via high-frequency signal injection can be merged easily into the quantization-harmonic-decoupling vector tracking observer used to process the Hall-effect sensor signals. The resulting algorithm provides accurate, high-resolution estimates of speed and position throughout the entire speed range; compared to state-of-the-art drives using Hall-effect sensors alone, the low speed performance is greatly improved in healthy conditions and also following position sensor faults. It is envisaged that such a sensing system can be successfully used in applications requiring IEC 61508 SIL 3 or ISO 26262 ASIL D compliance, due to its extremely high mean time to failure and to the very fast recovery of the drive following Hall-effect sensor faults at low speeds. Extensive simulation and experimental results are provided on a 3.7 kW permanent magnet drive

Real-Time Fault Diagnosis of Permanent Magnet Synchronous Motor and Drive System

Permanent Magnet Synchronous Motors (PMSMs) have gained massive popularity in industrial applications such as electric vehicles, robotic systems, and offshore industries due to their merits of efficiency, power density, and controllability. PMSMs working in such applications are constantly exposed to electrical, thermal, and mechanical stresses, resulting in different faults such as electrical, mechanical, and magnetic faults. These faults may lead to efficiency reduction, excessive heat, and even catastrophic system breakdown if not diagnosed in time. Therefore, developing methods for real-time condition monitoring and detection of faults at early stages can substantially lower maintenance costs, downtime of the system, and productivity loss. In this dissertation, condition monitoring and detection of the three most common faults in PMSMs and drive systems, namely inter-turn short circuit, demagnetization, and sensor faults are studied. First, modeling and detection of inter-turn short circuit fault is investigated by proposing one FEM-based model, and one analytical model. In these two models, efforts are made to extract either fault indicators or adjustments for being used in combination with more complex detection methods. Subsequently, a systematic fault diagnosis of PMSM and drive system containing multiple faults based on structural analysis is presented. After implementing structural analysis and obtaining the redundant part of the PMSM and drive system, several sequential residuals are designed and implemented based on the fault terms that appear in each of the redundant sets to detect and isolate the studied faults which are applied at different time intervals. Finally, real-time detection of faults in PMSMs and drive systems by using a powerful statistical signal-processing detector such as generalized likelihood ratio test is investigated. By using generalized likelihood ratio test, a threshold was obtained based on choosing the probability of a false alarm and the probability of detection for each detector based on which decision was made to indicate the presence of the studied faults. To improve the detection and recovery delay time, a recursive cumulative GLRT with an adaptive threshold algorithm is implemented. As a result, a more processed fault indicator is achieved by this recursive algorithm that is compared to an arbitrary threshold, and a decision is made in real-time performance. The experimental results show that the statistical detector is able to efficiently detect all the unexpected faults in the presence of unknown noise and without experiencing any false alarm, proving the effectiveness of this diagnostic approach.publishedVersio

Advanced Fault Detection Methods for Permanent Magnets Synchronous Machines

The trend in recent years of transport electrification has significantly increased the demand for reliability and availability of electric drives, particularly in those employing Permanent Magnet Synchronous Machines (PMSM), often selected due to their high efficiency and energy density. Fault detection has been identified as one of the key aspects to cover such demand. Stator winding faults are known to be the second most common type of fault, after bearing fault. An extensive literature review has shown that, although a number of methods has been proposed to address this type of fault, no tool of general application, capable of dealing effectively with fault detection under transient conditions unrelated to the fault, has been proposed up to date. This thesis has made contributions to modelling, real-time emulation and stator winding fault detection of PMSM. Fault detection has been carried out through model-based and signal-based methods with a specific aim at operation during transient conditions. Furthermore, fault classification methods already available have been implemented with features computed by proposed signal-based fault detection methods. The main conclusion drawn from this thesis is that model-based fault detection methods, particularly those based on residuals, appear to be better suited for transient conditions analysis, as opposed to signal-based fault detection methods. However, it is expected that a combination of the two (model/signal) would yield the best results

Real-Time Detection of Incipient Inter-Turn Short Circuit and Sensor Faults in Permanent Magnet Synchronous Motor Drives Based on Generalized Likelihood Ratio Test and Structural Analysis

This paper presents a robust model-based technique to detect multiple faults in permanent magnet synchronous motors (PMSMs), namely inter-turn short circuit (ITSC) and encoder faults. The proposed model is based on a structural analysis, which uses the dynamic mathematical model of a PMSM in an abc frame to evaluate the system’s structural model in matrix form. The just-determined and over-determined parts of the system are separated by a Dulmage–Mendelsohn decomposition tool. Subsequently, the analytical redundant relations obtained using the over-determined part of the system are used to form smaller redundant testable sub-models based on the number of defined fault terms. Furthermore, four structured residuals are designed based on the acquired redundant sub-models to detect measurement faults in the encoder and ITSC faults, which are applied in different levels of each phase winding. The effectiveness of the proposed detection method is validated by an in-house test setup of an inverter-fed PMSM, where ITSC and encoder faults are applied to the system in different time intervals using controllable relays. Finally, a statistical detector, namely a generalized likelihood ratio test algorithm, is implemented in the decision-making diagnostic system resulting in the ability to detect ITSC faults as small as one single short-circuited turn out of 102, i.e., when less than 1% of the PMSM phase winding is short-circuited.publishedVersio

Online control signal-based diagnosis of interturn short circuits of PMSM drive

Modern drives with Permanent Magnet Synchronous Motors (PMSMs) require both efficient control structure to ensure excellent dynamics and effective diagnostic algorithms to detect the motor faults that can occur. This paper shows the combination of both mentioned aspects – the direct-axis based signals of the Field Oriented Control (FOC) structure are proposed as diagnostic signals to allow diagnosing the interturn short-circuit failure that can appear inside stator windings. The amplitudes of second order harmonics are selected as the fault indicators. Different modelling methods are analysed and compared in detail in this paper: an analytical mathematical model, a Finite Element Method (FEM)- based model and next verified using a laboratory setup. The results obtained using all the mentioned models proved that the proposed fault indices are increasing significantly with the number of shorted turns and are independent on the load torque level

Contribution of the two rectifiers reconfiguration to fault tolerance connected to the grid network to feed the GMAW through processor-in-the-loop

This study aims to propose a new diagnosis technique based on the Park’s vector and the polar coordinates of electric currents for the detection and location of open-circuit faults (OC) at the level of two rectifiers connected to the grid network to feed the Gas Metal Arc Welding process (GMAW). This diagnosis technique allows the early location of faulty switches (Thyristors) to overcome the negative effect of faulty rectifiers on welding current, welding voltage, and droplet diameter. For that, the reconfigurable rectifiers have been integrated to accomplish the welding process. The proposed diagnosis technique is applied to reconfigurable rectifiers connected to the GMAW system through numerical simulations using MATLAB/Simulink and real-time processor-in-the-loop (PIL) implementation via DSpace ds 1103 card. The simulation and PIL experimental results show similar trends and great success of the diagnosis technique and the two rectifiers reconfiguration for overcoming the open circuit faults and obtaining high welding quality while maintaining the work-piece and avoiding the distortions caused by the faulty rectifiers, which affecting the grid network and on the GMAW system at the same time