Demagnetization Fault Research Articles

Mode Recognition and Fault Positioning of Permanent Magnet Demagnetization for PMSM

This paper proposes a demagnetization fault detection, mode recognition, magnetic pole positioning, and degree evaluation method for permanent magnet synchronous motors. First, the analytical model of the single-coil no-load back electromotive force (EMF) of demagnetization fault for Permanent magnet synchronous motor (PMSM) arbitrary magnetic poles is established. In the analytical model, the single-coil no-load back EMF residual of the health state and the single magnetic pole sequential demagnetization fault are calculated and normalized. Model results are used as the fault sample database. Second, the energy interval database of the single-coil no-load back EMF residual with different numbers of magnetic pole demagnetization is established. Demagnetization fault detection and degree evaluation are performed by the real-time acquired amplitudes of the single-coil no-load back EMF residual. The number of demagnetization poles is determined by comparing the energy of the single-coil no-load back EMF residual with the energy interval database. Demagnetization mode recognition and magnetic pole positioning are realized by analyzing the correlation coefficients between normalized the single-coil no-load back EMF residual and the fault sample database. Finally, results of analysis of the finite element simulation validate the feasibility and effectiveness of the proposed method.

Performance Degradation of Surface PMSMs with Demagnetization Defect under Predictive Current Control

To control the current of a surface mounted permanent magnet synchronous machine fed by a two-level voltage source inverter, a large variety of control algorithms exists. Each of these controllers performs differently concerning dynamic performance and control- and voltage quality, but also concerning sensitivity to demagnetization faults. Therefore, this paper investigates the performance degradation of three advanced predictive controllers under a partial demagnetization fault. The three predictive controllers are: finite-set model based predictive control, deadbeat control, and a combination of both previous algorithms. To achieve this goal, the three predictive controllers are first compared under healthy conditions, and afterwards under a partial demagnetization fault. A PI controller is added to the comparison in order to provide a model-independent benchmark. Key performance indicators, obtained from both simulations and experimental results on a 4 kW axial flux permanent magnet synchronous machine with yokeless and segmented armature topology, are introduced to enable a quantification of the performance degradation of the controllers under a demagnetization fault. A general conclusion is that the deadbeat controller shows superior control quality, even under partial demagnetization.

Demagnetization Fault Diagnosis of PMSM in Electric Vehicles Using H Infinity Filter

With the extension of the low-carbon economy in the transportation field, electric vehicles and its related technologies have been rapidly developed. As the power source of electric vehicles, the reliable operation of the motor and its drive system is a key factor to ensure the safe and stable operation of the while vehicle. Permanent magnet synchronous motor (PMSM) have received much attention in this field due to its well- known technical advantages. The control performance, efficiency, and reliability depend to a large extent on the health of the rotor permanent magnet. Therefore, the online and reliable monitoring of permanent magnet flux linkage is particular important. The performance degradation of permanent magnet is called demagnetization fault. It is directly related to the flux linkage of PMSM. In this paper, the whole drive system of an electric vehicle with healthy PMSM and demagnetized PMSM has been built. As the magnet flux linkage is proportional to the strengths of the permanent magnet, it is essential to estimate the flux linkage online to detect the demagnetization fault. Based on that, demagnetization fault diagnosis scheme for PMSM in electric vehicles has been proposed based on the state equation under dq axis reference. The scheme consists of the following serial processes: state judgement, data extraction, H infinity filter, estimation of magnet flux linkage, fault decision. The simulation results show that this method is robust to the inaccurate initial state value and can be used under dynamic progress online.

Analysis of Permanent Magnet Synchronous Motor Fault Diagnosis Based on Learning

This paper presents an effective diagnosis algorithm for permanent magnet synchronous motors running with an array of faults of varying severity over a wide speed range. The fault diagnosis is based on a current signature analysis. The complete fault motor diagnosis system requires the extraction of features based on the current method and a subsequent method for adding classifications. In this paper, we propose two feature extraction methods: the first involves a classification method that utilizes a wavelet packet transform and the second is a deep 1-D convolution neural network that includes a softmax layer. The experimental results obtained using real-time motor stator current data demonstrate the effectiveness of the proposed methods for real-time monitoring of motor conditions. The results also demonstrate that the proposed methods can effectively diagnose five different motor states, including two different demagnetization fault states and two bearing fault states.

Comprehensive Analysis of Demagnetization Faults in BLDC Motors Using Novel Hybrid Electrical Equivalent Circuit and Numerical Based Approach

Brushless Direct Current (BLDC) motors are the type of Permanent Magnet Synchronous Motors (PMSMs) with trapezoidal back-EMF. Due to high proliferation of BLDC motors in industrial applications, these motors are extensively been operated for longer durations. During the continuous heavy operation, these motors are subjected to environmental, physical and thermal stresses which can lead to faults. Fault can be on the stator windings or on the Permanent Magnets (PMs) of the rotor of a machine, which can manifest into electrical quantities like currents and/or voltages, magnetic quantities like flux density and thermal characteristics of a machine. This paper shall explore in detail about the demagnetization fault in PMs of a BLDC motor. Modeling of a machine can be done through different available techniques such as Electrical Equivalent Circuit (EEC) based method or analytical method which accounts several assumptions in order to simplify the analysis. While the Numerical Methods (NM) such as Finite Element Method Magnetics (FEMM) gives more authoritative solutions. This paper aims to combine both these approaches and contribute by developing a novel Hybrid EEC-FEMM model for a closed loop BLDC motor drive using a Hysteresis Current Control (HCC) technique. The developed model is simulated both under healthy and faulty conditions. In order to simulate the effects of fault in the machine, demagnetization is introduced in the PM through various methods like change in magnetic coercivity, placement of broken magnets, partial demagnetization and lastly by replacement of a PM with a non-magnetic material which is an extreme case of demagnetization. The investigation on the machine performance through change in quantities like stator current, back-EMF, electromagnetic torque, mechanical speed and magnetic flux density is analyzed. Further using the Maxwell 2D tool, a Finite Element (FE) model of a BLDC motor is developed and its performance is examined under both healthy and demagnetization fault conditions. The experimental validation of demagnetization fault supports the inferences drawn from the simulation results.

Robust Model-Free Nonsingular Terminal Sliding Mode Control for PMSM Demagnetization Fault

In this paper, a robust model-free nonsingular terminal sliding-mode control (MFNTSMC) algorithm based on the ultra-local model is proposed to reduce the influence of permanent magnet (PM) demagnetization for PM synchronous motors (PMSMs). First, the PMSM mathematical model in normal and demagnetization is described, and the ultra-local model of speed loop and current loop is constructed based on the input and the output of the PMSM vector control system. Then, the MFNTSMC method is proposed and adopted to design the speed controller and d-q -axis current controller, and the sliding-mode observer is designed to estimate the unknown terms of the ultra-local model. Finally, compared with the PI control method and model-free control method, the results of simulations and experimentations show that the MFNTSMC method can improve the dynamic response while maintaining robustness of PMSM driven system, reduce the dependence of the design of controller on the precise PMSM model, and has fault-tolerant control function for PM demagnetization fault.

A Comprehensive Review of Winding Short Circuit Fault and Irreversible Demagnetization Fault Detection in PM Type Machines

Contemporary research has shown impetus in the diagnostics of permanent magnet (PM) type machines. The manufacturers are now more interested in building diagnostics features in the control algorithms of machines to make them more salable and reliable. A compact structure, exclusive high-power density, high torque density, and efficiency make the PM machine an attractive option to use in industrial applications. The impact of a harsh operational environment most often leads to faults in PM machines. The diagnosis and nipping of such faults at an early stage have appeared as the prime concern of manufacturers and end users. This paper reviews the recent advances in fault diagnosis techniques of the two most frequently occurring faults, namely inter-turn short fault (ITSF) and irreversible demagnetization fault (IDF). ITSF is associated with a short circuit in stator winding turns in the same phase of the machine, while IDF is associated with the weakening strength of the PM in the rotor. A detailed literature review of different categories of fault indexes and their strengths and weaknesses is presented. The research trends in the fault diagnosis and the shortcomings of available literature are discussed. Moreover, potential research directions and techniques applicable for possible solutions are also extensively suggested.

Magnetic‐equivalent‐circuit approach for inter‐turn and demagnetisation faults analysis in surface mounted permanent‐magnet synchronous machines using pole specific search‐coil technique

Magnetic-equivalent-circuit model for surface mounted permanent-magnet synchronous machines in both healthy and faulty cases is presented in this study, where both saturation effect and space harmonics are considered. Pole numbers, magnets and slot numbers can be chosen arbitrarily in the proposed model, and the behavior of the machine can be studied under various kinds of faults by a single model. Demagnetization, as well as inter-turn short short-circuit faults of the stator windings, are modelled, and a fault detection method is proposed. It is shown that the demagnetization fault is not detectible by stator current analysis, therefore an additional pole specific coil is considered in this study as a search coil. For modelling, the differential equations representing the electrical part of the PMSM model are converted into an algebraic type using the well-known trapezoidal technique and are solved simultaneously together with the non-linear magnetic equations using the Newton-Raphson method. It is shown that the presented model in this study is capable of effective modelling of the healthy and faulty machine under mentioned faults by a single model, thus reducing the computational complexity of the model. The effectiveness of the proposed MEC model is verified using finite-element method via Maxwell software.

Demagnetization Fault Detection for Five-Phase IPMSM Through Integral Terminal Sliding Mode Flux-Linkage Observer

ABSTRACTThis research deals with robust demagnetization fault detection for five-phase interior permanent magnet synchronous motors (IPMSM) for the first time. To estimate the rotor flux linkage, two novel integral terminal sliding mode observers are proposed. The first observer utilizes a fractional integral terminal sliding surface and the second one uses a sign integral terminal sliding surface. These observers are designed based on the error of stator d1-q1 currents generated from their measured and estimated values. Practical stability of the proposed observers is demonstrated using Lyapunov stability theory. Comparative simulations validate the feasibility and effectiveness of the proposed ITSM observers on a five-phase IPMSM.

Demagnetization monitoring and life extending control for permanent magnet-driven traction systems

Abstract This paper presents a novel scheme of demagnetization monitoring and life extending control for traction systems driven by permanent magnet synchronous motors (PMSMs). Firstly, the offline training is carried to evaluate fatigue damage of insulated gate bipolar transistors (IGBTs) under different flux loss based on first-principle modeling. Then an optimal control law can be extracted by turning down the power distribution factor of the demagnetizing PMSM until all damages of IGBTs turn to balance. Next, the similarity-based empirical modeling is employed to online estimate remaining flux of PMSMs, which is used to update the power distribution factor by referring the optimal control law for the health-oriented autonomous control. The proposed strategy can be demonstrated by a case study of traction drive system coupled with dual-PMSMs. Compared with traditional control strategy, the results show that the novel scheme can not only guarantee traction performance but also extend remaining useful life (RUL) of the system after suffering demagnetization fault.

Tolerance analysis of electrified vehicles on the motor demagnetization fault: From an energy perspective

Due to possible overheat, abrasion or mechanical vibrations, demagnetization fault is inevitable in permanent magnet synchronous motors (PMSMs), which could greatly decrease the motor’s efficiency and hence an electrified vehicle’s performance. This paper, from an energy efficiency point of view, proposes to analyze the tolerance ability of different electrified vehicles on motor demagnetization faults, via PMSM flux density degradation modeling, efficiency estimation and dynamic programming (DP) based powertrain energy management. The relationship between different demagnetization levels and resultant motor efficiencies is obtained, and analyzed according to the motor operation area. Demagnetized PMSM is adopted in a pure electric vehicle (PEV), a hybrid electric vehicle (HEV) and a plug-in hybrid electric vehicle (PHEV) for energy efficiency analysis. Tolerance analysis indicates that the powertrain efficiency decrease caused by motor demagnetization is more severe under urban driving conditions, especially with PEV and PHEV configurations compared with HEV. A demagnetization threshold investigation is also given in this paper.

Demagnetization Fault Detection in Axial Flux PM Machines by Using Sensing Coils and an Analytical Model

The paper studies demagnetization detection in axial flux permanent magnet synchronous machines of the yokeless and segmented armature (YASA) type. In YASA machines, asymmetrical defects can occur: the demagnetization defects in the permanent magnets of both rotors differ from each other. Many techniques can indicate that there is a defect, even if it is an asymmetrical defect, but cannot detect which rotor has the defect, i.e., exactly locate the asymmetrical defect. In this paper, a method is proposed to detect and locate asymmetrical demagnetization defects in AFPMSMs. The method is useful for real-time condition monitoring of demagnetization defects, or as virtual temperature sensor for the magnets. A sensing coil is placed in each air gap. An analytical model is constructed, which uses the demagnetization defect and the three-phase current as input and calculates the sensing coil back-EMF. Sensing coils back-EMF data are combined with the data from the analytical model to solve an electromagnetic inverse problem. The results are the demagnetization amount and location of the demagnetization defect. The method is validated with the experimental data.

Demagnetization Modeling and Fault Diagnosing Techniques in Permanent Magnet Machines Under Stationary and Nonstationary Conditions: An Overview

Permanent magnet (PM) machines are widely used in industrial processes due to their merits such as high power density and torque and low losses (high efficiency). These machines operate frequently under harsh conditions; therefore, they expose different types of faults. These faults can be diagnosed in initial stages using different techniques and prevent the faults' progress to catastrophic stages. One of the most important PM machine faults in terms of occurrence rate is demagnetization fault, whose causes can be heat, electrical, environmental or combinations. This may lead to efficiency drop, poor performance, and low reliability of the system. This paper attempts to review and summarize the demagnetization fault diagnosis methods in PM machines. First the fault generating factors and their impacts on the performance of the motor are discussed. Then, the recently developed techniques for demagnetization fault under stationary and nonstationary conditions in two separate sections are addressed. Presented methods are compared; their weaknesses and strengths are noted. Finally, suggestions for further research are proposed.

Torque-Ripple-Based Interior Permanent-Magnet Synchronous Machine Rotor Demagnetization Fault Detection and Current Regulation

To develop a reliable permanent-magnet synchronous machine (PMSM) controller for electric vehicle application, detection of permanent-magnet (PM) demagnetization conditions is of significance. This paper explores the use of torque ripple for online PM demagnetization fault diagnosis using continuous wavelet transforms (CWT) and grey system theory (GST). First, a torque-ripple-based rotor flux linkage detection model considering electromagnetic noises is proposed, which employs CWT filtering, wavelet ridge spectrum, and torque ripple energy extraction. This model is able to reveal the torque variation and eliminate the effect of electromagnetic interferences. Second, GST is employed to facilitate the detection of demagnetization ratios and torque ripple energy pulsations caused by demagnetization. Third, a current regulation strategy is proposed to minimize the torque ripples induced by PM demagnetization, which contributes to making the approach feasible to interior PMSM (IPMSM). Furthermore, the proposed real-time irreversible demagnetization detection approach can identify the demagnetization fault under different operating conditions. The proposed approach and current regulation strategy are experimentally verified on a down-scaled laboratory IPMSM.

Comparative Study of Fault-Tolerant Switched-Flux Permanent-Magnet Machines

The fault-tolerant capabilities are compared in this paper for the conventional double-layer switched-flux permanent-magnet machine and its single-layer counterparts, i.e., C-core, E-core, and modular. The comparison includes the interturn short-circuit and irreversible demagnetization faults. A combination of Simulink and finite element models is used in the study. Based on the predictions, it is found that the modular topology produces the lowest short-circuit current and also has the best demagnetization withstand capability while the conventional one produces the highest short-circuit current and has the worst demagnetization withstand capability. The frozen permeability method is employed to separate the flux produced by armature current and magnets, and the results showed that, besides the influence of short-circuit current, the available magnet volume and magnetic circuit configuration play an important role in the demagnetization process. It is also found that removing half of the magnets, such as using C-core, E-core, and modular topologies, generally improves the demagnetization withstand capability and also increases the torque per magnet volume. Measured results are also presented to validate the short-circuit current predictions and magnet demagnetization.

Demagnetization Faults Robust Detection Method Based on an Adaptive Sliding Mode Observer for PMSM

To detect demagnetization faults in real time based on an adaptive sliding mode observer, we used a permanent-magnet synchronous motor (PMSM). Demagnetization faults are first modeled for the PMSM using coordinates oriented to the magnetic field. To solve demagnetization faults problems as multiple parameters change, we used adaptive and sliding mode variable structure control and designed an adaptive sliding mode observer. The adaptive estimation algorithm of the permanent magnet flux is given and the observer’s stability is proven by Lyapunov stability theory. Simulation and experimental results demonstrate the feasibility and effectiveness of our proposal.

Fault Diagnosis Method of Permanent Magnet Synchronous Motor for Electrical Vehicle

The permanent magnet synchronous motor has high efficiency driving performance and high power density output characteristics compared with other motors. In addition, it has good regenerative operation characteristics during braking and deceleration driving condition. For this reason, permanent magnet synchronous motor is generally applied as a power train motor for electrical vehicle. In permanent magnet synchronous motor, the most probable causes of fault are demagnetization of rotor's permanent magnet and short of stator winding turn. Therefore, the demagnetization fault of permanent magnet and turn fault of stator winding should be detected quickly to reduce the risk of accident and to prevent the progress of breakdown of power train system. In this paper, the fault diagnosis method using high frequency low voltage injection was suggested to diagnose the demagnetization fault of rotor permanent magnet and the turn fault of stator winding. The proposed fault diagnosis method can be used to check the faults of permanent magnet synchronous motor during system check-up process at vehicle starting and idling stop mode. The feasibility and usefulness of the proposed method were verified by the finite element analysis.

On the Accuracy of Fault Detection and Separation in Permanent Magnet Synchronous Machines Using MCSA/MVSA and LDA

In this paper, the motor current/voltage signature analysis and linear discriminant analysis (LDA) are evaluated with respect to the accuracy to detect the status of permanent magnet synchronous machines (PMSMs) whether it is healthy or faulted, determine the type of that fault, and estimate the severity in the case of static eccentricity or turn-to-turn short-circuit fault. Three types of faults are discussed: static eccentricity, turn-to-turn short circuit, and partial demagnetization fault. Two-dimensional finite element analysis (FEA) is used to model and simulate the machine under healthy and faulted conditions. Fast Fourier transform is applied to the phase voltage or current signals to obtain the frequency spectrum. A combination of the amplitude of the harmonics of the stator voltage or current signals are used as detailed features for the classifier for fault detection. LDA is chosen as a classification method for both detecting the fault and estimating its severity. Two different winding types of PMSMs are tested: a concentrated and a distributed winding machine. To validate the simulation results, experiments at different operational points are carried out and the results are compared with the sFEA.

Detection of Partial Demagnetization Fault in PMSMs Operating Under Nonstationary Conditions

Demagnetization fault detection of in-service permanent magnet synchronous machines (PMSMs) is a challenging task, because most PMSMs operate under nonstationary circumstances in industrial applications. A novel approach based on tracking characteristic orders of stator current using Vold–Kalman filter is proposed to detect the partial demagnetization fault in PMSMs running at nonstationary conditions. The amplitude of envelope of the fault characteristic orders is used as fault indictor. Experimental results verify the superiority of the proposed method on the partial demagnetization online fault detection of PMSMs under various speed and load conditions.

Demagnetization Diagnosis of Permanent Magnet Synchronous Motor Using Frequency Analysis at Standstill Condition

Recently, electric vehicles have got significant attention because it is more eco-friendly and efficient than internal combustion engine vehicles. Instead of an internal combustion engine, the electric vehicle has a motor for propulsion. The permanent magnet synchronous motor which has permanent magnet instead of field winding in the rotor has especially higher efficiency and power density than other types of motor. When the irreversible demagnetization is occurred, drivers are exposed to high risk of accident by the fault operation of motor. Therefore, the irreversible demagnetization of permanent magnet should be detected to reduce the risk of accident. In this study, the demagnetization diagnosis method based on the result of locked rotor test is proposed. Based on short measurement time, the proposed diagnosis method aims to detect the demagnetization fault when an electric vehicle is at a complete standstill. The proposed method is verified through the finite element analysis.