Elias G. Strangas

Trends in Fault Diagnosis for Electrical Machines: A Review of Diagnostic Techniques

The fault diagnosis of rotating electrical machines has received an intense amount of research interest during the last 30 years. Reducing maintenance costs and preventing unscheduled downtimes, which result in losses of production and financial incomes, are the priorities of electrical drives manufacturers and operators. In fact, both correct diagnosis and early detection of incipient faults lead to fast unscheduled maintenance and short downtime for the process under consideration. They also prevent the harmful and sometimes devastating consequences of faults and failures. This topic has become far more attractive and critical as the population of electric machines has greatly increased in recent years. The total number of operating electrical machines in the world was around 16.1 billion in 2011, with a growth rate of about 50% in the last five years [1].

Multiphase space vector pulse width modulation

Pole-phase modulation adjusts the pole-phase ratio of an induction machine and requires a multileg, multiphase inverter. This paper analyzes an n-leg n-phase inverter and presents techniques for n-phase space vector pulse width modulation (SVPWM). In particular, nine-phase SVPWM is developed and implemented on a nine-winding induction machine. The nine-phase SVPWM is compared to nine-phase sine-triangle PWM in terms of dc bus utilization.

Identification of Intermittent Electrical and Mechanical Faults in Permanent-Magnet AC Drives Based on Time–Frequency Analysis

The detection of noncatastrophic faults in conjunction with other factors can be used to determine the remaining life of an electric drive. As the frequency and severity of these faults increase, the working life of the drive decreases, leading to eventual failure. In this paper, methods are presented to identify developing electrical and mechanical faults based on both the short-time Fourier transform and wavelet analysis of the field-oriented currents in permanent-magnet ac drives. The different fault types are classified by developing a linear discriminant classifier based on the transform coefficients.

Time–Frequency Analysis for Efficient Fault Diagnosis and Failure Prognosis for Interior Permanent-Magnet AC Motors

The detection of noncatastrophic faults in conjunction with other factors can be used to determine the remaining life of an electric drive. As the frequency and severity of these faults increase, the working life of the drive decreases, leading to eventual failure. In this paper, four methods to identify developing electrical faults are presented and compared. They are based on the short-time Fourier transform, undecimated-wavelet analysis, and Wigner and Choi-Williams distributions of the field-oriented currents in permanent-magnet ac drives. The different fault types are classified using the linear-discriminant classifier and k-means classification. The comparison between the different methods is based on the number of correct classifications and Fishers discriminant ratio. Multiple-class discrimination analysis is also introduced to remove redundant information and minimize storage requirements.

Extended Kalman Filtering for Remaining-Useful-Life Estimation of Bearings

Condition-based maintenance, which includes both diagnosis and prognosis of faults, is a topic of growing interest for improving the reliability of electrical drives. Bearings constitute a large portion of failures in rotational machines. Although many techniques have been successfully applied for bearing fault diagnosis, prognosis of faults, particularly predicting the remaining useful life (RUL) of bearings, is a remaining challenge. The main reasons for this are a lack of accurate physical degradation models and limited labeled training data. In this paper, we introduce a data-driven methodology, which relies on both time and time-frequency domain features to track the evolution of bearing faults. Once features are extracted, an analytical function that best approximates the evolution of the fault is determined and used to learn the parameters of an extended Kalman filter (KF). The learned extended KF is applied to testing data to predict the RUL of bearing faults under different operating conditions. The performance of the proposed method is evaluated on PRONOSTIA experimental testbed data.

Iron and Magnet Losses and Torque Calculation of Interior Permanent Magnet Synchronous Machines Using Magnetic Equivalent Circuit

We present a faster and simpler approach for the calculation of iron and magnet losses and torque of an interior permanent-magnet synchronous machine (IPMSM) than finite-element methods (FEM). It uses a magnetic equivalent circuit (MEC) based on large elements and takes into account magnetic saturation and magnet eddy currents. The machine is represented by nonlinear and constant reluctance elements and flux sources. Solution of the nonlinear magnetic circuit is obtained by an iterative method. The results allow the calculation of losses and torque of the machine. Due to the approximations used in the formulation of the MEC, this method is less accurate but faster than nonlinear transient magnetic FEM, and is more useful for the comparison of different machine designs during design optimization.

Equivalent fuel consumption optimal control of a series hybrid electric vehicle

Abstract Improvements in hybrid electric vehicle fuel economy with reduced emissions strongly depend on their supervisory control strategy. In order to develop an efficient real-time supervisory control strategy for a series hybrid electric bus, the proposed equivalent fuel consumption optimal control strategy is compared with two popular strategies, thermostat and power follower, using backward simulations in ADVISOR. For given driving cycles, global optimal solutions were also obtained using dynamic programming to provide an optimization target for comparison purposes. Comparison simulations showed that the thermostat control strategy optimizes the operation of the internal combustion engine and the power follower control strategy minimizes the battery charging and discharging operations which, hence, reduces battery power loss and extends the battery life. The equivalent fuel consumption optimal control strategy proposed in this paper provides an overall system optimization between the internal combustion engine and battery efficiencies, leading to the best fuel economy.

Prognosis of Gear Failures in DC Starter Motors Using Hidden Markov Models

Diagnosis classifies the present state of operation of the equipment, and prognosis predicts the next state of operation and its remaining useful life. In this paper, a prognosis method for the gear faults in dc machines is presented. The proposed method uses the time-frequency features extracted from the motor current as machine health indicators and predicts the future state of fault severity using hidden Markov models (HMMs). Parameter training of HMMs generally needs huge historical data, which are often not available in the case of electrical machines. Methods for computing the parameters from limited data are presented. The proposed prognosis method uses matching pursuit decomposition for estimating state-transition probabilities and experimental observations for computing state-dependent observation probability distributions. The proposed method is illustrated by examples using data collected from the experimental setup.

Comparative Evaluation of Direct Torque Control Strategies for Permanent Magnet Synchronous Machines

This paper presents a comprehensive evaluation of several direct torque control (DTC) strategies for permanent magnet synchronous machines (PMSMs), namely DTC, model predictive DTC, and duty ratio modulated DTC. Moreover, field-oriented control is also included in this study. The aforementioned control strategies are reviewed and their control performances are analyzed and compared. The comparison is carried out through simulation, finite-element analysis, and experimental results of a PMSM fed by a two-level voltage source inverter. With the intent to fully reveal the advantages and disadvantages of each control strategy, critical evaluation has been conducted on the basis of several criteria: Torque ripple, stator flux ripple, switching frequency of inverter, steady-state control performance, dynamic response, machine losses, parameter sensitivity, algorithm complexity, and stator current total harmonic distortion.

Speed Observer and Reduced Nonlinear Model for Sensorless Control of Induction Motors

We consider field-oriented speed control of induction motors without mechanical sensors. We augment the traditional approach with a flux observer and derive a sixth-order nonlinear model that takes into consideration the error in flux estimation. A high-gain speed observer is included to estimate the speed from field-oriented currents and voltages. The observer design is independent of the feedback controller design. By high-gain-observer theory, we define a virtual speed output for the sixth-order nonlinear model, which can now be used to design a feedback controller whose performance is recovered by the speed observer when the observer gain is chosen high enough. We then focus on the traditional field oriented control (FOC) approach where the flux is regulated to a constant reference and high-gain current controllers are used. By designing a flux regulator to maintain the flux at a constant reference, and a current regulator to regulate the q-axis current to its command, we derive a third-order nonlinear model that captures the essence of the speed regulation problem. The model has the speed and two flux estimation errors as the state variables, the q -axis current as the control input, and the virtual speed as the measured output. It enables us to perform rigorous analysis of the closed-loop system under different controllers, and under uncertainties in the rotor and stator resistances and the load torque. In this paper, we emphasize the design of feedback controllers that include integral action. The analysis reveals an important role played by the steady-state product of the flux frequency and the q-axis current in determining the control properties of the system. The conclusions arrived at by using the reduced-order model are collaborated by simulation and experimental results.