Search results for "induction motor"
showing 10 items of 130 documents
Investigation and reduction of losses on inverter-fed induction motors
2017
An electric motor is more effective and flexible when supplied by a frequency converter. The frequency converter not only produces the fundamental voltage but also a set of higher harmonics which cause additional losses in the motor. Losses in the frequency converter are normally neglected in the drive dimensioning due to insufficient data available from manufacturers. Motor's losses can be reduced by increasing the switching frequency of frequency converters. An increase of the switching frequency may result in higher losses in the frequency converter. This work investigates analytically and experimentally the dependence of the losses of modern motor and frequency converter on a switching …
Identification of induction motor thermal model for improved drivetrain design
2016
Selection of components of electric drivetrains is not only based on evaluating their ability to perform according to mechanical specifications, but — what is equally important — on assessing their thermal protection limits. These are typically affected by electrical and thermal properties of motors and drives. Although rated parameters (such as power, torque, speed, etc.) are easily accessible in catalogs of equipment producers, more specific properties like mass / length of copper winding, heat dissipation factor, rotor / stator dimensions etc. are not available to customers. Therefore, effective selection of drivetrain components is limited due to the lack of sufficient data and the need…
Sensorless control of induction motors using an extended Kalman filter and linear quadratic tracking
2017
Induction motors are the most commonly used prime-movers in industrial applications. Many induction motors supplied by frequency converters are coupled with a physical angular rotor position/velocity sensor which makes the drive complex and require maintenance. This paper presents a sensorless control structure to avoid using a physical angular rotor position/velocity sensor. The proposed method estimates and control the angular rotor velocity using optimal control theory. The optimal controller used in this paper is based on linear quadratic tracking and the states of the machine are estimated using an extended Kalman filter. Both the controller and the estimator utilize the same internal …
Identification of parameters and harmonic losses of a deep-bar induction motor
2017
High frequency harmonics from a frequency converter causes additional losses in a deep-bar induction motor. The harmonics have their own amplitude and phase with respect to the fundamental signal, but the harmonic loss is only dependent on the amplitude of harmonics. A deep-bar induction motor can be modelled by a triple-cage circuit to take skin effect into account. The triple cage circuit having many parameters could be estimated from a small-signal model of the machine by using Differential Evolution. The correctly estimated parameters make the triple-cage circuit valid in a wide range of frequencies. However, the triple-cage circuit is very complicated which makes it difficult to model …
Data-driven Fault Diagnosis of Induction Motors Using a Stacked Autoencoder Network
2019
Current signatures from an induction motor are normally used to detect anomalies in the condition of the motor based on signal processing techniques. However, false alarms might occur if using signal processing analysis alone since missing frequencies associated with faults in spectral analyses does not guarantee that a motor is fully healthy. To enhance fault diagnosis performance, this paper proposes a machinelearning based method using in-built motor currents to detect common faults in induction motors, namely inter-turn stator winding-, bearing- and broken rotor bar faults. This approach utilizes single-phase current data, being pre-processed using Welch’s method for spectral density es…
Multi-Component Fault Detection in Wind Turbine Pitch Systems Using Extended Park's Vector and Deep Autoencoder Feature Learning
2018
Pitch systems are among the wind turbine components with most frequent failures. This article presents a multicomponent fault detection for induction motors and planetary gearboxes of the electric pitch drives using only the three-phase motor line currents. A deep autoencoder is used to extract features from the extended Park's vector modulus of the motor three-phase currents and a support vector machine to classify faults. The methodology is validated in a laboratory setup of a scaled pitch drive, with four commonly occurring faults, namely, the motor stator turns fault, broken rotor bars fault, planetary gearbox bearing fault and planet gear faults, under varying load and speed conditions.
Multiple Fault Diagnosis of Electric Powertrains Under Variable Speeds Using Convolutional Neural Networks
2018
Electric powertrains are widely used in automotive and renewable energy industries. Reliable diagnosis for defects in the critical components such as bearings, gears and stator windings, is important to prevent failures and enhance the system reliability and power availability. Most of existing fault diagnosis methods are based on specific characteristic frequencies to single faults at constant speed operations. Once multiple faults occur in the system, such a method may not detect the faults effectively and may give false alarms. Furthermore, variable speed operations render a challenge of analysing nonstationary signals. In this work, a deep learning-based fault diagnosis method is propos…
Robust control for high performance induction motor drives based on partial state-feedback linearization
2019
This paper deals with a robust input-output feedback linearization control technique for induction motors. Indeed, classic feedback linearization presents two main disadvantages: 1) the accuracy of the dynamic model; and 2) the corresponding correct knowledge of the model parameters. To address this issue, the linear controller has been substituted with a suitably controller designed to be robust to the variations of the main parameters of the induction motor, like stator and rotor resistances, and the three-phase magnetizing inductance. The proposed controller has been tested both in numerical simulation and experimentally on a suitably designed test setup. Moreover, it has been compared w…
Input-Output Feedback Linearization Control with On-line MRAS Based Inductor Resistance Estimation of Linear Induction Motors Including the Dynamic E…
2016
This paper proposes the theoretical framework and the consequent application of the input–output feedback linearization (FL) control technique to linear induction motors (LIMs). LIM, additionally to rotating induction motor, presents other strong nonlinearities caused by the dynamic end effects, leading to a space-vector dynamic model with time-varying inductance and resistance terms and a braking force term. This paper, starting from a recently developed dynamic model of the LIM taking into consideration its end effects, defines a FL technique suited for LIMs, since it inherently considers its dynamic end effects. Additionally, it proposes a technique for the on-line estimation of the indu…
Sensorless Speed Control for Double-Sided Linear Induction Motor Applications
2019
In this work, a flux and speed observer for double-sided linear induction motor applications is presented and experimentally validated. More in detail, from a Double-Sided Linear Induction Motor (DLIM) prototype, the complete modelling and the determination of the related parameters are here reported. Furthermore, the equations for a d-flux and q-flux observer are conceived and several simulation tests are performed. From the good agreements between the trends over time of the speed estimated by the observer and the simulated one, it can be stated that the observer is well designed. Moreover, in order to experimentally validate the proposed observer, a test bench is set-up for the DLIM/obse…