Delta Connected Induction Motor Research Articles

The analysis of odd triple harmonics to detect broken rotor bar in delta-connected induction motors

The analysis of odd triple harmonics to detect broken rotor bar in delta-connected induction motors

Physics Informed Neural Network-based High-frequency Modeling of Induction Motors

The high-frequency (HF) modeling of induction motors plays a key role in predicting the motor terminal overvoltage and conducted emissions in a motor drive system. In this study, a physics informed neural network-based HF modeling method, which has the merits of high accuracy, good versatility, and simple parameterization, is proposed. The proposed model of the induction motor consists of a three-phase equivalent circuit with eighteen circuit elements per phase to ensure model accuracy. The per phase circuit structure is symmetric concerning its phase-start and phase-end points. This symmetry enables the proposed model to be applicable for both star- and delta-connected induction motors without having to recalculate the circuit element values when changing the motor connection from star to delta and vice versa. Motor physics knowledge, namely per-phase impedances, are used in the artificial neural network to obtain the values of the circuit elements. The parameterization can be easily implemented within a few minutes using a common personal computer (PC). Case studies verify the effectiveness of the proposed HF modeling method.

Nonlinear Characteristics Compensation of Inverter for Low-Voltage Delta-Connected Induction Motor

This paper proposes a scheme that can compensate for the nonlinear characteristics of voltage source inverters (VSIs) for low-voltage delta-connected induction motors (IMs). Due to the nonlinearity introduced by the dead-time, the on/off delay, and the voltage drop across the power device, the output voltage of VSIs is seriously distorted, causing distortion in the phase current of the IM, which will lead to output torque ripple. However, the existing compensation methods for three-phase VSIs are derived from star-connected loads, or ignore the conducting properties of power devices. Moreover, the current polarity detection near the current zero is quite complex. In this paper, by taking such nonlinear characteristics into consideration, especially the conducting property of metal-oxide-semiconductor field effect transistors (MOSFETs), an output voltage model of VSIs for low-voltage delta-connected induction motors is presented. After that, in view of the difficulty in detecting the line current polarity near the current zero which might lead to the wrong compensation, an advancing current crossing zero (ACCZ) compensation is proposed. Subsequently, a compensation scheme which combines the compensation based on the VSI output voltage model and ACCZ compensation is proposed. Finally, the proposed compensation scheme is implemented based on a digital signal processor (DSP) drive system. The experimental results show that the proposed scheme has better performance than the common method in terms of suppressing the effect of the nonlinear characteristics of VSI, which demonstrates that the proposed compensation scheme is feasible and effective for the compensation of the nonlinear characteristics of VSI for low-voltage delta-connected IMs.

Online Equivalent Circuit Parameter Estimation of Three-Phase Induction Motor Using ANN

Three-phase induction motor is compact, robust and simple in construction. An accurate estimation of parameters is always required for precise control and monitoring of three-phase induction motor. There are many ways to find the induction motor parameters, but to improve the accuracy of them, the neural approach is used in this paper. The GNN used for online estimation of delta-connected induction motor parameters is presented, and the results are compared with ANN. Experimental setup is developed in Electrical Power Research Lab at Dayalbagh Educational Institute, Agra, U.P., India, which consists of a 415-V, 50-Hz, three-phase squirrel-cage induction motor, belt-pulley loading system, voltage-, current- and power-measuring sensors, three-phase autotransformer, data acquisition system and online parameter estimator. The sensor data are used to estimate induction motor parameters online using neural approach.

The Zero-Sequence Current as a Generalized Diagnostic Mean in Δ-Connected Three-Phase Induction Motors

In this paper, a new diagnostic mean is introduced for accurate, reliable, and effective diagnosis of faults in delta-connected induction motors. This mean is the zero-sequence stator current spectrum. The study is carried out with analytical calculations and finite-element method simulations. Most common faults are examined for a 4-kW cage induction motor. The analysis will reveal that the proposed mean is able to successfully identify the static eccentricity fault, even in induction motors which produce principal slot harmonics, the broken bar fault, the unbalanced voltage supply, and the stator interturn short-circuit. It will also be shown that through the proposed method, it is possible to distinguish the interturn short-circuit from the unbalanced voltage supply.

Observer-Based Estimation of Stator-Winding Faults in Delta-Connected Induction Motors: A Linear Matrix Inequality Approach

This paper addresses the subject of interturn short circuit estimation in the stator of a delta-connected induction motor. In this paper, an adaptive observer scheme is proposed. The proposed observer is capable of simultaneously estimating the speed of the motor, the amount turns involved in the short circuit, and an expression of the current in the short circuit. Moreover, the states of the motor are estimated, meaning that the magnetizing currents are made available even though a fault has occurred in the motor. To be able to develop this observer, a model that is particularly suitable for the chosen observer design, is also derived. The efficiency of the proposed observer is demonstrated by tests performed on a test setup with a customized designed induction motor. With this motor it is possible to simulate interturn short-circuit faults.

Development and analysis of novel soft-starter∕energy-saver topology for delta-connected induction motors

A thyristorised star/delta switch is proposed as a soft starter and energy saver for delta-connected induction motor drives. A low-cost microprocessor-based hardware is developed and used for the control of the star/delta switch. The use of the star/delta switch for starting is first explained followed by its application as an energy saver. Three schemes of switching transitions are proposed and implemented for the star (delta) to delta (star) changeover process. Extensive simulation and experimental results are presented to show that the proposed circuit is a promising candidate as a starter/energy saver for delta-connected induction motor drives.

Temperature Rise Test of Delta-Connected Induction Motors by Phantom Loading

Temperature rise test of delta-connected induction motors by phantom loading This paper describes a new circuit arrangement suitable for performing heat runs on delta-connected induction motors using the phantom loading principle. Experiments performed on two laboratory-sized motors verified the practicability and accuracy of the method.

A comparison between star and delta connected induction motors when supplied by current source inverters

This paper analyses whether any differences in behaviour arise due to an induction motor being star or delta connected when supplied by a current source inverter. Two comparisons are considered. The first is that of a delta connected motor compared to a star connected motor of the same power and voltage ratings; the star connected motor in this case is then mathematically the delta connected motor's equivalent star connection. The second case considered is that of a delta connected motor rewired as a star connected motor.