Methods for direct torque control of induction machines

Krušelj, Dubravko

doi:10.1109/edpe.2017.8123236

Cited by 4 publications

(5 citation statements)

References 39 publications

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“…Because it suffers from a few disadvantages like high flux and torque ripple or varying switching frequency, plenty of developed modifications striving to eliminate these disadvantages are known [3]. Because the switching losses are significant in high-power drives, the low switching frequency of the transistors must be used.…”

Section: Introductionmentioning

confidence: 99%

Induction Motor Drive Direct Torque Control and Predictive Torque Control Comparison Based on Switching Pattern Analysis

Karlovsky

Lettl

2018

Energies

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This paper describes a switching pattern generated in case of induction motor drive predictive torque control (PTC) compared to a switching pattern of direct torque control (DTC). PTC is a modern control method for electric drives based on model predictive control (MPC). DTC is a very powerful method and is today an industrial standard for controlling an induction motor drive. Its usage is wide-spread, mainly in high-power applications. However, the method suffers from a few disadvantages. One of the causes of the control method's problematic behavior is choosing the switching combinations in the flux sector. Another inconvenience is the common selection table not including all voltage vectors in given sector. By these factors, the ripples of flux vector trajectory and torque waveforms are influenced. The longer the sample time is, the more significant the influence of factors becomes, because only a few steps occur within one turn of the magnetic flux vector. Based on the detailed analysis, the reasons of the different performance of both systems are explained. The analysis performed by simulation in Matlab Simulink environment has proved that, while DTC might choose voltage vector that pushes system away from the reference values, the MPC always chooses the most proper vector. The experimental results measured on the real drive confirm the appropriate vector selection, just in case of the predictive control method.

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Section: Introductionmentioning

confidence: 99%

Induction Motor Drive Direct Torque Control and Predictive Torque Control Comparison Based on Switching Pattern Analysis

Karlovsky

Lettl

2018

Energies

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“…To decouple control between the torque and stator flux, the stator flux magnitude will be controlled and regulated to be constant, this concept complies with the constant V/F control principle, as shown in Equation (1). When considering Equation (2), under normal operation conditions, the slip is very small, implying that R r /S >> R s and R r /S >> (X ls + X lr ).…”

Section: Direct Torque Control Based On Constant Voltage Per Frequencmentioning

confidence: 99%

“…For these reasons, several control methods have been developed. In recent years, the two most popular high performance control methods for IM drives are field-oriented control (FOC) and direct torque control (DTC) [1][2][3]. These control algorithms can decouple control between torque and flux and offer good dynamic and steady-state torque responses.…”

Section: Introductionmentioning

confidence: 99%

“…DTC is more attractive than FOC in simplicity, less parameter sensitivity, quick torque response and effortless implementation complexity. Moreover, the coordinate transformation and the current regulators are not required [1]. However, for appropriate stator voltage selection, it uses nonlinear hysteresis comparators and look-up switching table that produce high torque and flux ripples and variable switching frequency cause noises, vibrations and increased losses [4,5].…”

Section: Introductionmentioning

confidence: 99%

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Online Speed Estimation Using Artificial Neural Network for Speed Sensorless Direct Torque Control of Induction Motor based on Constant V/F Control Technique

Pimkumwong

Wang

2018

Energies

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This paper presents the speed estimator for speed sensorless direct torque control of a three-phase induction motor based on constant voltage per frequency (V/F) control technique, using artificial neural network (ANN). The estimated stator current equation is derived and rearranged consistent with the control algorithm and ANN structure. For the speed estimation, a weight in ANN, which relates to the speed, is adjusted by using Widrow-Hoff learning rule to minimize the sum of squared errors between the measured stator current and the estimated stator current from ANN output. The consequence of using this method leads to the ability of online speed estimation and simple ANN structure. The simulation and experimental results in high-and low-speed regions have confirmed the validity of the proposed speed estimation method. switching table are replaced by the proportional-integral (PI) controllers and SVM technique when comparing with the traditional DTC. The coordinate transformation, which is used in DTC-SVM, is not required. As a result, the torque and flux ripples are reduced and the switching frequency is constant. However, the speed signal is required in this control algorithm. Speed signal is generally achieved in two ways: one is the direct measurement through speed sensors such as tachogenerators, optical rotary encoders and magnetic rotary encoders; the other is the software based state observers and estimators by other physical parameters known as speed sensorless.The speed sensorless control of IM drives has attracted attention due to its advantages of reduction of hardware complexity and cost, eliminating of sensor cables, higher mechanical robustness, increasing the system reliability, lower maintenance requirements and cost, and ability of working in hostile environments. Several speed estimation methods for the speed sensorless IM drives have been proposed and investigated. They can be classified into two categories: machine model-based schemes and signal injection-based schemes [8][9][10][11][12][13][14].Signal injection-based schemes use rotor slot harmonics, saturated, and leakage inductances for speed estimation by injecting high or low frequency signals. In [8][9][10], high frequency signal injection methods are introduced for speed estimation. A low frequency signal injection method for sensorless control of interior permanent magnet synchronous motor (IPMSM) drives is presented in [11]. These methods are insensitive to motor parameter variations and provide accurate speed estimation, especially at low speed [12]. However, they are very complicated to implement, strongly rely on motor designs and require special designs for specific motor drives [12][13][14]. Moreover, torque ripples and noises make them hard to be widely used in industry [14].Machine model-based schemes use the instantaneous values of machine stator voltages and currents to estimate the speed and flux linkage. These methods utilize the direct and quadrature (d-q) axis mathematical models to describe the machine behavior by ass...

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“…The method introduced in [5] is considered as the conventional method for DTC of IMs and many different modified methods for DTC have been developed in order to either cancel or diminish the influence of the above mentioned disadvantages. The modified DTC methods can be categorized in several groups with some common features [9]: methods with variable duty cycle, methods with space vector modulation (SVM), modified methods for the operation in the low speed range and model predictive control (MPC) methods. The advances in the DTC method and various adopted strategies are also presented in [10] and a review of the DTC method with improvements can be found in [11].…”

Section: Introductionmentioning

confidence: 99%

Modified predictive torque control method of induction machines for torque ripple reduction

Krušelj¹,

Sumina

2019

Automatika

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Direct torque control, model predictive control and field oriented control are control methods mostly used in high performance induction machine drives. In the direct torque control method, control variables are estimated from the stator variables, and the only parameter required is the stator resistance. The predictive torque control with horizon one has recently attracted much research attention but it requires the use of the induction machine speed, and both the stator and the rotor parameters, usually requires adjustment of the weighting factors, and has high computational burden. This paper proposes a modified predictive torque control method of induction machines. The estimated and predicted values are calculated from the stator variables, and the method uses the cost function without the weighting factor. When the two-level three-phase voltage source inverter is analyzed, it is shown that the predicted values should be calculated for three voltage vectors. The modified predictive torque control results in a better steady state performance regarding torque ripple in comparison with the conventional direct torque control and the predictive torque control methods. Simulation and experimental results for the main propulsion drive of the low-floor tram are presented in order to validate the effectiveness of the proposed method.

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Methods for direct torque control of induction machines

Cited by 4 publications

References 39 publications

Induction Motor Drive Direct Torque Control and Predictive Torque Control Comparison Based on Switching Pattern Analysis

Induction Motor Drive Direct Torque Control and Predictive Torque Control Comparison Based on Switching Pattern Analysis

Online Speed Estimation Using Artificial Neural Network for Speed Sensorless Direct Torque Control of Induction Motor based on Constant V/F Control Technique

Modified predictive torque control method of induction machines for torque ripple reduction

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