Direct Torque Control Approach Research Articles

Advanced direct torque control based on neural tree controllers for induction motor drives

This paper introduces a novel direct torque control approach based on the decision tree (T-DTC), employing artificial neural networks that are effectively trained to enhance accuracy and robustness. The main objective of T-DTC is the substantial reduction of flux and torque ripples inherent in the conventional DTC, ensuring effective control of the induction motor. The conventional hysteresis controllers for stator flux and electromagnetic torque are replaced by two advanced controllers named M5 Prime model trees. Additionally, the traditional switching table is substituted with a novel decision tree table utilizing the classifier algorithm 4.5. The effectiveness of the proposed T-DTC strategy is demonstrated through simulation in MATLAB/Simulink and validated in real-time using an HIL platform based on OPAL-RT OP 5600 and Virtex 6 FPGA ML605. The results obtained demonstrate a notable improvement compared to existing techniques in the literature.

A novel UEBASC‐qZSI‐based BLDC motor drive with modified DTC for EV application

SummaryAt present taking into account the situation of the environment and the growing demand of fossil fuels, electric vehicles (EVs) are a highly promising option for the transportation system. Many manufacturers of electric vehicles employ BLDC motors as the vehicle's driving component. In contrast to the many advantages that BLDC motors offer, one of the major drawbacks of employing these motors is the production of relatively high distortion in electromagnetic torque that is created by commutation. This distortion in torque has an effect on the vehicle's performance. In this proposed work a BLDC motor is powered by a cutting‐edge, highly gained q‐ZSI Ultra‐Extended Boost Active Switch Controlled Based Quasi Z‐source Inverter, or UEBASC‐qZSI. In the aforementioned drive, the torque distortion is minimized with the use of a modified direct torque control approach. With the aid of this UEBASC‐qZSI, the efficiency of EVs can be improved, and the overall safety of the driving cycle is also increased. Any vehicle's efficiency can be enhanced with the help of this UEBASC‐qZSI, and the overall safety of the overall system can also be improved. To validate the efficacy of the system, a Simulink model is developed in the MATLAB platform. Also, a hardware prototype model is developed for experimental authentication. The modeling and investigational findings demonstrate that the proposed system has significantly reduced the torque ripple while obtaining the necessary input dc bus voltage.

Enhanced Induction Motor Control Using Deep Reinforcement Learning and PWM with DTC

This article presents an enhanced approach for controlling an induction motor, combining Deep Reinforcement Learning (DRL), Pulse Width Modulation (PWM), and a Speed Controller. Flux, torque, and ripples in the stator current are problems with the traditional Direct Torque Control (DTC). A 12-sector DTC technique is suggested to overcome these problems and get rid of torque ripple. In order to reduce the ripples in the stator current vectors brought on by white noise, an enhanced Q-learning-based Kalman filter (IQL-KF) is also employed. The rotation speed and flux control are achieved using fuzzy VIKOR. Simulation data with various load conditions, processing, and noise power covariances are utilized to estimate the effectiveness of the suggested technique. Comparison with the typical DTC approach demonstrates that the suggested method outperforms in transient situations, as assessed by the integrated time absolute error performance index, undershoot, and ripple of crucial parameters.

Direct torque control of electric vehicle drives using hybrid techniques

Permanent magnet synchronous motors (PMSM) have the capability of delivering a high torque-to-current ratio, better efficiency and low noise. Because of the above-mentioned factors, PMSMs are commonly employed in variable speed drives, especially in electric vehicle (EV) applications. Without the usage of electromechanical devices, the conventional direct torque control (DTC) can control the speed and torque of PMSM. DTC is highly efficient, fast-tracking and provides smooth torque while limiting its ripple during transient periods. There are many benefits to using a DTC-controlled PMSM drive, including quick and reliable torque reaction, high-performance control speed, and enhanced performance. This research examines the use of the DTC approach to enhance the speed and torque behavior of PMSM. The jellyfish search optimizer (JSO) is used to adjust the DTC's responsiveness and tailor the controller's best gains. In order to train the adaptive neuro-fuzzy inference system (ANFIS) controller, JSO data are utilized. The simulation outcomes demonstrate that the proposed JSO-ANFIS controller achieves a minimal torque ripple of 0.26 Nm and preserves the speed with a harmonic error of 1.21% while contrasted to existing methods.

Developed an Improved Fractional Ordered Darwinian Particle Swarm Optimization Using Fuzzy Logic Controller to Improve the Performance Measures on E-Vehicle

This study introduces the improved fractional ordered Darwinian particle swarm optimization (IFODPSO) method combined with fuzzy logic controllers to optimize motor performance. By utilizing direct torque control (DTC) techniques controlled by IFODPSO, the system achieves quick response times and instantaneous torque generation. The research addresses the optimization of motor performance using the IFODPSO approach for combination with fuzzy logic controllers. The specific problem being addressed is the control of torque in motor applications. The scope of the research includes comparing the performance of the IFODPSO-FLC approach with common field-oriented control (FOC) as well as DTC approaches. The significance of the results attained is noteworthy as the IFODPSO-FLC approach demonstrates promising outcomes in terms of torque control compared to traditional FOC and DTC techniques. Additionally, the proposed PI-fuzzy opposition estimation helps improve system efficiency at low speeds by compensating for variations in stator resistance. The combination of fuzzy logic controllers and Darwinian particle swarm optimization of fractional order approaches presents a novel and efficient solution. The results are evaluated using MATLAB-Simulink, and the obtained performance demonstrates the potential for successful motor control applications.

Performance enhancement of direct torque control induction motor drive using space vector modulation strategy

Purpose. The main objective of this work is to demonstrate the advantages brought by the use of space vector modulation technique in the direct torque control of the induction motor. To achieve this purpose, two different direct torque control approaches (with space vector modulation) are proposed and studied from a comparative aspect with each other and with the conventional direct torque control. The novelty of this work consists in the employment of an Integral-Proportional (IP) speed controller in the two proposed direct torque control approaches and a more in-depth evaluation for their performance mainly the switching frequency of inverter semiconductor components and motor torque ripples. Methods. Two different direct torque control approaches that use the space vector modulation strategy and/or fuzzy-logic control, are described in detail and simulated with IP speed controller. The simulation experiments are carried out using Matlab/Simulink software and/or fuzzy-logic tools. Results. Practical value. Comparison results show that the two proposed direct torque control structures (with space vector modulation) exhibit a large reduction in torque ripples and can also avoid random variation problem of switching frequency (over a wide range of speed or torque control). On the other hand, the use of IP speed regulator ensured good dynamic performance for the drive system as well as considerably minimized peak overshoot in the speed response. Practically all of these benefits are achieved while retaining the simplicity and the best dynamic characteristics of the classical direct torque control, especially with the modified direct torque control approach in which the design or implementation requires minimal computational effort.

An improved look-up table-based direct torque control for permanent magnet synchronous generator using Vienna rectifier

This paper presents an improved look-up table-based direct torque control of the permanent magnet synchronous generator using Vienna rectifier for a wind energy conversion system. A stator voltage model for the system was developed to allow an in-depth analysis of the effect of the switching vectors for the Vienna rectifier on the performance of direct torque control. The developed generator model is dedicated to reducing the complexity of look-up table development. Subsequently, an improved look-up table was designed to enhance the overall performance of the permanent magnet synchronous generator in both torque and stator flux ripples, along with the investigation of the computation delay compensation for the digital implementation. The performance was first investigated through Matlab / Simulink before being further validated using a small-scale prototype and a wind turbine emulator. Both simulation and experimental results obtained were compared with the existing direct torque control approach to verify the effectiveness of the proposed system for wind energy extraction. The results show that the enhanced look-up table generates lower ripples in torque and stator flux while improving their reference tracking, especially during unbalanced DC load scenarios. This achievement can be clearly seen by the lower discrepancy percentage between the reference and actual value in the generated torque and stator flux by 6.35% and 0.47%, respectively.

MRAS-Based Super-Twisting Sliding-Mode Estimator Combined With Block Control and DTC of Six-Phase Induction Motor for Ship Propulsion Application

This article presents the block control (BC) approach combined with the direct torque control (DTC) through employing a model reference adaptive system (MRAS) based on the super-twisting sliding-mode (STSM) speed estimator of a six-phase induction motor (6PIM) for ship propulsion application. The BC is a robust speed controller that is employed for regulating the 6PIM speed. The closed-loop approach is designed in an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">αβ</i> -reference frame as well as is based on the linearization BC approach. The flux estimator is based on the super-twisting technique that is a second-order sliding-mode approach. This observer is utilized as a reference model throughout the MRAS-based speed estimator for discarding the chattering problem of the conventional sliding-mode technique. Two STSM controllers are used for controlling the torque along with the stator flux and improving the drive system performance throughout external load disruptions. Furthermore, the STSM estimator estimates the torque and stator flux in a robust response with discarding the chattering problem. The proposed MRAS-based STSM speed estimator performance is investigated experimentally for the 750-W 6PIM as well as compared with the traditional DTC approach throughout various speed references, load disruptions, and low-speed command/low loading torque conditions.

WITHDRAWN: Intelligent Fuzzy controller based N-T control of 5Φ SRM

Abstract The usage of outdated energy devices contributing to environmental pollution is becoming ever more concerned. The industry is forced to find new ideas without lowering demands. Motors are not very effective in the white good and other manufacturing applications of today. The brushed Electric engine comes here. However it is maintained highly and has a low speed due to the brushes used in elements. In recent years, the Brushless DC engine was successfully used in the electronic switching process and this motor retains the location sensors necessary for motor operation and magnet costs as main engine components. The 5μ switched reticence motor (SRM), including easy construction, high reliabilities and low cost, has a range of desired features. However the huge torque ripples, the output torque and the magnetization features are extremely non-uniform and the noise is high. Several experiments were carried out using the Direct Torque Control (DTC) technique to minimize torque ripple for SRM. This project focuses on the implementation of Five-Phase 10/8 SRM Direct Torque Controls (DTC), which provides many advantages over traditional voltage control and current chopping mode controls including convenient algorithms, lower torque and immediate torque response. The 5-phase 10/8 SRM DTC approach is proposed. The engine output is shown in Matlab/Simulink through computer simulation. The result is then evaluated by comparing the corresponding results with a 5-phase 10/8 engine response.

PI Regulator-Based Duty Cycle Control to Reduce Torque and Flux Ripples in DTC of Six-Phase Induction Motor

In this paper, a proper duty cycle control method is proposed to reduce torque and flux ripples and harmonic loss in direct torque control (DTC) of six-phase induction machine (6PIM). Three different methods are proposed to improve the performance of switching table DTC for 6PIM. First, by the suitable selection of two vectors in each sampling period, the harmonic amplitude is significantly decreased, but the torque and flux ripples are still large. Then, the abovementioned method is combined with duty cycle control technique and the torque and flux ripples and current harmonics are significantly reduced. In addition, the switching frequency is also reduced by selecting the suitable voltage vector in each sampling period. Finally, a simple control method is suggested to calculate the duty ratio of voltage vectors independently of machine parameters. Although neglecting the one-step delay makes performance of the final technique similar to the previous one, considering this delay in real conditions shows the following advantages for the final method: less torque and flux ripples, less current harmonics, simplicity, and constant switching frequency. Despite these improvements, all duty cycle-based DTC approaches (duty-DTC and PI-duty-DTC) increase the inverter switching losses. The simulation and experimental results presented in this paper verify the performance advantages of the proposed methods.

A comparative experimental study of direct torque control based on adaptive fuzzy logic controller and particle swarm optimization algorithms of a permanent magnet synchronous motor

Direct torque control (DTC) of permanent magnet synchronous motor (PMSM) drives is receiving increasing attention due to important advantages, such as fast dynamic and low dependence on motor parameters. However, conventional DTC scheme, based on comparators and the switching table, suffers from large torque and flux ripples. In this paper, two intelligent approaches are proposed in order to improve DTC performance. The first approach is based on two adaptive fuzzy logic controllers (AFLC). The first AFLC replaces the conventional comparators and switching table and the second AFLC adjusts in real time the outer loop PI parameters. In the second approach, particle swarm optimization (PSO) is used as another alternative to adjust the PI parameters. Simulation and experimental results demonstrate the effectiveness of the proposed intelligent techniques. Besides, the system associated with these techniques can effectively reduce flux and torque ripples with better dynamic and steady state performance. Quantitatively, PSO-based DTC approach reduces greatly flux and torque ripples. Further, PSO-based approach maintains a constant switching frequency which improves the PMSM drive system control performance.

Model Predictive Direct Torque Control With Finite Control Set for PMSM Drive Systems, Part 2: Field Weakening Operation

The direct torque control approach called model predictive direct torque control (MP-DTC) is extended to field-weakening operation in this research. The controller is of the finite control set (FCS) type, which takes the discrete states of the voltage source inverter (VSI) into account. Each sampling period, the future behavior of the plant is predicted and inputs (voltage vectors) are selected using an optimization criterion, i.e., a cost function. Optimization, however, depend on the operation region. Maximum torque per ampere (MTPA) tracking for high electrical efficiency is aimed below rated speed, operation off the MTPA trajectory is necessary for obtaining field-weakening. In this work, a cost function is designed, which is suitable for operation at high speeds without penalizing operation below rated speed. MP-DTC is applied to permanent magnet synchronous machine (PMSM) drive systems. High control performances, i.e., dynamics, is obtained without increasing the switching frequency nor reducing significantly the torque quality. This feature is interesting above all for high power applications. The proposed control strategy has been evaluated on a small-scale (PMSM) drive system with two-level VSI for demonstration showing promising results.

Direct Torque Control Using Fuzzy and Neural as Switching Vector Selector for Doubly Fed IM

The conventional Direct Torque Control approach has some drawbacks such as high torque ripple and switching frequency, which is varying with speed, load torque and the selected hysteresis bands, this paper discuss the application of neural network and fuzzy logic on DTC of Doubly fed induction motor DFIM, the proposed techniques having the advantages of low torque and flux ripples. Simulation results emphasize the good performance of the fuzzy and neural techniques.

A new approach to direct torque control of induction motor drives for constant inverter switching frequency and torque ripple reduction

In this paper, a new approach to the direct torque control (DTC) of induction motor drives is presented. In comparison with the conventional DTC methods, the inverter switching frequency is constant and is dramatically increased, requiring neither any increase of the sampling frequency, nor any high frequency dither signal. The well-developed space vector modulation technique is applied to inverter control in the proposed DTC-based induction motor drive system, thereby dramatically reducing the torque ripple and speed ripple. As compared to the existing DTC approach with constant inverter switching frequency, the presented new approach does not invoke any concept of deadbeat control, thereby dramatically reducing the computations. Experimental results are illustrated in this paper confirming that the proposed DTC method has the above-mentioned features even at the low speed range down to /spl plusmn/1 r/min.