Torque Control Of Induction Machine Research Articles

Field programmable gate array hardware in the loop validation of fuzzy direct torque control for induction machine drive

Introduction. Currently, the direct torque control is very popular in industry and is of great interest to scientists in the variable speed drive of asynchronous machines. This technique provides decoupling between torque control and flux without the need to use pulse width modulation or coordinate transformation. Nevertheless, this command presents two major importunities: the switching frequency is highly variable on the one hand, and on the other hand, the amplitude of the torque and stator flux ripples remain poorly controlled throughout the considered operating speed range. The novelty of this article proposes improvements in performance of direct torque control of asynchronous machines by development of a fuzzy direct torque control algorithm. This latter makes it possible to provide solutions to the major problems of this control technique, namely: torque ripples, flux ripples, and failure to control switching frequency. Purpose. The emergence of this method has given rise to various works whose objective is to show its performance, or to provide solutions to its limitations. Indeed, this work consists in validation of a fuzzy direct torque control architecture implemented on the ML402 development kit (based on the Xilinx Virtex-4 type field programmable gate array circuit), through hardware description language (VHDL) and Xilinx generator system. The obtained results showed the robustness of the control and sensorless in front of load and parameters variation of induction motor control. The research directions of the model were determined for the subsequent implementation of results with simulation samples.

Direct torque control of induction machine fed by 5-level flying capacitor inverter with active balancing strategy for electric vehicle application

Direct torque control of induction machine fed by 5-level flying capacitor inverter with active balancing strategy for electric vehicle application

Nonlinear Modeling, Identification, and Optimal Feedforward Torque Control of Induction Machines Using Steady-State Machine Maps

A novel but simple machine map-based modeling, identification, and optimal feedforward torque control (OFTC) approach for induction machines (IMs) is presented. It is based on, first, a generic, nonlinear transformer-like machine model considering nonlinear flux linkages (with magnetic saturation and cross coupling) and iron losses in the stator laminations in a novel, arbitrarily rotating but unique, robust, and reproducible ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$d,q$</tex-math></inline-formula> )-reference frame; second, a holistic machine identification procedure, which evaluates steady-state measurements over a grid of ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$d,q$</tex-math></inline-formula> ) stator currents and produces temperature and frequency dependent machine maps, for example, flux linkages, torque, iron resistance, and efficiency; and third, a numerical offline optimization and extraction of different OFTC look-up tables (LUTs) for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">optimal</i> current reference generation depending on reference torque and electrical frequency (and temperature). During the identification, stator winding temperature and electrical stator frequency of the IM are kept constant by an intelligent temperature and the speed control system. The presented measurement results for a squirrel-cage IM confirm that compared to constant flux operation or scalar V/Hz control, efficiency can be increased particularly in part-load operation by up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{7} \,\%$</tex-math></inline-formula> by Maximum Torque Per Losses minimizing copper <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">and</i> iron losses.

Artificial intelligent techniques based on direct torque control of induction machines

The direct torque control (DTC) system, which is based on induction machine drive is a developed and simple control method. It allows high dynamic performance with very simple hysteresis control scheme; However, its disadvantages are high current, torque, and flux ripple. In this paper, DTC of induction machine drive has been improved by using the applications of artificial intelligence (AI) approaches to reduce the current, torque, and flux ripples and also get better performance of the machines. At the conclusion of this study, the outcomes of traditional DTC and artificial intelligent methods are compared. By the program MATLAB/SIMULINK, the modeling and simulation results of the DTC system for induction machine (IM) have been proposed.

VHDL design and FPGA implementation of direct torque control for induction machines

This paper presents a VHDL design and an FPGA implementation of a direct torque controller (DTC) used to order induction machines (IM). The use of FPGA at high sampling frequency reduces the torque ripple while maintaining the classical DTC control structure. We have adopted a modular approach, by dividing the global entity into a set of elementary blocks designed and implemented separately. The performances of this command are to reduce the torque ripple to 0.01 Nm and the flux ripple to 0.01 wb with a circuit implementing DTC control of 3,256 LEs of complexity and 64 latency clock cycles. To evaluate the performance of our FPGA circuit implementing DTC controller, we have performed a co-simulation platform based on MATLAB/Simulink and Modelsim programs. MATLAB/Simulink was used to simulate the dynamics of the induction machine associated with its inverter and the proposed DTC control strategy was executed under the modelsim software using the VHDL fixed point. We have operated our circuit FPGA in the loop in a speed variation platform of induction machine and we have obtained the following performances: A zero overrun, response time at speeds of 300 ms and a zero static error as required in the specifications.

Observer-Predictor-Based Predictive Torque Control of Induction Machine for Robustness Improvement

In the finite control set model predictive control (FCS-MPC) of induction motors, the mismatched motor parameters will inevitably lead to model predictive errors, and then reduce the control performance. At present, the evaluation methods of the prediction errors caused by mismatched parameters and of improving robustness have become the research hotspots of FCS-MPC of induction motors. In this article, an observer-predictor-based predictive torque control of induction machine is proposed in order to improve the prediction accuracy. In the stator current prediction equation, this article abandons the traditional open-loop prediction equation and proposes a closed-loop stator current prediction equation. In the stator flux prediction equation, this article abandons the traditional stator flux prediction model based on voltage model, and proposes a discrete hybrid prediction model combining voltage model and current model, where the proportional-integral regulator is used to switch the voltage model to the current model. Second, the stability and parameter design principles of the closed-loop stator current prediction model and the closed-loop stator flux prediction model are analyzed. Finally, the experimental results show that the proposed method is superior to the traditional method in dynamic performance, steady-state performance, and parameter robustness.

New adaptive hysteresis band width control for direct torque control of induction machine drives

This paper presents a new adaptive hysteresis band control approach used in direct torque control (DTC) of the induction motor (IM) drives with the switching tables for the generation of PWM signals. Constant Hysteresis Direct torque control (CHB-DTC) method used the torque and stator flux errors to generate the stator voltage reference and frequency vectors for controlling the three-phase induction motor. The CHB-DTC gives better torque transient performance but it has large steady state ripples. To reduce torque and stator current ripples in CHB-DTC controlled induction motor drives a new adaptive hysteresis band control (AHB) approach is proposed, where the hysteresis band is adapted in real time with the stator flux and torque errors variation, instead of fixed bandwidth. Both classical CHB-DTC method and the proposed adaptive hysteresis band DTC (AHB-DTC) fed three induction motor have been simulated using Matlab/Simulink. The simulation results at different operating conditions over a wide speed range demonstrate the validity, effectiveness, and feasibility of the proposed scheme. The measurements showed that torque ripples were significantly decrease with the new AHB-DTC technique and better speed response in step up or down compared to the CHB-DTC.

Grey Relational Analysis-Based Objective Function Optimization for Predictive Torque Control of Induction Machine

This article presents grey relational analysis (GRA)-based objective function optimization in predictive torque control (PTC) for induction machine. Selection of appropriate weighting factor in the objective function is one of the key aspects in the implementation of PTC. However, selection of suitable weighting factor in the objective function is a heuristic task. To address this issue, GRA method is implemented for the objective function optimization. In this approach, single-objective function is modified into two independent objective functions for stator flux and torque. A grey relational grade is used to identify the suitable control action in each sampling. A MATLAB/Simulink model is developed to validate the control algorithm under various operating conditions of the drive, and corresponding results are compared with experimental results.

Enhanced Performance of Constant Frequency Torque Controller–Based Direct Torque Control of Induction Machines with Increased Torque-Loop Bandwidth

Constant frequency torque controller-based direct torque control (CFTC-DTC) is emerging as a powerful control strategy for a high-performance control of alternating-current motor drives. Compared to DTC, the CFTC-DTC has less torque and flux ripples with a fixed switching frequency. Nevertheless, it has a limitation of the torque-loop bandwidth, as it uses the sampling frequency from a digital signal processor to generate a triangular-based carrier. The switching frequency of the control system is determined by the carrier frequency of the CFTC. The frequency limitation of CFTC leads to sector-flux droop, which causes a distortion in the motor phase current and aggravation in the torque and speed waveforms at low speed regions. In this article, we propose a modification of the frequency carriers of the CFTC-DTC of induction motors to increase the switching frequency and torque loop bandwidth by replacing the triangular-carrier-based waveform with a ramp-carrier-based waveform. The proposed method is verified by simulation and experimental results showing its excellent performances in steady- and transient-state operations.

Speed-Sensorless Dual Reference Frame Predictive Torque Control for Induction Machines

In finite control set predictive torque control (FCS-PTC), mismatched parameters will lead to the electromagnetic torque prediction error. To solve the aforementioned problem, this paper proposes feedback-correction-based dual reference frame predictive torque control for induction machines, abbreviated as DRF-PTC. First, a DRF flux observer is proposed, which abandons a traditional model reference adaptive observer with rotor speed as adaptive variable. The proposed flux observer decouples the flux observation and the speed estimation and improves the estimation accuracy of flux linkage and rotor speed. Second, a DRF-PTC is proposed to eliminate the effect of speed estimation error on torque prediction. For the influence of mismatched parameters, a correction term is incorporated in double reference frame torque prediction equations, in which the correction term is derived from the correction term of the proposed flux observer. Finally, the proposed DRF-PTC in this paper is verified on the experimental platform of an induction machine. Experimental results show that the proposed DRF-PTC has excellent performance in speed estimation and electromagnetic torque prediction, compared with the traditional FCS-PTC.

Improvement of Flux Regulation with Adaptive PI Controller and DTHB based Direct Torque Control of Induction Machine

This paper presents an adaptive PI based two control strategies of Dynamic Hysteresis Torque Band (DHTB) for improving flux regulation at low speed and zero speed in lookup table based Direct Torque Control (DTC) of an Induction Machine (IM). This is achieved by varying the band value of torque dynamically but it is limited with flux error range. With the conventional HTB based DTC, at low and zero speed, the regulation of flux will not be good. To overcome this drawback, a small alteration in the structure is done, i.e., DTHB, thus retaining the simplicity of DTC algorithm. The performance is verified by varying the speed at low values. At low speeds of IM, the flux regulation and the speed is improved with adaptive PI controller based DHTB-II compared to DTC with DHTB-I and DHTB-II.

Design and Implementation of Luenberger Model-Based Predictive Torque Control of Induction Machine for Robustness Improvement

This letter proposes a Luenberger model-based predictive torque control (LM-PTC) of induction machine to compensate prediction error caused by mismatched parameters. In the traditional predictive torque control (T-PTC), stator current, stator flux vector, and electromagnetic torque are predicted in one sampling period by open-loop prediction model, which will inevitably lead to prediction error by mismatched parameters, first. Inspired by the idea of closed-loop Luenberger observer, in the torque and flux prediction, the feedback correction part is introduced into prediction equations for LM-PTC. Second, the steady prediction errors of T-PTC and LM-PTC are, respectively, analyzed with mismatched parameter. Finally, the proposed LM-PTC is verified by the comparison experiments including dynamic-state, transient-state, and steady-state experiments.

Imposed Switching Frequency Direct Torque Control of Induction Machine Using Five Level Flying Capacitors Inverter

Imposed Switching Frequency Direct Torque Control of Induction Machine Using Five Level Flying Capacitors Inverter

Parallel Predictive Torque Control for Induction Machines Without Weighting Factors

Finite control set model predictive control (FCS-MPC) calculates torque and flux tracking errors via a cost function that is used for selecting the optimal vector. Compared with field oriented control, FCS-MPC has the merit of a faster dynamic performance because it eliminates both pulsewidth modulation and inner proportion-integration controllers. However, the weighting factor for modifying torque and flux terms must be tuned in accordance with varying operating conditions; this is an area in which further research is needed. In this paper, a parallel predictive torque control (PPTC) with predefined constraints is proposed as a solution for this problem. The PPTC method optimizes torque and flux terms simultaneously, and switching-state candidates are then selected in an adaptive mechanism. The key feature is that torque and flux tracking errors are constrained within the initial boundaries. The proposed PPTC is compared with the state-of-the-art predictive torque control (PTC) method. Both simulation and experimental results confirm that the proposed method, which has no weighting factor, achieves an even better dynamic performance and robustness than the conventional PTC.

Direct torque control of induction machine drive based on sliding mode controller and a stator resistance compensator with a new hybrid observer

This paper presents a sensorles direct torque control (DTC) based on sliding mode controller approach (SMC) applied to an induction machine (IM) drive. The DTC is one of the excellent strategies. It aims to provide decoupled control of torque and flux. However, his main problem is the high torque and flux ripples of the devices. Its drawback was rectified with the use a control scheme that combined with SMC strategy. The rotor speed estimation is done by an observer using the model reference adaptive system (MRAS) technique whereas the nonlinear sliding mode observer (SMO) is used to get the rotor flux. The main aim is to achieve a robust and efficient control, which will allow us to test and evaluate the performance of the proposed observer, combined with sensorless control of the IM. The simulations results show the effectiveness of the proposed sensorless control scheme.

Direct torque control of induction machine drive based on sliding mode controller and a stator resistance compensator with a new hybrid observer

This paper presents a sensorles direct torque control (DTC) based on sliding mode controller approach (SMC) applied to an induction machine (IM) drive. The DTC is one of the excellent strategies. It aims to provide decoupled control of torque and flux. However, his main problem is the high torque and flux ripples of the devices. Its drawback was rectified with the use a control scheme that combined with SMC strategy. The rotor speed estimation is done by an observer using the model reference adaptive system (MRAS) technique whereas the nonlinear sliding mode observer (SMO) is used to get the rotor flux. The main aim is to achieve a robust and efficient control, which will allow us to test and evaluate the performance of the proposed observer, combined with sensorless control of the IM. The simulations results show the effectiveness of the proposed sensorless control scheme.

Improvement of Torque Capability of Direct Torque Control of Induction Machines

A control strategy for overmodulation operation of direct torque control hysteresis based in induction machine is proposed. The strategy is to extend the constant torque region as well as to improve the torque capability. The proposed overmodulation strategy is different to SVM based system where the reference stator voltage is available. In order for DTC hysteresis based system to be able to achieve that, several modifications have been applied so that the proposed overmodulation can be achieved by gradually transforming the PWM voltage waveform to six-step mode. Simulated results were provided to demonstrate the effectiveness of the strategy.

An Improved Model Predictive Direct Torque Control for Induction Machine Drives

The conventional model predictive direct torque control (MPDTC) method uses all of the voltage vectors available from a two level voltage source inverter for the prediction of the stator flux and stator current, which leads to a heavy computational burden. This paper proposes an improved model predictive direct torque control method. The stator flux predictive controller is obtained from an analysis of the relationship between the stator flux and the torque, which can be used to calculate the desired voltage vector based on the stator flux and torque reference. Then this method only needs to evaluate three voltage vectors in the sector of the desired voltage vector. As a result, the computational burden of the conventional MPDTC is effectively reduced. The time delay introduced by the computational time causes the stator current to oscillate around its reference. It also increases the current and torque ripples. To address this problem, a delay compensation method is adopted in this paper. Furthermore, the switching frequency of the inverter is significantly reduced by introducing the constraint of the power semiconductor switching number to the cost function of the MPDTC. Both simulation and experimental results are presented to verify the validity and feasibility of the proposed method.

High-Speed Computation using FPGA for Excellent Performance of Direct Torque Control of Induction Machines

The major problems in hysteresis-based DTC are high torque ripple and variable switching frequency. In order to minimize the torque ripple, high sampling time and fast digital realization should be applied. The high sampling and fast digital realization time can be achieved by utilizing high-speed processor where the operation of the discrete hysteresis regulator is becoming similar to the operation of analog-based comparator. This can be achieved by utilizing field programmable gate array (FPGA) which can perform a sampling at a very high speed, compared to the fact that developing an ASIC chip is expensive and laborious.

Predictive Control of an Induction Machine Fed by a Matrix Converter With Increased Efficiency and Reduced Common-Mode Voltage

Predictive control represents an optimization-oriented alternative for the control of power converters and drives. Predictive torque control of induction machines has been shown to achieve excellent initial results. The objective of this paper is to help develop this promising control approach by introducing new elements to improve its performance. The resulting algorithm improves the efficiency of the converter from 91.1% to 92.6% and achieves a common-mode voltage mitigation of 50%, compared to the basic control method. A tradeoff is observed in the power quality. The algorithm gives the designer the ability to select the best operating point for each particular application and to optimize the converter's performance. Experimental results are presented to validate the proposals.