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Improved Direct Torque Control of Doubly Fed Induction Motor Using Space Vector Modulation

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Improved Direct Torque Control of Doubly Fed Induction Motor Using Space Vector Modulation Received: December 22, 2020. Revised: February 26, 2021. 177 Improved Direct Torque Control of Doubly Fed Induction Motor Using Space Vector Modulation Mohammed El Mahfoud1* Badre Bossoufi1 Najib El Ouanjli2 Mahfoud Said2 Mohammed Taoussi2 1Laboratory of engineering Modeling and Systems Analysis, SMBA University Fez, Morocco 2Technologies and Industrial Services Laboratory, SMBA University Fez, Morocco * Corresponding author’s Email: [email protected] Abstract: This research paper deals with the improved direct torque control (DTC) of a doubly fed induction machine (DFIM) operating in motor mode. The conventional DTC is a powerful tool to ensure robustness and good torque dynamics. However, the variable switching frequency as well as the presence of torque and flux ripples due to the use of hysteresis controllers are the major drawbacks of this strategy. For this purpose, the control by space vector Modulation (SVM) is developed to improve DTC performance, by replacing hysterisis controllers by PI controllers to reduce electromagnetic flux ripple and torque ripple in order to minimize mechanical vibration and acoustic noise while maintaining the benefits of DTC control. The proposed control algorithm is simulated and tested in MATLAB/Simulink. A comparative analysis between this technique and conventional DTC is carried out, highlighting the efficiency of the proposed improvement approach. The performance indexes and comparative results show the effectiveness of the proposed control in reducing torque ripple and stator and rotor flux ripple by up to 43%, 42% and 31%, respectively, resulting in Total Harmonic Distortion (THD%) 61% lower, in addition the switching frequency is controlled, and the Rejection Time is improved by more than 76%. Keywords: Direct torque control, Space vector modulation, Doubly fed induction motor, Inverter, Switching table. machine. The invention of the Field Oriented Control 1. Introduction (FOC) algorithm in the 1972s has revived the applications of high-performance variable speed Over the past few decades, drive systems have drives [6]. FOC provides decoupling between torque been used regularly in a number of applications, such and machine flux and makes the DFIM like a DC as marine propulsion, rail traction, pumping and machine [7]. This decoupling gives fast torque electric vehicles [1], as well as in hydroelectric and response, a wide speed control range and high wind power conversion systems [2]. Among these efficiency over a wide load variation range. But this drives, the Doubly Fed Induction Machine (DFIM) control presents a high sensitivity to the parametric presents great robustness, high efficiency, reliability variations of the machine and a great complexity and longevity. Increasing interest is being given to caused by the presence of coordinate transformations DFIM [3]. and the use of several control variables [8]. In Despite its advantages, yet DFIM is still opposition to FOC, Direct Torque Control (DTC) is complicated and difficult to control particularly when known by its simple decoupled scheme which allows good performance is required in various operating controlling the electromagnetic flux and torque. DTC conditions [4]. This is because DFIM is a non-linear offers advantages such as fast response and less system, multivariable, time-varying and subject to dependence on machine parameters. In addition, it perturbations. In addition, some of its state variables, does not require any transformation of coordinates or like flux are not measurable [5]. These constraints current regulator loops [5]. The DTC has been made require more powerful algorithms to control this International Journal of Intelligent Engineering and Systems, Vol.14, No.3, 2021 DOI: 10.22266/ijies2021.0630.16 Received: December 22, 2020. Revised: February 26, 2021. 178 by TAKAHASHI [9]. It is based on the direct this purpose, the DTC-SVM control strategy (without application of a control sequence to the switches of the use of hysteresis controllers) is recommended, in the voltage inverter placed before the induction order to obtain a selection table allowing the best machine {Formatting Citation}. The choice of this choice of the voltage vector sequence to be applied to sequence is based on the use of a switching table and the motor, while respecting the constraints on flux hysteresis controllers which have the role of and electromagnetic torque [15]. This allows us to controlling and regulating the electromagnetic torque directly control the torque without using hysteresis and flux of the machine. However, this technique controllers and therefore a significant reduction in the causes [5]: ripple of the control quantities as well as a control of • Undesirable flux and torque ripples. the switching frequency. The behavior of the DFIM • High and uncontrollable switching frequency. controlled by DTC-SVM is evaluated and compared • Acoustic noise and mechanical vibration of the with that of the conventional DTC to highlight the motor. effectiveness of the proposed improvement approach. • Problems at low speeds. This article is divided into six major sections as In recent years, research has been conducted to follows: Section 2 presents a brief modeling of the overcome the drawbacks previously mentioned [1, doubly fed induction machine. Section 3 is devoted 11-13]. In [11], A DTC improved by the sliding mode to the study of the direct torque control of the DFIM command is studied. This technique provides a good and the explanation of the principle of flux control, improvement and guarantees robustness against electromagnetic torque and the general structure with external disturbances and parametric variations of the two switch tables. The modifications made to the motor, but there is the problem of the chattering DTC control and the principle of space vector phenomenon which is degrading the performance of modulation is described in section 4. Section 5 shows the system. The paper [1] presents direct torque the results of the simulation of the proposed control control of a DFIM by a PI controller tuned using a techniques, the comparative study between these two genetic algorithm. the GA is a particular class of control structures is given and discussed. Finally, evolutionary algorithms using techniques inspired by section 6 presents the conclusion and perceptual evolutionary biology, which has become a tool for the considerations. optimization of nonlinear problems, the major advantage of GA focuses on the optimization of the 2. Modeling of the DFIM variable parameters of the system, but which requires The system studied is composed of a doubly a large number of iterations for the system to fed induction motor associated with two variable converge towards optimal solutions. Another method frequency power supply systems; one is connected to of improving DTC is proposed in [12]. New the stator and the other one to the rotor [16]. Fig. 1 switching tables are developed using fuzzy logic shows the DFIM power supply scheme. controllers (FLC) to control the switching frequency. The stator and rotor voltage of DFIM in Furthermore, the authors of [13] are proposed another synchronously rotating reference frame (훼, 훽) can be structure of DTC based on the artificial neural expressed as [17]: network (ANN) to have fast responses of flux and torque with less distortion. However, these last two 푣푠훼 푅 0 0 0 푖푠훼 solutions present a high complexity of design and 푠 푣푠훽 0 푅 0 0 푖푠훽 implementation. For the FLCs, The design and choice [ ] = [ 푠 ] + 푣푟훼 0 0 푅 0 푖 of structure is difficult due to the lack of a clear 푟 푟훼 푣푟훽 0 0 0 푅푟 [푖푟훽] methodology. These techniques of artificial 휓 0 intelligence are not recommended for optimizing 푠훼 휓 0 excessively complex or very large problems, and 푑 푠훽 푑휃 [−휓 ] (1) requires much time to fine tune all parameters. 푑푡 휓푟훼 푑푡 푟훽 Our contribution in this work consists of [휓푟훽] 휓푟훼 proposing an improvement of the performances of the classical DTC control for a DFIM operating in motor mode, while keeping its advantages. They are as The expression of stator and rotor flux in diphase follows: robustness, simplicity and good speed reference frame (훼, 훽): tracking. The integration of the SVM to the classical DTC is a very attractive solution to guarantee an optimal regulation of the motor under study [14]. For International Journal of Intelligent Engineering and Systems, Vol.14, No.3, 2021 DOI: 10.22266/ijies2021.0630.16 Received: December 22, 2020. Revised: February 26, 2021. 179 3.2 Application of DTC control to the DFIM The control must always be asynchronous so at too able to regulate both stator and rotor flux; this means adjusting the torque supplied by the DFIM [12]. The flux expressions are: 푡 휓푠(푡) = ∫ (푉푠 − 푅푠퐼푠)푑푡 + 휓푠0 { 0 (5) ( ) 푡 휓푟 푡 = ∫0 (푉푟 − 푅푟퐼푟)푑푡 + 휓푟0 Figure.1 Power system of the DFIM The terms 푅푠퐼푠 and 푅푟퐼푟 are considered negligible in front of the voltages 푉푠and 푉푟. During a 휓푠훼 sampling period Te, the logic control states (푆퐴, 푆퐵 휓푠훽 = and 푆퐶) remain fixed. Thus, Eq. (5) becomes: 휓푟훼 [휓푟훽] 훥휓 = 휓 (푘 + 1) − 휓 (푘) = 푉 푇 { 푠 푠 푠 푠 푒 (6) 퐿 0 푀 푐표푠 휃 −푀 푠푖푛 휃 푖푠훼 ( ) ( ) 푠 훥휓푟 = 휓푟 푘 + 1 − 휓푟 푘 = 푉푟푇푒 0 퐿 푀 푠푖푛 휃 푀 푐표푠 휃 푖푠훽 [ 푠 ] 푀 푐표푠 휃 푀 푠푖푛 휃 퐿푟 0 푖푟훼 With: −푀 푠푖푛 휃 푀 푐표푠 휃 0 퐿푟 [푖푟훽] 휓(푘 + 1): Flux vector (stator or rotor flux) at the next (2) sampling step. 휓(푘) : Flux vector (stator or rotor) at the current The electromagnetic torque can be determined from: sampling step. 3 푃푀 훥휓 : Variation of the flux vector (휓(푘 + 1) − 푇푒푚 = (휓푠훽휓푟훼 − 휓푠훼휓푟훽) (3) 2 휎퐿푠퐿푟 휓(푘)). 푑훺 푇푒 : Sampling period. With: 푇 = 푇 + 퐽 + 푓. 훺 (4) 푒푚 푟 푑푡 From Eq. (6), it can be noticed that over a 3. Direct torque control strategy sampling interval [0. 푇푒], the extremity of the flux vector moves on a straight line whose direction is 3.1 Principe of the DTC given by the selected voltage vector 푉 for a period 푇푒, through choosing an appropriate sequence of the The DTC aims directly at controlling the torque voltage vector of the inverter over successive and flux produced by the machine, without current sampling periods of duration 푇푒 .
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