Hybrid beluga whale optimization based MPPT for photovoltaic powered open end winding induction motor drives.

This paper introduces an effective four-level voltage switching state algorithm for direct torque controlled open end winding induction motor drive with two-two level inverters in dual mode. In the recent days, direct torque control of open end winding induction motor drive became an interesting area for researchers because it provides high dynamic performance and instantaneous control of stator flux and torque. It is more important especially in applications like propulsion and hybrid electric vehicles they require ripple free torque. The direct torque control provides high flux, torque ripple, and variable switching frequency. This paper introduces an effective voltage switching state algorithm for an open end winding induction motor drive to reduce torque and flux ripple at different frequencies of operation. The experimental results show that the proposed algorithm reduces torque and flux ripples without losing features of conventional direct torque control (DTC) algorithm and in addition it provides multi-level operation.

Direct torque control (DTC) and predictive torque control (PTC) strategies emerged as powerful tools for speed control of variable frequency drives (VFD). The limitations in classical DTC and PTC are: higher ripple in torque, flux, variable switching frequency, and higher common‐mode voltage (CMV). High dv/dt and CMV results in shaft voltages, bearing currents, malfunction of power electronic devices and electromagnetic interference (EMI). To eliminate the CMVs and also to reduce the switching frequency, voltage vector selection‐based DTC and PTC strategies are introduced to an open‐end winding induction motor (OEWIM) drive. Another limitation of classical PTC is cumbersome tuning of weighting factors. To address this limitation, modified cost function‐based PTC strategy has been developed to eliminate weighting factors. OEWIM drive operates with dual inverter configuration and the two inverters are operated with equal DC‐link voltages; therefore, it delivers three‐level output voltage. This article introduces various DTC and PTC strategies to an OEWIM drive to reduce torque, flux ripples, switching frequency, elimination of CMV, and weighting factors. The effectiveness of proposed DTC and PTC strategies is tested by dspace‐1104 real‐time interface controller and comparing the obtained results with classical DTC and PTC.

Introduction: The growing emphasis on sustainable transportation, driven by climate change awareness, is accelerating the adoption of electric vehicles (EVs). A critical challenge is the precise control of induction motors (IMs) used in EVs. Traditional control methods like Field Oriented Control (FOC) and Direct Torque Control (DTC) suffer from parameter sensitivity and high torque ripple, reducing efficiency. This research proposes a Fuzzy DTC scheme to address these limitations. Objectives: The primary objectives of this research are to develop and implement a Fuzzy-based Direct Torque Control (DTC) scheme for Induction Motor (IM) drives in Electric Vehicles (EVs), specifically designed to overcome the limitations of conventional DTC methods. This entails achieving a significant reduction in torque ripple, a common issue in traditional DTC, which directly impacts the smoothness and efficiency of the EV's operation. Furthermore, the research aims to enhance the dynamic response of the IM drive system, enabling faster and more precise control of the motor's torque and speed, crucial for the dynamic driving conditions experienced by EVs. Ultimately, the successful implementation of the Fuzzy DTC scheme should lead to an overall improvement in the efficiency and robustness of the IM speed control within the EV system, ensuring reliable and high-performance operation across all driving scenarios, including acceleration, deceleration, and constant speed maintenance. Methods: The methodology employed in this research centers around the development and implementation of a Fuzzy-based Direct Torque Control (DTC) scheme for Induction Motor (IM) drives. Departing from traditional DTC, which relies on hysteresis bands and a switching table, this approach integrates a Fuzzy Logic Switching Controller (FLSC) to optimize inverter switching decisions. The FLSC takes as inputs the torque error, stator flux error, stator flux angle, and the count of switching updates, providing a more refined control mechanism. A Mamdani fuzzy inference system (FIS) is utilized, employing triangular and trapezoidal membership functions to fuzzify these input variables. The output of the fuzzy controller dictates the switching state, selected from seven possible states represented by crisp triangular membership functions. This fuzzy logic-based approach allows for a more nuanced and adaptive control strategy, enabling the system to respond effectively to the nonlinearities and uncertainties inherent in IM drives. The fuzzy rules, developed based on engineering expertise and practical experience, guide the selection of the optimal switching state. The research leverages simulations using MATLAB/Simulink to model the IM drive system and evaluate the performance of both conventional and Fuzzy DTC schemes under various operating conditions. This allows for a comparative analysis of torque ripple, dynamic response, and overall efficiency, validating the effectiveness of the proposed fuzzy-based control strategy. Results: The simulation results presented in this paper demonstrate the superior performance of the proposed Fuzzy-based Direct Torque Control (DTC) scheme compared to conventional DTC methods for Induction Motor (IM) drives in Electric Vehicles (EVs). Across various operating conditions, including different load and speed combinations, the Fuzzy DTC consistently exhibited a significant reduction in torque ripple. This reduction translates to a smoother and more efficient motor operation, crucial for enhancing the driving experience and overall performance of EVs. Furthermore, the Fuzzy DTC showed improved dynamic response, characterized by lower overshoot and faster settling times. These findings indicate that the fuzzy logic-based control strategy enables more precise and rapid control of the IM's torque and speed, effectively addressing the limitations of traditional DTC. Specifically, the data presented in Table 3 and Figures 18, 19, and 20 highlight the quantifiable improvements in parameters such as torque ripple percentage, slew rate, and overshoot. The comparative analysis consistently favored the Fuzzy DTC scheme, validating its effectiveness in achieving robust and efficient IM speed control under the dynamic operating conditions typical of electric vehicles. Conclusions: This paper has investigated the application of fuzzy based DTC to induction motor (IM) drives in electric vehicles (EVs). The proposed Fuzzy DTC approach addresses the limitations of conventional technique of DTC, including high ripple of torque by integrating fuzzy logic into the control scheme. Simulation results show the proposed Fuzzy DTC effectively achieves precise and robust speed control under various EV operating conditions. The approach optimizes switching decisions based on fuzzy rules, resulting in improved performance compared to traditional DTC methods. The proposed Fuzzy DTC scheme offers reduced torque ripple, improved efficiency, enhanced dynamic performance, and a smoother driving experience.

Introduction: The growing emphasis on sustainable transportation, driven by climate change awareness, is accelerating the adoption of electric vehicles (EVs). A critical challenge is the precise control of induction motors (IMs) used in EVs. Traditional control methods like Field Oriented Control (FOC) and Direct Torque Control (DTC) suffer from parameter sensitivity and high torque ripple, reducing efficiency. This research proposes a Fuzzy DTC scheme to address these limitations. Objectives: The primary objectives of this research are to develop and implement a Fuzzy-based Direct Torque Control (DTC) scheme for Induction Motor (IM) drives in Electric Vehicles (EVs), specifically designed to overcome the limitations of conventional DTC methods. This entails achieving a significant reduction in torque ripple, a common issue in traditional DTC, which directly impacts the smoothness and efficiency of the EV's operation. Furthermore, the research aims to enhance the dynamic response of the IM drive system, enabling faster and more precise control of the motor's torque and speed, crucial for the dynamic driving conditions experienced by EVs. Ultimately, the successful implementation of the Fuzzy DTC scheme should lead to an overall improvement in the efficiency and robustness of the IM speed control within the EV system, ensuring reliable and high-performance operation across all driving scenarios, including acceleration, deceleration, and constant speed maintenance. Methods: The methodology employed in this research centers around the development and implementation of a Fuzzy-based Direct Torque Control (DTC) scheme for Induction Motor (IM) drives. Departing from traditional DTC, which relies on hysteresis bands and a switching table, this approach integrates a Fuzzy Logic Switching Controller (FLSC) to optimize inverter switching decisions. The FLSC takes as inputs the torque error, stator flux error, stator flux angle, and the count of switching updates, providing a more refined control mechanism. A Mamdani fuzzy inference system (FIS) is utilized, employing triangular and trapezoidal membership functions to fuzzify these input variables. The output of the fuzzy controller dictates the switching state, selected from seven possible states represented by crisp triangular membership functions. This fuzzy logic-based approach allows for a more nuanced and adaptive control strategy, enabling the system to respond effectively to the nonlinearities and uncertainties inherent in IM drives. The fuzzy rules, developed based on engineering expertise and practical experience, guide the selection of the optimal switching state. The research leverages simulations using MATLAB/Simulink to model the IM drive system and evaluate the performance of both conventional and Fuzzy DTC schemes under various operating conditions. This allows for a comparative analysis of torque ripple, dynamic response, and overall efficiency, validating the effectiveness of the proposed fuzzy-based control strategy. Results: The simulation results presented in this paper demonstrate the superior performance of the proposed Fuzzy-based Direct Torque Control (DTC) scheme compared to conventional DTC methods for Induction Motor (IM) drives in Electric Vehicles (EVs). Across various operating conditions, including different load and speed combinations, the Fuzzy DTC consistently exhibited a significant reduction in torque ripple. This reduction translates to a smoother and more efficient motor operation, crucial for enhancing the driving experience and overall performance of EVs. Furthermore, the Fuzzy DTC showed improved dynamic response, characterized by lower overshoot and faster settling times. These findings indicate that the fuzzy logic-based control strategy enables more precise and rapid control of the IM's torque and speed, effectively addressing the limitations of traditional DTC. Specifically, the data presented in Table 3 and Figures 18, 19, and 20 highlight the quantifiable improvements in parameters such as torque ripple percentage, slew rate, and overshoot. The comparative analysis consistently favored the Fuzzy DTC scheme, validating its effectiveness in achieving robust and efficient IM speed control under the dynamic operating conditions typical of electric vehicles. Conclusions: This paper has investigated the application of fuzzy based DTC to induction motor (IM) drives in electric vehicles (EVs). The proposed Fuzzy DTC approach addresses the limitations of conventional technique of DTC, including high ripple of torque by integrating fuzzy logic into the control scheme. Simulation results show the proposed Fuzzy DTC effectively achieves precise and robust speed control under various EV operating conditions. The approach optimizes switching decisions based on fuzzy rules, resulting in improved performance compared to traditional DTC methods. The proposed Fuzzy DTC scheme offers reduced torque ripple, improved efficiency, enhanced dynamic performance, and a smoother driving experience.

Open End Winding Induction Motors (OEWIM) are popular for electric vehicles, ship propulsion applications due to less DC link voltage. Electric vehicles, ship propulsions require ripple free torque. In this article, an enhanced three-level voltage switching state scheme for direct torque controlled OEWIM drive is implemented to reduce torque and flux ripples. The limitations of conventional Direct Torque Control (DTC) are: possible problems during low speeds and starting, it operates with variable switching frequency due to hysteresis controllers and produces higher torque and flux ripple. The proposed DTC scheme can abate the problems of conventional DTC with an enhanced voltage switching state scheme. The three-level inversion was obtained by operating inverters with equal DC-link voltages and it produces 18 voltage space vectors. These 18 vectors are divided into low and high frequencies of operation based on rotor speed. The hardware results prove the validity of proposed DTC scheme during steady-state and transients. From simulation and experimental results, proposed DTC scheme gives less torque and flux ripples on comparison to two-level DTC. The proposed DTC is implemented using dSPACE DS-1104 control board interface with MATLAB/SIMULINK-RTI model.

This work aims to enhance the performance of Photovoltaic Water Pumping Systems (PVWPS) by optimizing its two primary controllers. The first controller utilizes a Particle Swarm Optimization (PSO)-based Maximum Power Point Tracking (MPPT) technique to maximize the photovoltaic array’s output under varying irradiance conditions. The second controller incorporates a PSO-optimized Proportional-Integral (PI) controller within a Direct Torque Control (DTC) method to improve the dynamic behavior of the induction motor (IM) and ensure the efficient functioning of the centrifugal pump. The performance of the PVWPS employing PSO for MPPT and DTC was evaluated in MATLAB Simulink and compared with a system using Artificial Neural Networks (ANN) for MPPT and DTC. The PSO-based approach demonstrated significant advantages, including an 83.33% reduction in power oscillations, a 66.67% and 60% reduction in flux and torque ripples, a 50% improvement in response time, and a rise in water flow. Real-time simulations of both the ANN-DTC and PSO-DTC configurations were carried out on the dSPACE DS1104 platform to validate the performance of each configuration. The outcomes of these simulations closely matched those from MATLAB/Simulink, further confirming the proposed PSO-based control strategy’s effectiveness, robustness, and reliability.

This paper proposes 20-sector based direct torque control (DTC) scheme for dual inverter fed five phase induction motor drives with open-end stator windings powered by a single DC source. The proposed scheme utilizes 20 virtual voltage vectors that divide the space vector plane into 20 sectors, each sector spanning 18 degrees. The 20-sector based DTC scheme provides a smoother control over torque and flux compared to the conventional 10 sector-based DTC schemes for five phase induction motors. The switching scheme used in the proposed scheme eliminates the auxiliary plane harmonic voltages and provides higher DC bus utilization compared to two-level five phase voltage source inverter fed DTC schemes. The switching scheme for realization of these virtual voltage vectors does not generate any resultant common mode voltage across the stator windings and hence a single DC source is used to supply both the voltage source inverters. The proposed DTC scheme is validated by extensive simulation using MATLAB-Simulink software and experimentally verified on a laboratory prototype.

Parameter sensitivity analysis of Direct Torque Control(DTC) scheme for dual inverter fed open end winding induction motor drive with single DC source is presented in this paper. The effect of stator resistance variation on the voltage vector selection in this DTC scheme is analysed using the voltage space structure of a dual inverter configuration with single DC source. Theoretical analysis is validated by simulation on a MATLAB Simulink platform. The results of the theoretical and simulation analyses are experimentally verified on an induction motor with open-end stator windings using TMS320F28335 digital signal processor.

Predictive torque control (PTC) of induction motor drives is one of the best suitable alternatives for direct torque control (DTC). In this article, the weighting factor eliminated PTC for four-level inversion fed open end winding induction motor drive (OEWIMD) has been introduced. The major limitations of classical PTC are as follows: assignment of weighting factor due to dissimilar control objectives, tuning of weighing factors and high computational burden. To circumvent these problems, this article introduces an effective weighting factor elimination-based PTC scheme to an OEWIMD. The proposed algorithm eliminates the complex tuning process of weighting factors by classifying the cost function. The proposed PTC algorithm is simple and provides less computational burden on the controller. In the proposed PTC, the cost function is segregated and ranked accordingly to reduce flux and torque ripples. Cost function-I is formulated to obtain optimum voltage vectors to reduce flux ripples. The same voltage vectors obtained from cost function-I are used in cost function-II to maintain minimum torque ripple. Therefore, the proposed PTC reduces torque and flux ripples with a limited number of voltage vectors and maintains minimum computational burden. The effectiveness of the proposed PTC is verified through MATLAB/SIMULINK and experimentation.

The Direct Torque Control (DTC) technique for Permanent Magnet Synchronous Motors (PMSM) is receiving increased attention due to its simplicity and robust dynamic response when compared with other control techniques. The classical switching table based DTC results in large flux and torque ripples in the motors. Several studies have been reported in the literature on classical DTC. However, there are only limited studies that actually discuss or evaluate the classical DTC. This paper proposes, novel switching table / DTC methods for PMSMs to reduce torque ripples. In this paper, two DTC schemes are proposed. The six sector and twelve sector methodology is considered in DTC scheme I and DTC scheme II, respectively. In both DTC schemes a simple modification is made to the classical DTC structure. The two level inverter available in the classical DTC is eliminated by replacing it with a three level Neutral Point Clamped (NPC) inverter. To further improve the performance of the proposed DTC scheme I, the available 27 voltage vectors are allowed to form different groups of voltage vectors such as Large - Zero (LZ), Medium - Zero (MZ) and Small - Zero (SZ), where as in DTC scheme II, all of the voltage vectors are considered to form a switching table. Based on these groups, a novel switching table is proposed. The proposed DTC schemes are comparatively investigated with the classical DTC and existing literatures through theory analysis and computer simulations. The superiority of the proposed DTC method is also confirmed by experimental results. It can be observed that the proposed techniques can significantly reduces the torque ripples and improves the quality of current waveform when compared with traditional and existing methods.

Modern electric vehicles (EVs) that drive an induction motor (IM) fed by a traction inverter are fast gaining popularity due to their simple configuration and robustness. The direct torque control (DTC) technique is one of the best control methods to drive the IM, especially in open-end winding configurations, as it offers more voltage vectors. However, the existence of hysteresis controllers and improper switching technique causes larger torque ripples that leads to variable switching frequency. The study will be focused on the open-end winding induction motor where the direct current (DC) power is fed from both sides of the stator windings using the dual inverter configuration. To minimize the torque ripples, a simple switching technique using the duty cycle control method is proposed by injecting a high-frequency square wave into the default inverter switching status to form the new pattern of voltage vectors. The effectiveness of the proposed technique is tested through MATLAB/Simulink software and validated experimentally with a lab-scale setup using a dSPACE controller. The findings show that the proposed method reduces torque ripple by over 50% while keeping the DTC's simple structure.

In this paper, a family of RPWM techniques for the direct torque control (DTC) of open end winding induction motor (OEWIM) drive are presented. The conventional PWM inverters generate high harmonic content and concentrated power spectrum. Using RPWM techniques the harmonic spectrum of inverter is continuously distributed, and thus, the harmonic content in the current waveform is reduced, resulting reduction of ripple in electro-magnetic torque. The simulation results of the DTC of OEWIM drive prove the effectiveness of RPWM techniques in the reduction of the ripple and harmonic contents.

The direct torque control (DTC) strategy is one of the most effective techniques, used to control the switched reluctance motor (SRM) with improved dynamic performance and reduced torque ripple. However, this approach draws a higher source current due to an extension of the phase current into the negative torque region, which lowers the net torque per ampere ratio. This study proposes a new DTC strategy for SRM to overcome this issue by modifying the partition of the sectors and appropriate voltage vector selection. Therefore, the proposed method improves the drive efficiency while minimising torque ripple. To implement this method, a non‐linear machine model is developed using the torque and flux characteristics obtained from experimental studies on a four‐phase 8/6 SRM. The proposed DTC scheme is implemented on a digital control platform and power loss calculations are performed to evaluate the drive efficiency. Test results show that the proposed DTC method has improved performance in terms of efficiency and torque ripple under various operating conditions in comparison to the conventional DTC strategy.

Direct Torque Control (DTC) has gained popularity for development of advanced motor control due to its simplicity and offers fast instantaneous torque and flux controls. However, the conventional DTC which is based on hysteresis controller has major drawbacks, namely high torque ripple and variable inverter switching frequency. This paper presents an improved switching strategy for reducing flux and torque ripples in DTC of PMSM drives; wherein the torque hysteresis controller and the look-up table used in the conventional DTC are replaced with a constant frequency torque controller (CFTC) and an optimized look-up table, respectively. It can be shown that a constant switching frequency is established due to the use of the CFTC while the reduction of torque and flux ripples is achieved mainly because of the selection of optimized voltage vector (i.e. with an optimized look-up table). This paper also will explain the construction of DTC schemes implemented using MATLAB-Simulink blocks. Simulation results were shown that a significant reduction of flux and torque ripples which is about 90% can be achieved through the proposed DTC scheme.

Harris hawk optimization-based MPPT control for PV systems under partial shading conditions