Direct Torque Control Research Articles

Neural network based variable DC-link voltage control of electric vehicle driveline

ABSTRACT The variable DC link direct torque control (DTC) for induction motors was proposed in this paper utilizing an artificial neural network (ANN). Variable DC-link voltage is utilized as the inverter’s controlling input to improve the induction motor’s performance. By injecting the dynamically variable dc-link voltage, inverter switching losses are decreased and inverter efficiency is increased. Two significant limitations are the torque ripple in DTC and the speed regulation of induction motors at low speeds. The driveline of an electric vehicle is modeled, and the suggested control is put into practice to enhance low-speed speed regulation, high dynamic performance, and minimal torque ripple. With variable DC-link voltage based on ANN, an improvement in torque and speed is made possible. Additionally, the suggested strategy minimizes the current ripples. To verify the improved efficacy of the electric driveline under various operating scenarios, a proposed control of the electric driveline is implemented using MATLAB SIMULINK, and the results are compared with the conventional scheme. The recommended speeds for the three speed ranges are as follows: 300 rpm for low speed, 900 rpm for medium speed, and 1275 rpm for high speed. The torque ripples decreased from 0.39 to 0.24 in the low-speed region, 0.38 to 0.24 in the medium-speed region, and 0.36 to 0.24 in the high-speed region while the motor was operated at a constant load torque of 2 N-m. The torque ripples decreased from 0.4 to 0.274 in the low speed region, 0.4 to 0.274 in the medium speed zone, and 0.2 to 0.274 in the medium speed region when the motor operated at various speed regions with a constant load. The main effect of running the motor at different load torques, such as 1.5 N-m, 2.5 N-m, and 2.0 N-m, is shown in Table 9 and numerical data of torque ripples is presented in Table 9.

New coordinated drive mode switching strategy for distributed drive electric vehicles with energy storage system

High performance and comfort are key features recommended in hybrid electric vehicle (HEV) design. In this paper, a new coordination strategy is proposed to solve the issue of undesired torque jerks and large power ripples noticed respectively during drive mode commutations and power sources switching. The proposed coordinated switching strategy uses stair-based transition function to perform drive mode commutations and power source switching’s within defined transition periods fitting the transient dynamics of power sources and traction machines. The proposed technique is applied on a battery/ supercapacitor electric vehicle whose traction is ensured by two permanent magnet synchronous machines controlled using direct torque control and linked to HEV front and rear wheels. Simulation results highlight that the proposed coordinated switching strategy has a noteworthy positive impact on enhancing HEV transient performance as DC bus fluctuations were reduced to a narrow band of 6 V and transient torque ripples were almost suppressed.

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.

Improvised direct torque control of a permanent magnet synchronous motor

Permanent magnet synchronous motor (PMSM) is widely used in different applications because of their different key operation features. But despite having important key features, PMSM suffers from torque ripple when simple control techniques like direct torque control (DTC) are employed. Several approaches have been raised by many researchers to lessen the ripple when DTC is used for controlling the PMSM drive. In this work, duty ratio-optimized DTC control, which has the same simplicity as conventional DTC (CDTC), and delay compensation for input signal prediction are proposed. In the proposed system, to determine the duty ratio, slope manipulation was made by considering the minimization of torque error and forcing the developed torque to be equal to the reference torque at the end of the span. An online slope determination approach was employed to compute the duty ratio. MATLAB 2021b is used for simulation purposes. The dynamics and steady-state performance of the proposed scheme were tested for both variable-load and variable-speed operations. In addition, the harmonic performance and ratio of harmonic power loss to total active power loss of the motor were evaluated. In general, the proposed scheme performs effectively in reducing steady-state ripple and harmonic.

Laboratory Implementation of Direct Torque Controller based Speed Loop Pseudo Derivative Feedforward Controller for PMSM Drive

Laboratory Implementation of Direct Torque Controller based Speed Loop Pseudo Derivative Feedforward Controller for PMSM Drive

Direct Torque Control of a Four-Phase Switched Reluctance Motor for Electric Vehicle Drives

Direct Torque Control of a Four-Phase Switched Reluctance Motor for Electric Vehicle Drives

An Enhanced Discrete Virtual Vector-Based Direct Torque Control of PMSM Drives

An Enhanced Discrete Virtual Vector-Based Direct Torque Control of PMSM Drives

Direct Torque Control Schemes for Dual Three-Phase PMSM Considering Unbalanced DC-Link Voltages

Direct Torque Control Schemes for Dual Three-Phase PMSM Considering Unbalanced DC-Link Voltages

A New Direct Torque Control of an Efficient and Cost-Effective Traction System Using Two Squirrel Cage Induction Motors Feed by a Single Inverter

Reducing the financial cost of controlling electrical machinery is a major factor in industrial systems. The research is based on controlling dual squirrel cage induction motors (SCIMs) using direct torque command (DTC) based on neural algorithms (NAs). The proposed neural DTC (NDTC), developed from DTC and NAs, where NAs have a lot of outstanding advantages in many aspects, such as accuracy, robustness, and dynamic performance. However, the NDTC-based dual-SCIM system is a simple, robust technique, reliable and highly efficient system with a low cost of implementation. In this work, Matlab software was used to study the NDTC behavior of dual SCIMs by comparing the results obtained with DTC results in terms of response time, current quality, torque ripples, overshoot, … etc. Also, the performance of the NDTC is studied in case the parameters of the system change compared to DTC performance. The obtained results show the efficiency and performance of the NDTC of the dual SCIMs, and that this system is a practical alternative to controlling a group of motors in industrial systems. The ratio ripples between both strategies are 72.97%, 48.38% and 66.11% for current, flux, and torque. This means that the NDTC can be a good candidate for controlling machines.

Modified Direct Torque Control of Solar Fed Sensorless Switched Reluctance Motor Drive for Electric Vehicle With Regenerative Braking

Modified Direct Torque Control of Solar Fed Sensorless Switched Reluctance Motor Drive for Electric Vehicle With Regenerative Braking

An Optimal Maximum Torque Per Active Flux and Field Weakening Operation for Deadbeat Direct Torque Control Based IPMSM Drive

An Optimal Maximum Torque Per Active Flux and Field Weakening Operation for Deadbeat Direct Torque Control Based IPMSM Drive

Towards sustainable water pumping systems: Integration of particle swarm optimization and direct torque control PSO-DTC

This research paper focuses on the optimization of solar water pumping systems (SWPS) by combining the particle swarm optimization (PSO) technique on the generator photovoltaic (GPV) side and direct torque control (DTC) on the pump motor side. The integration of a maximum power point tracking system (MPPT-PSO) represents a significant advance, enabling maximum power to be extracted from the GPV whatever the weather conditions. The main objective is to improve the energy efficiency of the SWPS system by maximizing the electrical power dedicated to the pumping system. At the same time, the application of DTC to the pump motor aims to optimize the use of the energy generated by the GPV. This intelligent approach adjusts the motor power according to the power extracted from the GPV, thus avoiding unsuitable profiles for the pumping system. This results in better power quality, longer system life and improved tracking speed, which in turn improves the pump's rotational speed, which in turn improves the flow rate of the water pumped. The results of the study confirm that the combination of PSO-DTC approaches improves the overall performance of the SWPS. These improvements persist under different climatic conditions.

Design of a Novel Chaotic Horse Herd Optimizer and Application to MPPT for Optimal Performance of Stand-Alone Solar PV Water Pumping Systems

A significant part of agricultural farms in the Kingdom of Saudi Arabia (KSA) are in off-grid sites where there is a lack of sufficient water supply despite its availability from groundwater resources in several regions of the country. Since abundant agricultural production is mainly dependent on water, farmers are forced to pump water using diesel generators. This investigation deals with the increase in the effectiveness of a solar photovoltaic water pumping system (SPVWPS). It investigated, from a distinct perspective, the nonlinear behavior of photovoltaic modules that affects the induction motor-pump because of the repeated transitions between the current and the voltage. A new chaotic Horse Herd Optimization (CHHO)-based Maximum Power Point Tracking technique (MPPT) is proposed. This algorithm integrates the capabilities of chaotic search methods to solve the model with a boost converter to maximize power harvest while managing the nonlinear and unpredictable dynamical loads. The analytical modeling for the proposed SPVWPS components and the implemented control strategies of the optimal duty cycle of the DC–DC chopper duty cycle and the Direct Torque Control (DTC) of the Induction Motor (IM) has been conducted. Otherwise, the discussions and evaluations of the proposed model performance in guaranteeing the maximum water flow rate and the operation at MPP of the SPVWPS under partial shading conditions (PSC) and changing weather conditions have been carried out. A comparative study with competitive algorithms was conducted, and the proposed control system’s accuracy and its significant appropriateness to improve the tracking ability for SPVWPS application have been proven in steady and dynamic operating climates and PSC conditions.

Efficiency Improvement of Permanent Magnet Synchronous Motors Using Model Predictive Control Considering Core Loss

The highway cycle is an important consideration in the EV’s new European driving cycles (NEDCs) range, as the steady-state efficiency improvement in such conditions can be greatly beneficial. In the model predictive control (MPC) of the permanent magnet synchronous motors (PMSMs), the predicted next-step feedback reference generated by the equivalent circuit model (ECM) will contribute directly to the voltage vector selection, therefore influencing the performance of the motor control. In the current MPC scheme, when the conventional ECM is applied, it only considers copper loss, and the core loss is usually disregarded. In some circumstances, such as the highway cycle of EVs, the motors are at high speed, the torque is low, and the core loss can be significant in the losses, thus affecting the accuracy of control and the efficiency of the system; hence, the introduction of core loss ECM into the MPC would be beneficial. This paper aims to investigate the steady-state efficiency improvement of a novel ECM of PMSM considering core loss ECM, and the comparison will be based on model predictive direct torque control (MPDTC) using the core loss ECM, which will be compared to MPDTC with the conventional ECM of the PMSM. The results demonstrate the proposed ECM’s efficiency improvement in various conditions, the limitations of the model and the simulation are discussed, and future work is proposed.

Improvements the direct torque control performance for an induction machine using fuzzy logic controller

This article examines a solution to the major problems of induction machine control in order to achieve superior dynamic performance. Conventional direct torque control and indirect control with flux orientation have some drawbacks, such as current harmonics, torque ripples, flux ripples, and rise time. In this article, we propose a comparative analysis between previous approaches and the one using fuzzy logic. Results from the simulation show that the direct torque control method using fuzzy logic is more effective in providing a precise and fast response without overshooting, and it eliminates torque and flux fluctuations at low switching frequencies. The demonstrated improvements in dynamic performance contribute to increased operational efficiency and reliability in industrial applications.

Direct Instantaneous Torque Control for Six-Phase SRM With Nonsingular Fast Terminal Sliding Mode Controller

Direct Instantaneous Torque Control for Six-Phase SRM With Nonsingular Fast Terminal Sliding Mode Controller

Improved Torque Controller for Enhancing Performance at Full Speed Range of Direct Torque Control of Brushless Doubly Fed Machine

Improved Torque Controller for Enhancing Performance at Full Speed Range of Direct Torque Control of Brushless Doubly Fed Machine

Speed Control of Induction Motor using Fuzzy Logic

Abstract: In this paper, speed control of induction motor using fuzzy logic controller is proposed. Speed control of induction motor takes place by, Direct torque control(DTC) method i.e. by directly controlling torque. Here we have used Voltage/Frequency speed control method of induction motor. The fuzzy logic controller (FLC) solves the problem of non linearity’s and parameter variation of induction motor. Unlike the conventional standard controllers, the proposed controller has much less computationally demanding. Direct torque control scheme of induction motor is firstly used. Then, the specified rule and their membership functions of proposed fuzzy logic system will be represented. The performance of a controller is evaluated under various operating conditions. A simplified FLC with relatively fewer rules will be implemented for perfect speed control.

Enhanced deadbeat predictive current control with novel generalized space vector modulation for five‐level inverter fed permanent magnet synchronous motor drive with reduced torque ripples and less computational burden

SummaryTraditional electric drive control methodologies, such as field oriented control (FOC) and direct torque and flux control (DTFC), predominantly rely on multiple proportional‐integral (PI) controllers that demand complex tuning. While model predictive current control (MPCC) omits PI controllers, it has inherent challenges including high computational burden and tempered dynamics. Although two‐level inverters (2LI) are prevalent in many applications, their performance wanes in high‐power applications like high performance industrial drives and marine propulsions. Multilevel inverters (MLIs) are more efficient, but combined with space vector modulation (SVM), they add computational complexity, particularly at higher levels, limiting drive sampling frequencies and causing torque ripples and harmonics, affecting performance. To address the above drawbacks, this manuscript presents a deadbeat predictive current control of five‐level inverter fed permanent magnet synchronous motor (PMSM) drive with a novel generalized SVM algorithm with reduced computational burden and improved performance. The proposed method is validated through MATLAB/Simulink‐based simulation study and experimental implementation. The results are presented and discussed. The results are compared with DTFC and MPCC where it is observed that the proposed method offers superior performance with reduced computational burden and streamlined implementation.

An enhanced direct torque control strategy with composite controller for permanent magnet synchronous motor

AbstractDirect torque control (DTC) based on sliding mode control (SMC) has been widely applied to permanent magnet synchronous motor (PMSM) drives for torque ripple reduction and flux tracking. However, the control performance may be degraded due to disturbances such as variations in motor parameters or uncertainties. In this paper, a DTC strategy with an improved composite SMC controller is proposed for the PMSM drive system to enhance its performance under various disturbances. The speed controller is first designed based on a proposed adaptive reaching law (ARL) to eliminate chattering that appears in the conventional SMC, accelerate convergence, improve tracking performance, and reduce torque ripples. Then, an enhanced extended sliding mode disturbance observer (E2SMDO) is developed to estimate the lumped disturbances of the PMSM drive system in real time and compensate for a feedforward to the speed controller. By combining the ARL and E2SMDO, a composite controller (denoted ARL + E2SMDO) is established, whose stability is proven through the Lyapunov theory. The effectiveness of the proposed method is validated by simulations and experiments. The results of both simulations and experiments demonstrate that the composite ARL + E2SMDO controller has a fast dynamic response, reduced torque ripples, strong robustness, and good anti‐disturbance compared to other conventional methods.