Electric Motor Control Research Articles

IoT-Based Control, Monitoring, and Protection System for 3-Phase Induction Motors in Electric Motorcycles

This study investigates the application of the Internet of Things (IoT) for wireless control and monitoring of a 3-phase electric motor using a smartphone. The system integrates PZEM-004T, DS18B20, and Hall Effect sensors to collect data on voltage, current, temperature, and rotational speed using the NodeMCU ESP8266 microcontroller. Measurements are displayed on an LCD and transmitted to the Blynk server for smartphone access. A comparative method evaluates the accuracy of sensor readings against standard measuring instruments. Results obtained an average percentage error of 0.5% for the R phase voltage, 0.2% for the S phase, and 0.1% for the T phase. Current measurements reveal errors of 5% for the R phase, 10.3% for the S phase, and 11.7% for the T phase. The control system’s performance varies with internet speed, with an average delay of 0.99 seconds on a 4G network and 2.51 seconds on 3G. Additionally, the study evaluates three protection mechanisms, demonstrating that the motor stops within 4.03 seconds in the event of a phase failure, while overcurrent and overheating protections activate within 8.47 seconds and 3.64 seconds, respectively. Overall, the findings affirm the viability of IoT in motor monitoring and control, emphasizing accuracy and response times under varying conditions.

Chaotic-Based Improved Henry Gas Solubility Optimization Algorithm: Application to Electric Motor Control

This study presents a novel meta-heuristic optimization method that combines the Henry Gas Solubility Optimization (HGSO) technique with symmetric chaotic systems. By leveraging the randomness of chaotic systems, the parameters of the HGSO algorithm that require random generation are produced through chaotic processes, allowing the algorithm to exhibit chaotic behavior in its pursuit of optimal values. This innovative approach is termed Chaotic Henry Gas Solubility Optimization (CHGSO), with the primary objective of enhancing the performance of the HGSO method. The randomness of the data obtained from chaotic systems was validated using NIST-800-22 tests. The CHGSO method was applied to both 47 benchmark functions and the optimization of parameters for a PID controller utilized in the speed control of a DC motor. To evaluate the effectiveness of the proposed method, it was compared with several widely recognized algorithms in the literature, including PSO, WOA, GWO, EA, SA, and the original HGSO algorithm. The results demonstrate that the proposed method achieved the best performance in 43 of the benchmark functions, outperforming the other algorithms. In the context of controller design, the PID parameters were optimized using the error-based ITSE objective function. According to the controller responses, the proposed method has achieved the best results in the simulation studies, with a settling time of 0.035 and a rise time of 0.014 without overshooting, and in the experimental studies, with a settling time of 0.15 and a settling time of 1.4%. When the results are examined, it is observed that it has achieved successful results in the controller design problem.

Desing of an observer with real time monitoring speed and load torque for submersible induction motors

Relevance. When operating submersible equipment for oil production in aggressive environments and transferring wells to the cyclic operation mode, a decrease in the service life of the submersible installation for oil production is observed. In the first case, this is due to the formation of salt deposits and clogging of the working parts of the electric pump with mechanical impurities. In the second case – an increase in the number of starts of the submersible electric motor. To solve the existing problems, it is possible to implement closed control systems for submersible electric motors based on state variable observers, which determines the relevance of the study. Aim. To develop an observer with operational monitoring of the angular velocity of the rotor and the moment of resistance on the shaft of a submersible asynchronous motor at inconsistency of the initial conditions in various operating modes and its testing using modeling tools. Methods. The observer is built on the basis of known engine models in a fixed coordinate system α, β, the theory of IIR-filters to obtain a forecast of estimates of the angular velocity of the rotor and the torque on the shaft and their correction in real time. Results. The authors have proposed the original structure of an observer with operational monitoring of the angular velocity of the rotor and the moment of resistance on the shaft of a submersible asynchronous motor. Conclusions. The paper demonstrates the observer performance with inconsistency of initial conditions and electric motor model data in various operating modes. In all modes, stable estimates of the speed and torque of resistance on the electric motor shaft are obtained. At the same time, the error in estimating the angular velocity under the condition of changing the load on the shaft and starting in the loaded state is no more than 1.2%, which is acceptable in submersible electric motor control systems. It is revealed that the developed observer, under the condition of changing the active resistance of the stator and rotor in the ranges from –25 to +25% of the nominal value, obtains estimates of the angular velocity with an integral error of no more than 5%, except for starting the motor with a decrease in the active resistance of the rotor by 25% of the nominal value –5.53%, which is acceptable in engineering practice.

Approach for sizing by optimization of an electrical drive considering a multiphysics and multidynamics behaviour

PurposeThis paper aims to describe a modelling and solving methodology of a (static converter–electric motor–control) system for its sizing by optimization, considering the dynamic thermal heating of the machine.Design/methodology/approachThe electrical drive sizing model is composed of two simulators (electrical and thermal) that are co-simulated with a master−slave relationship for the time step management. The computation is stopped according to simulation criteria.FindingsThis paper details a methodology to represent and size an electrical drive using a multiphysics and multidynamics approach. The thermal simulator is the master and calls the electrical system simulator at a fixed exchange time step. The two simulators use a dedicated dynamic time solver with adaptive time step and event management. The simulation automatically stops on pre-established criteria, avoiding useless simulations.Research limitations/implicationsThis paper aims to present a generic methodology for the sizing by optimization of electrical drives with a multiphysics approach, so the precision and computation time highly depend on the modelling method of each components. A genetic multiobjective optimization algorithm is used.Practical implicationsThe methodology can be applied to size electrical drives operating in a thermally limited zone. The power electronics converter and electrical machine can be easily adapted by modifying their sub-model, without impacting the global model and simulation principle.Originality/valueThe approach enables to compute a maximum operating duration before reaching thermal limits and to use it as an optimization constraint. These system considerations allow to over constrain the electrical machine, enabling to size a smaller machine while guaranteeing the same output performances.

Optimizing electric vehicle powertrains peak performance with robust predictive direct torque control of induction motors: a practical approach and experimental validation

Enhancing the efficiency of the electric vehicle’s powertrain becomes a crucial focus, wherein the control system for the traction motor plays a significant role. This paper presents a novel electric vehicle traction motor control system based on a robust predictive direct torque control approach, an improved version of the conventional DTC, where the traditional switching table and the hysteresis regulators are substituted with a predictive block based on an optimization algorithm. Additionally, a robust predictive speed loop regulator is employed instead of the proportional-integral regulator, which integrates a new cost function with a finite horizon, incorporating integral action into the control law based on a Taylor series expansion. This technique’s primary benefit is its independence from the necessity to measure and observe external disturbances, as well as uncertainties related to parameters. The effectiveness of the suggested system was confirmed through simulation and experimental results under the OPAL-RT platform. The findings indicate that the proposed approach outperforms the conventional method in terms of rejecting disturbances, exhibiting robustness to variations in parameters, and minimizing torque ripple.

SYNTHESIS OF NARMA-L2 NEURAL CONTROLLER FOR TRACTION INDUCTION ELECTRIC DRIVE SYSTEM

In today's world, where technology is developing rapidly, electric drive systems play a key role in a huge range of applications: from industrial production lines to vehicles and household appliances. These systems require high efficiency, accuracy and reliability. It is here that there is a need to improve and optimize the processes of controlling electric drives.In recent decades, neural network controllers, or neuroregulators, have won their place in the world of automatic control. Their unique ability to model complex nonlinear dependencies makes them an ideal tool for applications in electric drive systems. Neuro-regulators can adapt to changing operating conditions, learn from data and optimize the control process depending on specific requirements and conditions.This work is devoted to the possibility of using a neuroregulator in the traction asynchronous electric drive system. In the Matlab/Simulink environment, a simulation model of the AD914-U traction asynchronous electric motor vector control system described in the d,q rotating coordinate system was developed. The synthesis of the NARMA-L2 neuroregulator was performed, which combines the principles of the autoregressive model and the moving average model to provide prediction and control of complex processes. The main idea of this controller is to build a nonlinear transformation of input data that can predict the future states of the system. To demonstrate the capabilities of neuroregulators in traction electric motor control systems, comparative modeling of the NARMA-L2 neuroregulator and the classical proportional-integral regulator was conducted.The results of simulation modeling show that the system with a neuro-regulator shows the best indicators of regulation of the given parameters in transient processes and is a promising tool in the development of high-performance and energy-efficient traction electric drives.

Impact of Variable Speed Drive Jobsheet Integrated with Project-Based Learning Model on Electric Motor Control Skills of Vocational Students

The problem in this study is that many students in the electrical power installation engineering (EPIE) class have not mastered the skills of electric motor control (EMC). This is because the teacher still uses traditional methods in the learning process. Namely, the teacher actively explains the material according to practical experience rather than referring to EMC learning objectives. This study aims to apply a variable speed drive (VSD) jobsheet based on project-based learning (PjBL) in the EMC learning process and measure the effectiveness of the jobsheet applied. The research method used was a pre-experiment with an intact group comparison research design. The research subjects were taken from 11th-grade students of vocational schools majoring in electrical power installation engineering and were assessed using a questionnaire instrument to evaluate students' EMC performance. Data analysis techniques used were independent t-test and effect size test. Based on the independent t-test analysis results, the t-value is larger than the t-table (t = 4.936 > 1.99962), and the significance value is 0.000, which shows a significant difference in skills between the experimental and control classes. Based on the effect size analysis, the value is 1.243, which means the jobsheet can improve students' EMC skills in the large category. Based on these two results, it is known that the PjBL-based VSD jobsheet is effective in the EMC learning process. Thus, it is expected that EPIE vocational high schools can use the PjBL-based VSD Jobsheet in the EMC learning process.

Real-time and hardware in the loop validation of electric vehicle performance: Robust nonlinear predictive speed and currents control based on space vector modulation for PMSM

The transport industry's environmental impact has prompted various stakeholders to focus more on electric vehicles as a potential solution. Extensive research on electric vehicle motor control reveals their complexity, highlighting the crucial role of the traction motor control mechanism being one of their essential subsystems. This study presents a novel approach to control the drive system of an electric vehicle's permanent magnet synchronous motor, using a robust non-linear model predictive control in a cascaded structure combined with a space vector modulation technique. The formulation of the robust non-linear model predictive control law involves optimizing a new cost function with the inclusion of an integral action in the controller to ensure zero steady-state error. An important aspect of this control approach is its ability to enhance robustness without needing information about external perturbations and parameter uncertainties. Moreover, the space vector modulation technique is designed to address the issue of current harmonic distortion by carefully selecting appropriate switching vectors. The appropriate selection for space voltage vectors for every sampling period maintains a consistent switching frequency. As a result, the SVM can enhance torque-rippled regulation and accomplish effective flux and torque control. The performance of the proposed control system is evaluated through a series of numerical simulations using MATLAB/Simulink. The simulation results are analyzed and compared to assess the effectiveness of the proposed control system in terms of tracking accuracy, disturbance rejection, robustness against parameter uncertainties, reduction of torque, and current ripples. To further validate the numerical simulation results, a hardware-in-the-loop (HIL) setup is established using the OPAL-RT platform. Furthermore, experimental validation on a PMSM utilizing the dSPACE DS1202 board is carried out, demonstrating the efficacy of the proposed control system. These findings validate the suggested control technique's robustness and efficiency.

Comparative Study of In-Wheel Motor Control Systems Based on Multiple Controllers

This paper proposes a comparative study of hub motor control based on multiple control strategies (pi control, direct torque control, model predictive current control) to address the problem of slow dynamic response in traditional vector control of electric vehicle permanent magnet synchronous hub motors. By strictly extracting the mathematical model of the motor, the desired target voltage vector and current vector are derived using three controllers and applied to the controlled object. Finally, experiments are conducted on a simulation platform, and the experimental conclusions are used to compare and analyze the reliability and adaptability of different controllers.

Three-phase Electric Motor Control with a Manual Forward Reverse Control System Equipped with a Delay Timer

The control of three-phase electric motors with manual forward and reverse control systems equipped with off-timers (TOF) is a production solution with a simple structure and relatively low cost compared to other systems. Three-phase induction motors typically work via electromagnetic induction from the stator winding to the rotor, making them the preferred choice in both large and small industries due to their accommotivity and efficiency. The purpose of this study was to determine and analyze the control of a three-phase electric motor with a manual back and forth control system equipped with a delay timer. The research method used is secondary data analysis from various relevant and valid sources. The results showed that the manual back and forth control system with TOF is very effective in moving production equipment efficiently and reliably. The implications of this study show that with current technological developments, the use of three-phase electric motors with manual back and forth control systems equipped with TOF has become very important in improving operational efficiency and effectiveness in the industrial world.

Devising a technique for assessing the accuracy of measuring electric motor torque

The object of this study is a technique for assessing the accuracy of measuring the torques of electric motors. This technique is based on the improvement of dynamic torque measurement processes under transient operating modes. Special attention was paid to devising adaptive methods to normalize the output signal, which take into account vibrations and nonlinearities of the measuring channel. In order to improve the accuracy of measurements under conditions when the controlled parameter has different deviations from its average value, a technique for integrating time measurement intervals was proposed. That has made it possible to generalize parameter fluctuations, providing more stable measurement results. This paper reports the simulation of the process of measuring torques of electric motors under transient operating modes and under vibration conditions. That has made it possible to test the proposed technique for estimating the variance of the methodological error, which includes the integration of measurement time intervals and makes it possible to increase the accuracy of the measurement under the conditions of transient modes in electric motor operation. An algorithm for correcting the error of the dynamic torque of the electric motor has been proposed, which allows it to be corrected. This becomes possible owing to the use of a reference measure and the proposed technique for determining the deviations of the controlled parameter of the measured quantity, as well as the automatic calibration of measuring transducers. The algorithm allows for flexible settings of the corrective action, expanding the potential of electric motor control systems. It can complement soft measurement methods, as well as adjust the threshold values of deviations under different operating modes of electric motors. This allows the measured systems to better adapt to changes in operating conditions, to adjust the specified measurement accuracy under conditions of uncertainty

CFD simulation analysis optimization and experimental verification of heat dissipation problem of electric vehicle motor controller

Abstract Pollution and energy crisis are two major challenges facing society today, and electric vehicles are regarded as an effective way to solve these problems. Solving the heat dissipation problem of the motor controller can effectively solve the problem of small motion range of electric vehicles, which is an effective attempt for new energy vehicles. Optimizing the heat dissipation structure of the power system can improve the efficiency of electric vehicles, save energy, and truly achieve optimal energy management. Therefore, the establishment of a reasonable and complete power system cooling system is of great significance for improving the overall performance of the vehicle. This article aimed to explore the heat dissipation problem of electric vehicle motor controllers. This article proposed that the motor can be divided into DC and AC based on the power supply. The DC motor has the characteristics of complex structure, cumbersome production process, easy to wear during use, and troublesome repairs in the later period. Through CFD simulation analysis, the experimental temperature of 1.5 kw natural convection is 62.35 °C, the simulation temperature is 64.05 °C; the experimental temperature of 1.1 kw natural convection is 50.45 °C, and the simulation temperature is 66.67 °C.

Four-compartment muscle fatigue model to predict metabolic inhibition and long-lasting nonmetabolic components.

Introduction: Computational muscle force models aim to mathematically represent the mechanics of movement and the factors influencing force generation. These tools allow the prediction of the nonlinear and task-related muscle behavior, aiding biomechanics, sports science, and rehabilitation. Despite often overlooking muscle fatigue in low-force scenarios, these simulations are crucial for high-intensity activities where fatigue and force loss play a significant role. Applications include functional electrical stimulation, motor control, and ergonomic considerations in diverse contexts, encompassing rehabilitation and the prevention of injuries in sports and workplaces. Methods: In this work, the authors enhance the pre-existing 3CCr muscle fatigue model by introducing an additional component of force decay associated with central fatigue and a long-term fatigue state. The innovative four-compartment model distinguishes between the short-term fatigued state (related to metabolic inhibition) and the long-term fatigued state (emulating central fatigue and potential microtraumas). Results: Its validation process involved experimental measurements during both short- and long-duration exercises, shedding light on the limitations of the traditional 3CCr in addressing dynamic force profiles.

Motor 3 Fasa Star Delta Menggunakan Outseal PLC (Programmable Logic Control)

With the development of science and technology, the use of electrical energy will continue to increase in households and industry. One of them is the use of a three-phase induction motor which is often used in industry in the production process. The many types of induction motors used require the selection of a more efficient system. The induction motor regulation system can be done manually or automatically. To automatically regulate the system, it can be done by applying programmable logic control (PLC). The aim of this research is to develop an automatic 3-phase electric motor control system using Outseal Programmable Logic Control (PLC).

Control system for noise-resistant electronic speed controller of a brushless electric motor for an unmanned aerial vehicle

Objectives. The high demand for unmanned aircraft and their efficiency makes the production of their components a matter of relevance. One of these components is the speed controller of the brushless electric motor of the propeller motor group. At the current time, Russian industry, however, does not mass-produce them. In order to start production, control methods and algorithms for the hardware and software parts of devices of this type are needed. Criteria for selecting the main components also need to be formalized. The aim of this work is to develop a method for the software control of electric motors. This includes block diagrams and invariant algorithms and methods for the calculated selection of parameters of the main microcontroller of the electronic speed controller.Methods. Methods of algorithmization, expert assessments, linear computational processes and experimental studies were used.Results. The paper presents the theoretical basis for controlling the required motors. It proposes a block diagram of the implementation of the controller, and a technique for switching windings when controlling with a trapezoidal signal is proposed. Examples are given in the form of an oscillogram. Based on theoretical research, an invariant algorithmic apparatus was developed for building software for various types of microcontrollers. Block diagrams of all the main modules of the software are also presented. The main ones include: the event switching algorithm; and the main endless loop of the microcontroller. The requirements for microcontrollers to create the various types of speed controllers are formalized herein and presented in the form of a set of mathematical expressions. They enable the number of required peripheral devices and microcontroller ports to be calculated according to the requirements for the microcontroller, as well as the computing power of the core used.Conclusions. Experimental studies show the reliability of the theoretical research presented herein. The results obtained can be used to select the optimal element base and develop software for speed controllers of electric motors of the propellers of unmanned aircraft.

Selection of power supply scheme for controlled excitation converters in traction electric motors of single-phase DC electric locomotives

The article focuses on the development of an effective design and algorithms for automatic control of singlephase DC electric locomotives according to the laws of constant traction force and power without switching electrical devices within power electric circuits. Methods of mathematical modelling for electromagnetic, electromechanical, and mechanical processes by MatLab, Simulink, and SimPowerSystems software were used to address this problem. The nonlinearities of the magnetisation curve were taken into account, along with the influence of eddy currents from the coils of the main and additional poles in traction motors. Structural and parametric synthesis of a power electrical circuit and control algorithms by controlled bridge IGBT converters were used in the simulation. The object of the research was an electrotechnical complex, including a 9840 kW three-stack electric locomotive 3ES5K “Ermak”. On the basis of the research results, it is recommended to use a power electrical circuit with two reversible converters for each of the three sections on the electric locomotive. These converters provide power to four 820 kW traction motors and a group power supply for controlled bridge IGBT converters shunting the field coils for axial traction control. The calculations confirmed the applicability of a scheme for individual control of traction electric motors and excitation currents, ensuring a smooth increase in the traction force of an electric locomotive. The developed algorithm of axial traction control ensures a smooth increase in this force and creates the optimal conditions for coupling the wheels of an electric locomotive with rails. These solutions can be used in the manufacture and modernisation of new and existing electric locomotives

Optimal High-Frequency Injection Minimizing High-Frequency Torque Ripple for Sensorless Control of Electric Vehicle IPM Traction Motors

Optimal High-Frequency Injection Minimizing High-Frequency Torque Ripple for Sensorless Control of Electric Vehicle IPM Traction Motors

Intelligent vector-frequency control system for asynchronous electric motors

This article analyzes the main directions and principles of developing a mathematical model for creating an intelligent system for vector-frequency control of asynchronous electric motors. Particular attention is paid to the development of a frequency converter structure that allows the implementation of an energy-saving algorithm in a direct torque control (DTC) system to reduce stator current consumption from the power source. This approach guarantees stable operation of the electric motor under various load conditions and voltage changes in the electrical network. The synthesis of a speed control system and current control loops are considered and generalized models of a vector control system are developed using the Matlab software package and the main Simulink library.

Design and Implementation of Innovative Electric Motor and Electrical Control Curriculum

Design and Implementation of Innovative Electric Motor and Electrical Control Curriculum

Impact of Variable Speed Drive Jobsheet Integrated with Project-Based Learning Model on Electric Motor Control Skills of Vocational Students

Impact of Variable Speed Drive Jobsheet Integrated with Project-Based Learning Model on Electric Motor Control Skills of Vocational Students