Brushless Direct Current Motor Control Research Articles

Analysis of Closed Loop Current Controlled BLDC Motor Drive

Brushless direct current (BLDC) motors are mostly preferred for dynamic applications such as automotive industries, pumping industries, and rolling industries. It is predicted that by 2030, BLDC motors will become mainstream of power transmission in industries replacing traditional induction motors. Though the BLDC motors are gaining interest in industrial and commercial applications, the future of BLDC motors faces indispensable concerns and open research challenges. Considering the case of reliability and durability, the BLDC motor fails to yield improved fault tolerance capability, reduced electromagnetic interference, reduced acoustic noise, reduced flux ripple, and reduced torque ripple. To address these issues, closed-loop vector control is a promising methodology for BLDC motors. In the literature survey of the past five years, limited surveys were conducted on BLDC motor controllers and designing. Moreover, vital problems such as comparison between existing vector control schemes, fault tolerance control improvement, reduction in electromagnetic interference in BLDC motor controller, and other issues are not addressed. This encourages the author in conducting this survey of addressing the critical challenges of BLDC motors. Furthermore, comprehensive study on various advanced controls of BLDC motors such as fault tolerance control, Electromagnetic interference reduction, field orientation control (FOC), direct torque control (DTC), current shaping, input voltage control, intelligent control, drive-inverter topology, and its principle of operation in reducing torque ripples are discussed in detail. This paper also discusses BLDC motor history, types of BLDC motor, BLDC motor structure, Mathematical modeling of BLDC and BLDC motor standards for various applications. Key Words: Brushless direct current, industries, direct torque control.

Sensorless Field-Oriented Control (FOC) using Sliding Mode Observer for BLDC Motor

Motor Brushless Direct Current (BLDC) has become the preferred choice in various engineering applications. However, BLDC motor control involves high complexity, and motor performance depends on the control algorithms used. This research discusses the use of sensorless control methods, specifically the Sliding Mode Observer (SMO) for rotor position and speed estimation in BLDC motors within the context of Field-Oriented Control (FOC), validated through simulations using Matlab/Simulink. Simulation results indicate that SMO provides rapid dynamic response to current changes, albeit with slight delays at high speeds. Rotor position estimation with SMO is also reasonably accurate in both steady-state and transient conditions, affirming the iveness of SMO in sensorless control for BLDC motors. SMO can be experimentally implemented to enhance sensorless control in BLDC motors by reducing the cost of installing Hall sensors while maintaining comparable performance.

Enhancing the solar water pumping efficiency through Beta MPPT method-controlled drive

This paper presents an innovative approach to achieve efficient solar water pumping through the integration of a Photovoltaic (PV) array and a Brushless Direct Current (BLDC) motor water pumping system. The system incorporates a Voltage Source Converter (VSC) with six switches, utilized to facilitate commutation. The inherent solar radiation is harnessed by the PV array, capitalizing on its renewable nature to generate electricity. By dynamically adjusting the switching states of the six VSC switches, the speed of the BLDC motor is modulated in response to the varying levels of available solar radiation. The BLDC motor's hall sensor signals play a crucial for determining the rotor's position and they are employed to generate precise commutation signals. The control strategy integrates the Incremental Conductance (INC) Maximum Power Point Tracking (MPPT) algorithm, which initially governs the commutation signals. To enhance adaptability to rapidly changing solar irradiation conditions, the control strategy dynamically updates the commutation signals using the innovative Beta MPPT algorithm. To assess the efficiency of the proposed control strategy, a comprehensive comparison between the INC and Beta MPPT algorithms is conducted using MATLAB Simulink. The performance of the BLDC motor under these algorithms was evaluated in terms of its ability to optimize energy extraction. The graphical analysis of these algorithms, considering the temporal aspect, substantiates the identification of the superior MPPT algorithm for BLDC motor control in solar water pumping applications. This study contributes to the advancement of solar water pumping systems by introducing a novel control approach that combines PV array utilization, VSC-based commutation, and a dual-step MPPT algorithm. The results demonstrate the effectiveness of the Beta MPPT algorithm by enabling the system to respond promptly to fluctuating solar irradiation conditions, thereby enhancing the overall efficiency of the solar water pumping process.

Advances in BLDC motor control: A thorough examination of torque ripple reduction and speed regulation techniques

Applications that depend on variable speed drives have one main concern: accurate and efficient control of Brushless Direct Current (BLDC) motors. This research explores the key factors that determine the performance of BLDC motors, including torque, motor speed and flux or electromagnetic back-emf fluctuation for optimal efficiency. Although optimal circumstances need continuous torque generation in BLDC motors with trapezoidal back emf, real-world situations result in pulsing torque because of elements such as changes in the motor's manufacturing structure and design, such as slot and teeth. Because of their efficiency, dependability and precise control capabilities, BLDC motors have acquired appeal across a wide range of applications. They are inherently prone to torque ripple and need sophisticated speed management for maximum performance. Torque ripple in BLDC motors is caused by the interaction of the rotor's permanent magnets with the stator's ferromagnetic teeth, which varies in strength throughout the magnetic field and causes unpredictable torque variations. This torque ripple can have a negative impact on speed-torque characteristics, causing noise, vibrations and probable problems in sensorless drives. This study provides a thorough examination of several approaches for decreasing torque ripple. The analysis demonstrates that torque ripple in BLDC motors can be reduced by boosting the input voltage during commutation, magnifying it fourfold compared to the back emf. In addition, the research examines alternative approaches for increasing input voltages throughout the commutation time. These discoveries contribute to the progress of BLDC motor control approaches, allowing for smoother operation and greater performance in a variety of applications.

Implementation of ARM STM32F4 microcontroller for speed control of BLDC motor based on bat algorithm

Brushless direct current (BLDC) motor speed performance is an essential component that must be considered in the electric vehicle drive system. This research aims to obtain the transfer function from the mathematical modeling of the BLDC motor and optimization of the BLDC motor so that a high transient response is received. The method used in this study is to identify system parameters and then model them using the structure of the autoregressive exogenous (ARX) polynomial model. Meanwhile, to get a high transient response performance, optimization is done with a hybrid intelligent controller. The experimental findings indicate that the optimization process utilizing the bat method yielded the most favorable transient response. The resulting values for the proportional gain (Kp), integral gain (Ki), and derivative gain (Kd) were determined to be 31.2685, 7.7375, and -1.1934, respectively. In the current investigation, the minimum frequency value is 6381934.619. Also determined are the transient response characteristics, which include a rise time of 0.289 seconds, a settling time of 10.9 seconds, an overshoot of 3.4%, and a peak time of 1.04 seconds. Furthermore, the closed-loop system demonstrates stable behavior in terms of stability.

Surrogate indirect adaptive controller tuning based on polynomial response surface method and bioinspired optimization: Application to the brushless direct current motor controller

The increment of autonomous systems has stimulated the research of new controller tuning techniques to face the unpredictable disturbances and parametric uncertainties inherent in any autonomous system that affect its performance. The indirect adaptive controller tuning approach based on the general dynamic model (IACTA-GDM) and bioinspired optimization is one of the most successful elections facing parametric uncertainties and disturbances, which are intricate to handle by other controller tuning techniques. However, this controller tuning approach is limited by the complexity of the dynamic model due to the computational burden, restricting its application to relatively small systems or systems with slow responses where the tuning is updated at large time intervals. The present work proposes a novel surrogate indirect adaptive controller tuning approach based on the response surface method (SIACTA-RSM) to address computational burden limitations. The proposal is tested on the speed regulation controller of a brushless direct current motor, with the aim of reducing the speed regulation error and the control system’s power consumption. The closed-loop system performance and the required computational time obtained by the proposed SIACTA-RSM are compared to the ones of a well-established IACTA-GDM. The descriptive and inferential statistics, as well as graphical comparisons, show that the system performance obtained by the SIACTA-RSM proposal is as competitive as the IACTA-GDM approach, keeping a mean difference among the results by up to 3.18% while reducing the computational burden of IACTA-GDM by up to 90%. These outcomes show that the SIACTA-RSM proposal is a reliable alternative to overcome the computational burden limitations that affect the IACTA-GDM approach while maintaining competitive performance.

Field Oriented Control Implementation on BLDC Motor Controller with PI and SVPWM using STM32F103C8T6

Brushless direct current (BLDC) motor are high power density motors with a wide scope for use in electric vehicles, home automation, and industry. But the motor performance degrades due to improper control actions. This is caused by uncontrolled BLDC motor torque currents. Field Oriented Control (FOC) method is a solution for controlling BLDC motor, because it has the advantaged of overcoming torque ripples at low speeds. This paper presents the implementation of FOC on BLDC motor using STM32F103C8T6, which is high speed and low cost microcontroller. STM32F103C8T6 has been applied to handle FOC algorithm calculation and data processing. In order to validate the FOC algorithm system and assess the performance of the STM32F103C8T6 microcontroller, a 350-watt BLDC motor on an electric bicycle was tested and compared with a Universal controller. The tests that have been conducted proven that the FOC controller makes power more efficient, rotates BLDC motor at low speeds, and reduces torque ripple.

Intelligent Power Controller for BLDC Motor

Now-a-days BLDC motors are used in many applications including electric vehicles. The battery-operated vehicles are gaining popularity as people become increasingly aware of the adverse effects of fossil fuel-powered vehicles on the environment. These battery- operated vehicles are equipped with the Brushless direct current (BLDC) motor due to its high efficiency. Many researchers carried out researches to regulate the operations of BLDC motors. In this research the control of BLDC motor is analyzed. While taking into account reliability and durability, the BLDC motor fails to provide an increased fault tolerance, with decreased electromagnetic interference, acoustic noise, flux ripples, and torque ripple. Torque ripple in a BLDC motor’s is mainly caused due to the variation in the interactions across the stator and rotor as well the electromagnetic fields. So, the research has come up with the solution to the torque ripple using the controllers. By using intelligent power controllers, the output performance can be improved with good power quality and efficiency.

Advanced optimal GA-PID controller for BLDC motor

The brushless direct current (BLDC) motor is characterized by high torque, which made it widely used in many industrial applications. To improve the working performance of the BLDC motor, the addition of controllers such as proportional integral derivative (PID) is adopted. To obtain high-performance controllers, the design process is adopted to develop a suitable algorithm. The genetic algorithm (GA) was chosen to tune the PID controller and get suitable parameters for each of kp, ki and kd with self-tuning. The design process is based on BLDC motor control using the GA to tune the traditional PID controller. Simulations were carried out for three cases including the absence of controllers secondly, by using the traditional control unit and finally with the GA. The integral time absolute error (ITAE) type error control standard for BLDC motor control system was selected. After conducting the simulation, the results demonstrated the superiority of the GA over the traditional ones in terms of response speed, (stability, rise, and settling) time and percentage overshootas details will be mentioned the model in the subsequent paragraphs of the research, finally the simulation results indicate the development and improvement of BLDC motor operation and performance during real time.

Advanced optimal GA-PID controller for BLDC motor

The brushless direct current (BLDC) motor is characterized by high torque, which made it widely used in many industrial applications. To improve the working performance of the BLDC motor, the addition of controllers such as proportional integral derivative (PID) is adopted. To obtain high-performance controllers, the design process is adopted to develop a suitable algorithm. The genetic algorithm (GA) was chosen to tune the PID controller and get suitable parameters for each of kp, ki and kd with self-tuning. The design process is based on BLDC motor control using the GA to tune the traditional PID controller. Simulations were carried out for three cases including the absence of controllers secondly, by using the traditional control unit and finally with the GA. The integral time absolute error (ITAE) type error control standard for BLDC motor control system was selected. After conducting the simulation, the results demonstrated the superiority of the GA over the traditional ones in terms of response speed, (stability, rise, and settling) time and percentage overshootas details will be mentioned the model in the subsequent paragraphs of the research, finally the simulation results indicate the development and improvement of BLDC motor operation and performance during real time.

Closed-loop control of BLDC motor using Hall effect sensors

Due to its key advantages of top performance, strong torque, and simple volume, brushless direct current (BLDC) motors are now extensively employed in a variety of industrial sectors, including the automotive industry, robotics, and electrical vehicles. Yet, in some circumstances, it can be challenging to use speed control techniques for specific devices. The major goal of this work is to use a proportional integral derivative (PID) converter to regulate the speed characteristics of BLDC. PID converter is preferred over all other converters because of its straightforward design and straightforward implementation. Using MATLAB simulation results are verified at different reference speed changing conditions, the motor input current and back electromotive force (EMF) values are verified. The speed and torque characteristics are verified during steady and transient state conduction.

Performance Evaluation of Brushless Direct Current Motor Control Methods through Low-Cost Microcontroller-Based Real-Time Experiments

Brushless direct current (BLDC) motors are high efficiency synchronous motors that are employed in a variety of applications due to prominent features such as long operational life, low maintenance requirements, and great dynamic response. BLDC motors are driven by energizing the motor stator windings with an inverter circuit. To commute the inverter switches, the trapezoidal (120°) method is generally used by considering the back electromagnetic force induced on unenergized phase of BLDC. Furthermore, depending on the application requirements, alternative commutation modes (CM) such as 180°, 150°, and sinusoidal-based approaches are utilized. In the literature, the performance comparison of some CMs was studied for two-phase on operation and three-phase on operation mode as a switching pattern. However, only a few research assessed the performance of two or three commutation modes simultaneously. In this study, the performance comparison of pulse width modulation (PWM) based commutation modes are examined by considering 120°, 180°, 150° modes, and sinusoidal PWM. In this scope, it is the first time that direct digital synthesis (DDS) is addressed as a BLDC control algorithm in a performance comparison study. In experimental studies, a simple and a low-cost drive circuit is designed to acquire the case results. According to the results, the proposed DDS-based sine commutation method is more efficient than other commutation methods and it has lower power consumption at both low and high speeds also a wider operable speed range.

Stability analysis and speed control of brushless DC motor based on self-ameliorate soft switching control methods

In recent years, electric vehicles are the large-scale spread of the transportation field has led to the emergence of brushless direct current (DC) motors (BLDCM), which are mostly utilized in electrical vehicle systems. The speed control of a BLDCM is a subsystem, consisting of torque, flux hysteresis comparators, and appropriate switching logic of an inverter. Due to the sudden load torque variation and improper switching pulse, the speed of the BLDCM is not maintained properly. In recent research, the BLDC current control method gives a better way to control the speed of the motor. Also, the rotor position information should be the need for feedback control of the power electronic converters to varying the appropriate pulse width modulation (PWM) of the inverter. The proposed optimization work controls the switching device to manage the power supply BLDCM. In this proposed self-ameliorate soft switching (SASS) system is a simple and effective way for BLDC motor current control technology, a proposed control strategy is intended to stabilize the speed of the BLDCM at different load torque conditions. The proposed SASS system method is analyzing hall-based sensor values continuously. The suggested model is simulated using the MATLAB Simulink tool, and the results reveal that the maximum steady-state error value achieved is 4.2, as well as a speedy recovery of the BLDCM's speed.

On the Benefits and Limitations of Modulated Damping With Passive Motor Control

Abstract Conventional emulated damping, in which velocity feedback is employed in combination with motor current control to emulate damping, is used in a number of mechatronic applications. As known in the field, although such damping should be strictly passive, several implementation factors render this emulation nonpassive and subject to instability, especially with increasing damping ratios. This paper describes an alternative implementation of emulated damping that employs passive motor control, which does not draw energy from a battery or any other power source. The method is specifically described in the context of a brushless direct-current (BLDC) motor; an unique controller architecture is used along with a particular MOSFET switching scheme which employs only a subset of the standard BLDC motor driver and does not require electronic commutation. This paper employs analytical and experimental means to compare damping control with the described passive motor approach, relative to using a conventional BLDC motor control approach. Stability considerations for each scheme are discussed. Benchtop testing demonstrates the advantage of the passive control scheme in terms of providing smooth behavior, enhancing control robustness, preventing energy leaks, and providing accurate behavior. The special cases of unilateral and asymmetric behaviors (i.e., different damping command for each direction of rotation) are also considered.

Desain Kontrol Motor Brushless Direct Current (BLDC) Menggunakan Boost Converter

Technological developments are increasingly rapid, especially in the field of transportation, especially in electric vehicles, which are triggered by the increasing scarcity of fossil fuels. One of the propulsion engines that are widely used in electric vehicles is the brushless direct current (BLDC) motor because this motor has high torque, constant speed and is easy to regulate. This study aims to design a BLDC motor control using a boost converter as a voltage increaser and using a PID controller as a motor speed controller to keep it constant. In this study, the motor speed is simulated with an input value of 3000 rpm and then a DC voltage of 310 Vdc is given. The results showed that the motor speed regulation using a boost converter can rotate constant. The boost converter as a voltage booster is able to increase the Vin 220 Vdc voltage to a more 10% Vout, which is 242.3 V. Keywords: Brushless Direct Current (BLDC) Motor, Boost Converter, PID

A review on the closed-loop strategy for speed control of BLDC motors

The advancements in the field of materials and force gadgets, coupled with the increased affordability of highperformance processors, have led to a widespread adoption of Brushless Direct Current (BLDC) motors across various industries. These applications range from household appliances to automotive, aerospace, and medical sectors. The widespread use of may be attributed to its manifold advantages over various types of engines, such as its superior efficiency, robust power output, extended operational lifespan, relatively quiet operation, and broader range of achievable speeds. Due to the increasing adoption of Brushless Direct Current (BLDC) motors in many real-life applications as a replacement for traditional motors, this paper aims to compile and evaluate a comprehensive list of control algorithms employed for BLDC motor control. This study discusses several ways for managing speed and current, including hysteresis band control, variable DC-link voltage control, and Pulse Width Modulation (PWM) control schemes. The optimization of Proportional-Integral-Derivative (PID) gains for these controlling techniques is achieved through the utilization of the particle swarm optimization (PSO) algorithm. By employing Fast Fourier Transform (FFT) analysis to examine the controller behavior through frequency analysis of the output signals and calculating the Total Harmonic Distortion (THD), a more advantageous control method may be determined.

Investigation of type 1 and type 2 fuzzy logic controllers performance: application of speed control of BLDC motor

In this paper, a simulation study enhanced to model that the speed control of brushless direct current (BLDC) motors used in electric vehicles with intelligent control methods. The simulation study was prepared in Matlab/Simulink environment. The first control method is Type-1 fuzzy logic control (T1FLC), and the second control method is the Intermittent Type-2 fuzzy logic control (IT2FLC) model. Membership functions for different membership numbers have been created for both types of FLC models. These are 3×3, 5×5, 7×7. Control methods are prepared in Matlab/M-file environment. The model is defined as the input variable of the error, which is the difference between the reference speed and the motor speed, and the output variable of the Pulse Width Modulation (PWM) signal applied to the motor. The simulation study maintains the speed of the BLDC motor up to the reference speed with T1FLC and IT2FLC controllers, depending on the reference speed and applied load values. Depending on the number of different memberships, the effects of controller performances on the control of motor speed have been observed. The graphs and findings of the experiment are shown in the results and discussion section.

A Review of BLDC Motor: State of Art, Advanced Control Techniques, and Applications

Brushless direct current (BLDC) motors are mostly preferred for dynamic applications such as automotive industries, pumping industries, and rolling industries. It is predicted that by 2030, BLDC motors will become mainstream of power transmission in industries replacing traditional induction motors. Though the BLDC motors are gaining interest in industrial and commercial applications, the future of BLDC motors faces indispensable concerns and open research challenges. Considering the case of reliability and durability, the BLDC motor fails to yield improved fault tolerance capability, reduced electromagnetic interference, reduced acoustic noise, reduced flux ripple, and reduced torque ripple. To address these issues, closed-loop vector control is a promising methodology for BLDC motors. In the literature survey of the past five years, limited surveys were conducted on BLDC motor controllers and designing. Moreover, vital problems such as comparison between existing vector control schemes, fault tolerance control improvement, reduction in electromagnetic interference in BLDC motor controller, and other issues are not addressed. This encourages the author in conducting this survey of addressing the critical challenges of BLDC motors. Furthermore, comprehensive study on various advanced controls of BLDC motors such as fault tolerance control, Electromagnetic interference reduction, field orientation control (FOC), direct torque control (DTC), current shaping, input voltage control, intelligent control, drive-inverter topology, and its principle of operation in reducing torque ripples are discussed in detail. This paper also discusses BLDC motor history, types of BLDC motor, BLDC motor structure, Mathematical modeling of BLDC and BLDC motor standards for various applications.

Sensor-less field orientation control for brushless direct current motor controller for electric vehicles

The electric vehicle traction of Brushless Direct Current Motor (BLDCM) is better from other electric machines due to its magnetic flux linkage, power to weight ratio and so on. The conventional Field Orientation Control (FOC) scheme with sensor for BLDCM has few shortcomings like deviation of current and thrust characteristics. In this paper, we have proposed a sensor less FOC for BLDCM. The back emf and speed of machine are estimated using slide mode controller which is given as a feedback to the motor controller part. The results are observed by varying reference speed which results in controlling the speed of machine accordingly. The results are verified by simulation and experimental evaluation. Simulation is done through MATLAB 2020a software and the experimental evaluation is done through Altair Embed Emulator which controls the BLDCM.

Adaptive Fuzzy Neural Network PID Algorithm for BLDCM Speed Control System

Because of its simple structure, high efficiency, low noise, and high reliability, the brushless direct current motor (BLDCM) has an irreplaceable role compared with other types of motors in many aspects. The traditional proportional integral derivative (PID) control algorithm has been widely used in practical engineering because of its simple structure and convenient adjustment, but it has many shortcomings in control accuracy and other aspects. Therefore, in this paper, a fuzzy single neuron neural network (FSNNN) PID algorithm based on an automatic speed regulator (ASR) is designed and applied to a BLDCM control system. This paper introduces a BLDCM mathematical model and its control system and designs an FSNNN PID algorithm that takes speed deviation e at different sampling times as inputs of a neural network to adjust the PID parameters, and then it uses a fuzzy system to adjust gain K of the neural network. In addition, the frequency domain stability of a double closed loop PID control system is analyzed, and the control effect of traditional PID, fuzzy PID, and FSNNN PID algorithms are compared by setting different reference speeds, as well as the change rules of three-phase current, back electromotive force (EMF), electromagnetic torque, and rotor angle position. Finally, results show that a motor controlled by the FSNNN PID algorithm has certain superiority compared with traditional PID and fuzzy PID algorithms and also has better control effects.