BLDC Motor Research Articles

High-Order State-Filtering System Design and Its Application to Feedback Control of a Three-Phase BLDC Motor

High-Order State-Filtering System Design and Its Application to Feedback Control of a Three-Phase BLDC Motor

Efficiency Analysis of BLDC Motor with Delta Connection According to Magnitude of Circulating Current

Efficiency Analysis of BLDC Motor with Delta Connection According to Magnitude of Circulating Current

Enhancing BLDC Motor Speed Control by Mitigating Bias with a Variation Model Filter

Enhancing BLDC Motor Speed Control by Mitigating Bias with a Variation Model Filter

Design of BLDC motor drive system using alternative controllers for performance evaluation in electric vehicle applications

Design of BLDC motor drive system using alternative controllers for performance evaluation in electric vehicle applications

Enhanced Speed Control for BLDC Motors using WOA-Integrated PID Controller Optimization

Enhanced Speed Control for BLDC Motors using WOA-Integrated PID Controller Optimization

BLDC Motor Stability Management Using Adaptive PID (MRAC-PID)

BLDC motors have become popular in various industries such as automotive, consumer, healthcare, industrial automation, and instrumentation due to their optimal performance. To keep the BLDC motor in optimal condition, a control engineering system is required that serves as a controller. A single Proportional Integral Derivative (PID) control system is only suitable for linear conditions, so it cannot produce satisfactory output when there is a change in set point. To overcome this obstacle, an adaptive PID control system known as MRAC-PID control system is applied, which is able to control the stability of the BLDC motor as desired. Testing of this system is done under 4 different conditions using MATLAB software. After testing, the parameter values for the MRAC control system were obtained, namely ???????? = 0.4; ???????? = 50.75; ???????? = 0.0000867. Based on the test, the MRAC control system produces a system success rate of 81.2% to 98.9%.

Badania przyczyn niepożądanej synchronizacji prędkości obrotowej silnika z częstotliwością modulacji PWM w układzie napędowym PM BLDC

In a drive system comprising a high-speed PM BLDC motor and an inverter implementing motor phases commutation and phase voltages PWM modulation, a spontaneous synchronisation between the PWM modulation frequency and the motor rotational speed may occur. The drive behaves like an unintended phase-locked loop. The effect distorts mechanical characteristic of the drive by introducing flat segments where the rotational speed remains constant despite changing load torque. It makes the speed-torque relationship discontinuous, nonlinear, and non-unique. The phenomenon is closely related to the problem of phase current and motor torque ripples. The paper presents experimental results recorded with a laboratory test bench for drives for electric power tools where the phenomenon of the parasitic speed locking has been observed. A root cause of this effect is discussed, and the mechanism of unwanted synchronisation is investigated. Several mitigation techniques are proposed and verified with computer simulations.

Design and Co-Analysis of A Permanent Magnet Brushless DC Motor By Using Clonal Selection Principle Based Wound Healing Algorithm and Ansys-Maxwell

This paper presents the design and analysis of a 550 W Permanent Magnet (PM) Brushless DC motor (BLDC). The finite element method (FEM) was employed to assess the motor's performance characteristics. The design and dynamic performance analysis were conducted using ANSYS/Rmxprt, while electromagnetic studies were carried out using ANSYS/Maxwell-2D. Additionally, optimization of the DC motor was achieved through a Wound Healing Algorithm (WHA). A PID controller was designed for this purpose. The paper also elaborates on the detailed design equations for creating a BLDC motor. BLDC motors are known for their high dynamic responses, efficiency, extended operating life, wide speed change intervals, and noise-free operation. The motor's geometry was modeled in the ANSYS-Maxwell-Rmxprt software tool and later imported into the Maxwell-2D environment for further analysis. The designed motor was observed to operate with 93% efficiency, meeting the specified torque value. The results of the optimization process were interpreted by comparing them with the values obtained from the ANSYS software.

RANCANG BANGUN SISTEM PENGEMUDIAN ELEKTRIK PADA MOBIL LISTRIK AGNIJAYA WEIMANA

Electric energy can be used as a substitute for oil fuel. One of the efforts to address air pollution is through the Energy-Efficient Car Contest (KMHE), which emphasizes vehicle efficiency. In this study, the electric propulsion system in the electric car WEIMANA, which focuses on the selection of an electric motor, conducted tests on a BLDC motor to determine the required power of the BLDC motor. In the selection of the electric motor, calculations were made for rolling resistance, aerodynamic resistance of the car, power, and required torque. Based on the discussion's results, the chosen motor is the qs-motor brand with a capacity of 800 W, 500 RPM, torque of 80 Nm, and operating voltage of 48 – 70 VDC. The magnitudes of rolling resistance, aerodynamic resistance of the car, power, and torque are 16.67 N, 7.83 N, 864.7 W, and 59.22 Nm, respectively. The selected motor has been able to propel the WEIMANA car with driver weights of 45 kg, 55 kg, and 65 kg at speeds of 20 km/h and 30 km/h. The highest average power efficiency of the controller is 90.31% with a driver weight of 55 kg. The highest average power efficiency of 88.03% is achieved at a speed of 20 km/h.

Control System for Swerve Drive Wheeled Automated Guided Vehicle with Ultra-Wide Band Local Positioning System

Control system for Automates Guided Vehicle (AGV) is used to control the motor movement so that the AGV can go to a position in certain speed and orientation. Discussion in this paper is about how to control 4-wheel swerve drive-based AGV. Mechanical structure of each wheel is built in such a way that the wheel can move forward / backward and the orientation can be adjusted while moving. Each wheel requires two BLDC motors to drive and to steer the AGV. In this project, the power each motor is 200W which is drove and controlled by Syntron LS20530G motor driver that connected to a computer via CAN-bus. An Ultra-Wide Band (UWB)-based Local Positioning System (LPS) is used to monitor the position of the AGV as well as a guide for non-physical paths so that AGV moves according to a given path virtually. The experimental results show that AGV can move in a straight line with a speed of 50m/min. Wheels can also be steered according to a certain angle so that the AGV can move towards the destination point. The steering angle of each wheel is between -135 degrees to 135 degrees.

Optimal configuration of the artificial neural network to estimate the speed of the BLDC motor

Optimal configuration of the artificial neural network to estimate the speed of the BLDC motor

Exploring the Cargo Potential: A Comprehensive Analysis of Kertajati Airport

Motorized vehicle can’t be apart from our daily activity, because it’s very significantly save our time and energy. According to Erwin (in Sasongko, 2014: 1) mentioned air pollution that comes out from motorized vehicle is very high, so it can pollute the environment and harm human health. Besides, the fossil fuel is an unrenewable which is running low and will cause an energy crisis. So we need alternative energy that is more eco friendly, common, and easy to obtain. Therefore, electric vehicle are one solution to this problem. Electric vehicle is a fuelless vehicle that ran by electric motor with battery for the energy supplier. In accordance with the Kepmen ESDM No. 13 Tahun 2020 about “that to increase the energy efficiency, energy resilience, and energy conservation in transportation sector, it needs to accelerate the battery-based electric motor vehicle program” so that it is necessary to develop innovations to support electric vehicle infrastructure in Indonesia. BLDC Motor is one of the motor type that used in electric vehicle. BLDC Motor used by one of the electric vehicle brands in Indonesia named GESITS, experienced an overheat on the BLDC motor after travelling 30 kilometers around Bekasi (GESITS, 2016). Finally to add cooling to the BLDC Motor, an external fan is installed. This experience shows the importance of cooling to maintain BLDC Motor durability. In addition to cooling the electric motor, it is necessary to pay attention to the efficiency produced by the electric motor. So that it can make consideration of battery consumption on the motorcycle design. Based on the problems above, this research will analyze the efficiency and thermal of a 3000 Watt BLDC Motor in the design of an electric motorcycle. The data collection will be carried out by using the Dynotest tool or Chassis Dynamometer to obtain amount of power, torque, electric current and thermal on the electric motor being tested. From these data calculations will be carried out for the efficiency of a 3000 Watt BLDC Motor. So that this research can be used as a reference for the further development of electric vehicles.

Power quality improvement in BLDC motor drive using PFC converter

The use of brushless DC motors (BLDC) in low-power appliances is increasing because of their features of high efficiency, wide speed range, and low maintenance. This project deals with a power factor correction (PFC) based BL Landsman converter-fed brushless DC motor drive as a cost-effective solution for low-power applications. The speed of the BLDC motor is controlled by varying the DC-link voltage of the voltage supply electrical converter feeding the BLDC motor drive. A low-frequency switch of the VSI is used for achieving the electronic commutation of the BLDC motor for reduced switch losses. The PFC-based letter of the alphabet device is designed to control in discontinuous inductance current mode; therefore utilizing a voltage follower approach which needs one voltage sensing element for dc-link voltage management and PFC operation. The projected drive is meant to control a large variety of speed management with improved power quality at AC mains. The performance of the projected drive is valid with experimental results obtained on a developed epitome of a PFC device. This manuscript deals with the configuration of a power factor correction converter feeding a drive of brushless DC motors for medium and low-power equipment. The DC link voltage of the drive system is maintained by a single DC voltage actuator. Two control converters for the BLDC motor drive have been implemented. The control strategy is based on a PFC-Landsman converter-fed BLDC motor drive. Comparison has been made in PI controller-based converter in terms of minimizing ripple and improving the power factor of BLDC Motor drive. The proposed work has been implemented under MATLAB/Simulink environment

Sensorless speed and position control of permanent magnet BLDC motor using particle swarm optimization and ANFIS

This paper describes the operation of a Permanent Magnet Brushless Direct Current (PMBLDC) motor without a position sensor. In this case, the sensorless operation is enhanced by an effective hybrid technique that detects the back electromotive force (Back EMF) of the zero crossing point (ZCP) from the terminal voltages. The Adaptive Neuro Fuzzy Interference System (ANFIS) controller, which is based on Particle Swarm Optimization (PSO) and uses PSO to train its operation, is combined in the proposed hybrid analysis. The PMBLDC motor's ANFIS controller receives the line voltages as input, and it uses this information to estimate the sample signals that are then sent to the ZCP detection circuit. Appropriate commutation control of the inverter is generated by the ZCP detecting circuit. By varying the ANFIS consequent parameters, the PSO algorithm iterates until the error between the sample output and the real training data reaches a low value. The MATLAB/Simulink platform is utilized to implement the suggested sensorless controller action. To verify the controller's performance, a comparison with the other soft computing methods is also carried out.

A Crossover Optimization-Based Control for Making Strides in BLDC Motor Utilizing Renewable Sources

This study explores the eco-friendly and versatile applications of renewable energy sources, with a focus on solar modules adaptable to varying conditions. The objective is to minimize switching loss and enhance Total Harmonic Distortion (THD) outcomes. Solar energy harnessed from PV panels is utilized to power a BLDC motor, employing two methods to amplify PV panel output. In the initial approach, Maximum Power Point Tracking (MPPT) is implemented using a hybrid PSO and cuckoo-searches (HPSO_CSO) technique. The second method integrates an AC load through DC-DC converters connected to a BLDC motor and a multilayer inverter. Comparative analyses encompassing maximum power, stator current, THD, and duty cycle are conducted for both the conventional PSO-based BLDC and the proposed HPSO_CSO BLDC systems. The findings reveal that the suggested HPSO_CSO converter with BLDC motor outperforms existing methods, exhibiting the most favorable outcomes. The entire system is simulated using the SIMULINK model, with MATLAB 2021a employed for implementation. The proposed HCSO-PSO-MPPT approach achieves an impressive THD of just 1.08%, signifying superior power conversion performance in contrast to existing techniques.

BI - Directional Operation of BLDC Motor for Electric Drives

BI - Directional Operation of BLDC Motor for Electric Drives

An intelligent PID controller tuning for speed control of BLDC motor using driving training-based optimization

Tuning of proportional-integral-derivative (PID) controller remains a matter of great concern for the control engineers as it plays a major role to obtain optimal performance of any system Due to their simplicity and excellent efficiency, metaheuristic algorithms have recently become extremely popular among researchers for handling a wide range of real-world optimization challenges. In order to optimize a PID controller for managing the speed of a BLDC motor, this work proposes a novel application of the driving training-based optimization (DTBO) algorithm, one of the latest and most recent human-based metaheuristic algorithms. The purpose of this present study is to optimize a PID controller for a BLDC motor speed control by DTBO method and evaluate its performance with a similar controller tuned by grey wolf optimization (GWO) method. Additionally, the suggested DTBO-PID controller's robustness analysis is being carried out with BLDC motor parameter modifications as well as a comparison to the GWO-PID controller. The comparison is carried out in MATLAB/Simulink, and the results are based on common step response metrics such rise time, settling time, and maximum overshoot. For easier comprehension, the results are presented in tabular and graphical form. The chosen BLDC motor drive system's selected DTBO-PID controller performs better and is more reliable than the GWO-PID controller, according to the final simulation findings.

Energy management of solar photovoltaic fed water pumping system based BLDC motor drive using NBO–SDRN approach

Energy management of solar photovoltaic fed water pumping system based BLDC motor drive using NBO–SDRN approach

Simulation of Energy Dissipation in BLDC Motor and Analysis of Speed-Acoustic Characteristics

The hybrid electric vehicle combines dual propulsion systems: one employs the traditional internal combustion engine, while the other utilizes a PMDC or BLDC motor. Generally, BLDC motors exhibit an efficiency of 85% to 90%. Conversely, the PMDC motor inherently achieves an efficiency of 88% under optimal running conditions. Moreover, improving the efficiency of both motors is impeded by their design constraints. Power losses in these motors primarily stem from factors such as heat generation in the rotor (I²R losses), bearing friction, vibrations, and noise. This paper aims to investigate energy loss in a 4 kW BLDC motor manufactured by Bosch, attributable to speed-induced acoustic noise effects. Harmonic analysis of the phase current reveals the presence of odd-order harmonics, specifically those below the 11th order, resulting in current ripples. These dominant harmonic frequencies interact, ultimately generating noise and consuming a certain amount of power. These predominant frequencies correlate with fundamental electrical parameters: current frequency (Hz), RMS current (A), and threshold (%r), all associated with the motor's input power source. The 'K' factor, a parameter dependent on these three electrical factors, is calculated to determine harmonic stability. Variations in stable speeds (ranging from 1280 to 7500 RPM) are used to record 'K' factor readings. Based on IEEE Standard 85-1980 guidelines, motors are classified as either acceptable (OK) or not acceptable (not OK) according to their harmonic stability 'K' factor. Readings for each speed step are captured at a specific predominant frequency, facilitating subsequent comparisons. To validate the experimental findings, MATLAB/Simulink and a Fluke scope meter are employed to conduct power analyses for each motor, thus assessing energy loss attributed to noise. The waveform of the phase current proves instrumental in quantifying energy consumption in the BLDC motor. Notably, higher-frequency noise waves with shorter wavelengths entail greater energy consumption. Evaluating energy loss significantly contributes to the analysis of BLDC motor speed acoustics, serving to inform the design of energy-efficient hybrid electric vehicle models powered by BLDC motors, which are intended for customer service.

21 Level Asymmetric Inverter without Inversion Circuit with Reduced Switch Count for BLDC Motor Drive

21 Level Asymmetric Inverter without Inversion Circuit with Reduced Switch Count for BLDC Motor Drive