Brushless Direct Current Motor Performance Research Articles

Multi-Step Design Optimization for the Improvement of an Outer-Rotor Brushless Direct Current Motor

Brushless Direct Current (BLDC) motors have seen significant improvements across various electrical applications. The growing focus on motor design research highlights the BLDC motor’s superior efficiency compared to traditional motors, which consume more power. BLDC motors are compact, lightweight, energy-efficient, and easy to control, making them ideal for modern applications. This study aims to enhance BLDC motor design and performance by employing the Taguchi method, Response Surface Methodology (RSM), and Finite Element Method (FEM) for multi-stage optimization. A 26-watt BLDC electric fan motor is the reference model for this study. The Taguchi method helps identify optimization points, guiding further enhancements in the second stage. The study proposes a design with improved output power, torque, and efficiency. The final design achieves a 15% higher energy efficiency than the reference model, with a 10 W increase in output power and a 0.032 Nm increase in maximum torque. The FEM analysis using JMAG software v 21.2 validates the proposed design, which shows improved configurations compared to the reference model, demonstrating the efficiency of the optimization techniques for BLDC motor design.

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.

Effect of Slot-Pole Numbers on the Performance of a BLDC Motor for Agro-EV Application

This paper analyzes the performance of a brushless direct current (BLDC) motor for agro electric vehicle (agro-EV) applications. Agro-EV technology is being developed in response to increasing environmental pollution. Various types of electric motors are in agro-EV, one of which is the BLDC. With its good capabilities, it has been chosen for further exploration in this research. On the other hand, some issues limit the usage of the conventional BLDC motor in heavy applications, such as low torque performance caused by weak magnetic energy. Therefore, this research aims to analyze the effect of magnetic energy based on slot-pole combinations to evaluate the BLDC motor's performance. Three BLDC models with different slot-pole numbers are designed and simulated using a fixed structure size, permanent magnet volume, and magnetomotive force (MMF). Finite element method (FEM) software known as Altair Flux 2D is used to compute the cogging torque, back-electromotive force (BEMF), magnetic flux density, and the torque produced. As a result, an 18/20 slot-pole was chosen for its high torque (105 Nm) and BEMF (35.9 V). In conclusion, this research simulation presents guidelines and an overview regarding the effect of slot-pole numbers on the performance of the BLDC motor for agro-EV applications.

Performance and Energy Consumption of Paddle Wheel Aerator Driven by Brushless DC Motor and AC Motor: A Preliminary Study

Energy demand for paddle wheel aerator in a shrimp pond is high and brings to second highest cost of operational behind feed supply. Most of wheel aerators are driven by electric motors than diesel engines as their easy operations. The electric motors need high electrical energy to drive wheel aerators along day and night. The common type of motor used is Alternating Current (AC) or induction motor, however Brushless Direct Current (BLDC) motor has potential electrical energy saving which need to be explored. This study objectives to find out performance of BLDC and AC motor as paddle wheel aerator driver. The motor’s performances were compared in term of operation of paddle wheel at various static loads. Both motor also challenged by On/Off running every 5 minutes, the treatment goal was to determine their reliability. Parameters observed included consumption of power, wheel rotary, torque, and efficiency, motor temperature as well. Results showed energy consumption of BLDC motor 51% lower than AC motor, and BLDC motor attained 89.99% of maximum efficiency while AC motor efficiency had 73.16%, however rotary wheel and torque both of them were similar. The On/Off treatment caused rising temperature of AC motor but did not affect the temperature of BLDC motor. Therefore, applied BLDC motor as paddle wheel aerator driver could be alternative way to reduce energy consumption without reducing its performance.

Dynamic modeling, simulation, and parameter study of electric quadrotor system of Quad-Plane UAV in wind disturbance environment

Quad-Plane UAV(quadrotor fixed-wing hybrid vertical take-off and landing Unmanned Aerial Vehicle) is vulnerable to wind disturbance in quadrotor mode, and the performance of the electric quadrotor system directly affects its wind disturbance rejection performance. To study and optimize the wind disturbance rejection performance of the electric quadrotor system of Quad-Plane precisely and efficiently, a dynamic electric quadrotor simulation system integrating high-precision submodels of electric quadrotor system components is required. However, there are few papers on this kind of simulation system. This paper proposed a simulation system with both high computational efficiency and precision, and it can be used in optimization and flight simulation of Quad-Plane. The simulation system includes submodels of rotor, brushless direct current (BLDC) motor, electronic speed controller (ESC), and Li-ion Polymer battery. The surrogate-based rotor model is established to calculate the aerodynamic performance of the rotor in oblique flow. The BLDC motor performance calculation model considering inductance is presented and the power loss of the ESC is considered. The discharge characteristics of the battery are modeled considering the rate capacity effect. All submodels are validated and the simulation results show good agreements with test data. A flight test of Quad-Plane in quadrotor mode is conducted to validate the integrated dynamic simulation system. The results show that the simulation system has the advantages of high computational efficiency and precision. Based on the simulation system, the influence of the electric quadrotor system parameters on the performance of the electric quadrotor system, and furthermore on the wind disturbance rejection performance of the Quad-Plane are found, the conclusions are helpful to the selection and optimization of the electric quadrotor system components.

Speed Control Using Fuzzy Controller for a Four Switch Sensorless BLDC Motor

- Brushless Direct Current (BLDC) motors are highly efficient motors with high reliability and a longer life span. The advent of sensor less technology has improved the performance and reliability of BLDC motor drives. This work is to analyze a drive system for BLDC motor with Four-Switch Three-Phase Inverter (FSTPI). Back Electromotive Force (EMF) Zero Crossing Detection (ZCD) method is used to estimate the rotor position. Speed control of motor is achieved by using Fuzzy Logic Controller (FLC) based closed loop control system. The Simulation was carried out using MATLAB software and motor the performance was analyzed with FLC for motor speed regulation.

Design and Experimental Investigation of BLDC Motor for Aircraft Electromechanical Actuator

Among the electric motors used in the aircraft industry, brushless direct-current (BLDC) ones have the highest power density and efficiency. This paper presents the BLDC motor design and electromagnetic analysis for use in direct-drive aircraft electromechanical actuator. An experimental BLDC motor prototype has been made to test the output. Finite-element analysis (FEA) has been applied to finalize and investigate the characteristics of the BLDC motor design. Then, FEA output has been compared to experimental results in order to validate the latter. The high specific torque has been attained by the 12-slot, 8-pole configuration. Segmenting the rotor magnetic pole has reduced loss to eddy currents in permanent magnets, while double-layer concentric winding has reduced loss to copper and more effective dissipated heat. The BLDC motor presented herein has short response time and high rotor rotational angle precision thanks to the high torque to rotor moment-of-inertia ratio. For evaluating BLDC motor performance assessment, experiments have been run stand-alone, i.e. with no integration in a gearless EMA. Rotational speed vs torque, as well as the holding torque vs phase current at a given BLDC motor rotor position fit well the FEA output at a maximum difference of 10%. Post-test residual magnetization readings of the permanent magnets proved the BLDC motor operable.

Modeling & design of a ANN controller for a BLDC motor on Propulsion Application for Hybrid Electric Vehicle

This paper proposes the brushless direct current (BLDC) motor with high power density and high efficiency characteristics may be used to propulsion framework for electric vehicle. The progressive model for BLDC motor under rotor flux linkage route reference frame might have been providing. Here we analyzed the chart of ann vector and principal of ann control strategies and proposing the ann based reactive power with BLDC motor. To make ann based framework on active power, torque ripple, dc voltage, power factors can be used BLDC motor was designed. After designed simulation results was test the validity of field weakening based on reactive power with BLDC for electric vehicle application. In this research work will introduced artificial neural network (ANN) for non electrical input used. To control the BLDC motor speed it can using pulse width modulated control of the voltage source inverter (VLSI) using DC link voltage (Vdc) controller. To perform electronic commutation by hall signal sensing they are using PWM signal, to generate PWM signal inbuilt encoder can be used in this circuit. Analyze the BLDC motor performance driving propulsion framework is carried out under the MATLAB/Simulink software’s and efficiency of whole frame work is calculated under various source conditions

Analysis of the Effect of the Motor Temperature to Brushless Direct Current Motor Performance on KARLING Electric Vehicle

Indonesia is a country that has tropical climate with average temperature vary in between 27°C until 37°C. BLDC motor industry is not common in Indonesia so that has to be imported from another country mostly subtropical countries. BLDC motor is built according to subtropical characteristics. Therefore, BLDC motor performance is changing in Indonesia due to the temperature differences. The following methods are used in the study: laboratory experiment and field test using electrical vehicle. The temperature in laboratory is in range between 23°C up to 55°C. However the field temperature varies from 27.7°C and 34, 2°C. The increasing temperature inside the motor in laboratory and field experiments conducts modification of BLDC motor parameters. The rising motor temperature degrades the current and torque of motor, but increasing the rotation velocity of the motor.

Analysis of The Influence of Loading Variations Toward Brushless Direct Current Motor Performance on KARLING Electric Vehicle

One type of electrical motors often used for electric vehicle purposes is Brushless Direct Current Motor (BLDC Motor). BLDC motor performance can be seen from its current line, electromagnetic torque, rotational speed, induction voltage, and input power as the parameters. The research’s aim is to find out the effect of loading towards BLDC motor performance on the electric vehicle. The loading variations are used in the form of passenger weight and track characteristics variations. The variation of passengers’ weight is 55 kg, 78 kg, and 143 kg. In this study obtained line current value when the passengers load 143 kg is 41.52 A. Furthermore, the values of the electromagnetic torque and energy consumption in the same weight are 23.88 Nm and 0.06 kWh/km. To ascertain the effect of track characteristics variations to the motor parameter, variations of track characteristics are done in trajectory 0° and 1.25°. The outcome is the 1.25° tilted track has higher energy consumption but lower speed.

Sensorless Drive of High-Speed BLDC Motors Based on Virtual Third-Harmonic Back EMF and High-Precision Compensation

For brushless direct current (BLDC) motor applications, one of the most concerning points in the drive system is the commutation error, which will deteriorate the whole system performance, especially in a high-speed range. Unfortunately, the commutation error is hard to be unitedly eliminated since many non-ideal factors will impact the precision of commutations. To remedy this problem and improve the sensorless drive performance, a novel sensorless control and compensation scheme based on virtual third-harmonic back electromotive force (EMF) combining BEPF-SFE (back EMF power factor combining synchronic-frequency extractor) has been developed. In the proposed method, the virtual third-harmonic back EMF based method is applied to a sensorless drive high-speed magnetically suspended BLDC motor. At the same time, the commutation error is actively compensated by BEPF-SFE-based compensation. An experimental high-speed blower setup is built for evaluating the developed high-speed BLDC motor performance. The effectiveness of the proposed algorithm is validated both through mathematical analysis and experimental results.

Enhancement of Variable Speed Brushless DC Motor using Neural Network

Background/Objectives: Direct Current (DC) motor plays an important role, especially in the industry as it is used in various applications as consequences from its unique characteristic. However, some limitations of variable speed DC motor cause the application of DC motor become less effective whereas some available speed controllers have difficulties in controlling the motor speed. An improved design based on neural network controller for the Brushless Direct Current (BLDC) permanent magnet motor drives is introduced in this paper. The variable input speed is applied to the controller in order to maintain the BLDC motor output speed. Methods/Statistical Analysis: In the proposed enhanced scheme, the mathematical model of BLDC motor and a back propagation Artificial Neural Network (ANN) algorithm are considered and included to replace the conventional method of Proportional Integral Derivative (PID). The proposed ANN algorithm is based on the plant information, where the number of input and output neurons in each layer of the network are designed to be equivalent to the input and output number of signals of the proposed system. The architecture of the proposed ANN controller is designed to has a 2-3-1 structure of the network, where the two input neurons will exist in the input layer. For the first incoming neuron is the different signal among the desired and the real signal. Meanwhile, the second input neuron illustrates the differ between earlier error signal and the ongoing error signal. The network parameter is updated once the process for learning model is defined to ensure the ANN is appropriate to be applied in the proposed system and meet the motor features. Findings: From the analysis, the output error of the system effectively decreases once the training method is implemented where sufficient training dataset for the input-output mapping plant is significantly acquired. The analysis of overshoot, rise time and steady state error for the speed range between 1000 and 1500 rpm indicates that the proposed Neural Network Control (NNC) technique has successfully improved the performance of the BLDC motor drive and outperforms the conventional state-of-the-art methods. Applications/Improvements: The complete simulation model of BLDC motor using NNC controller has been developed. In order to make it more effective, the implementation of the simulation work into the real hardware to investigate the performance of BLDC motor become more interesting. Besides, the NNC controller can be implemented in other applications such as DC-DC converter, permanent magnet synchronous motor or servo motor.