Brushless DC Motor Control Research Articles

Matlab/Simulation of Brushless DC motor vector control

Based on improving the dynamic and static performance of the brushless DC motor control system, a speed current closed-loop brushless DC motor control scheme is designed by using SVPWM. In the light of the environment of matlab/simulink, the vector control model of BLDCM is established by using the control strategy of id=0 and the idea of modularization. The simulation results show that the system has good dynamic and static performance and stable operation, which proves the reliability and effectiveness of the simulation model.

Speed-Sensorless DTC of BLDC Motor with EKF-based Estimator Capable of Load Torque Estimation for Electric Vehicle

This study presents the simulation of brushless DC (BLDC) motor control in MATLAB/Simulink simulation environment with model-based and direct torque control (DTC) method with extended kalman filter (EKF). In this study, a control method based on DTC method is tested to control a nonlinear BLDC motor with extended kalman filter. In this method, an accurate control can be made thanks to the load moment estimation, which is not found in the literature. As a result of the tests have carried out at low and high speeds, it is concluded that the system can lead to real-time systems.

Speed Control of BLDC Motor With Ripple Effect Reduction Using Recurrent Wavelet Neural Networks

The interest in research and use of the Brushless DC (BLDC) motor has increased significantly over the last few years, due to development of electric vehicles (EV) as well as to its use in other growing areas. With further predicted growth of the EV industry, it is expected that the BLDC motor will become even more significant. BLDC motor is a highly nonlinear, dynamic system, which in terms of its control makes tuning of controllers difficult, especially when high precision is required. Because of its operating principle BLDC motor also has issues with torque ripple which affects the speed response in a speed controlled system. In this paper an intelligent controller that combines a proportional-integral-derivative (PID) controller with a recurrent wavelet neural network is proposed. By using an intelligent controller, as an adition to a standard PID, the approximation ability of neural networks is used not only to deal with the nonlinearity of the system, but also to reduce the torque ripple influence on the speed response. By computer simulations it is verified that the proposed controller is able to completely neutralize the ripple effect and achieve good transient speed response. It is also shown that improved robustness against load disturbance compared to the system containing only a PID controller is achieved.

Sensored speed control of brushless DC motor based salp swarm algorithm

<p>This article uses one of the newest and efficient meta-heuristic optimization algorithms inspired from nature called salp swarm algorithm (SSA). It imitates the exploring and foraging behavior of salps in oceans. SSA is proposed for parameters tuning of speed controller in brushless DC (BLDC) motor to achieve the best performance. The suggested work modeling and control scheme is done using MATLAB/Simulink and coding environments. In this work, a 6-step inverter is feeding a BLDC motor with a Hall sensor effect. The proposed technique is compared with other nature-inspired techniques such as cuckoo search optimizer (CSO), honey bee optimization (HBO), and flower pollination algorithm (FPA) under the same operating conditions. This comparison aims to show the superiority features of the proposed tuning technique versus other optimization strategies. The proposed tuning technique shows superior optimization features versus other bio-inspired tuning methods that are used in this work. It improves the controller performance of BLDC motor. It refining the speed response features which results in decreasing the rising time, steady-state error, peak overshoot, and settling time.</p>

RANCANG BANGUN CONTROLLER BLDC BERBASIS MIKROKONTROLER STM32 BLUE PILL PADA KENDARAAN LISTRIK URBAN AGNIJAYA WEIMANA

The increase in the consumption of fuel oil causes the depletion of fossil fuel reserves. One alternative energy solution that can be utilized is electrical energy. One of the efforts to overcome the energy crisis can be realized in a creativity in the energy efficient car contest (KMHE). The Weimana Team of Udayana University participated in the urban concept category of electric motor drive under the name Agnijaya Vehicle. One important aspect in order to be able to compete and win the competition is the Motor Controller. In this paper, the results of the research are presented on a design of a Brushless DC Motor Controller based on the STM32 Blue Pill microcontroller and used to rotate the BLDC motor on the Agnijaya Weimana Urban Electric Vehicle. The specifications of the BLDC controller design are made to have a power dissipation inverter with a power of 1980 Watt connected to an 800 Watt sensored BLDC motor. The STM32 Blue Pill microcontroller-based Brushless DC Motor Controller has been successfully designed and manufactured and produces a sinusoidal output waveform containing switching noise when connected to a no-load BLDC motor. The performance to drive Agnijaya Wimana's Urban Electric Vehicle is capable of implementing a PWM duty cycle of up to 100% with an average current achievement of 24,775 Ampere, an average voltage drop of up to 48,485 VDC, an average power rating of up to 1200,5 Watt and a BLDC motor speed up to 419,5 RPM.

PV FED Interleaved Boost Converter for BLDC Motor

Abstract: The generation of solar energy and its conversion techniques gained greater importance due to increase use of electricity. The power generation scheme is more striking due to its advantages among all the Renewable Energy Sources. This project introduces a PV fed interleaved boost converter for BLDC motor, which is a simple, cost effective and efficient brushless DC (BLDC) motor drive for solar photovoltaic (SPV) array system. A interleaved boost converter is used in order to extract the maximum available power from the SPV array. This control algorithm eliminates phase current sensors and adapts a fundamental frequency switching of the voltage source inverter (VSI) hence avoids the power losses due to high frequency switching. In speed control of BLDC motor no additional circuitry or control is used. An appropriate control of interleaved boost converter is done by the incremental conductance maximum power point tracking (INC-MPPT) algorithm which offers soft starting of the BLDC motor. The proposed system is designed and modelled at steady state conditions of practical operating conditions is demonstrated through simulation results using MATLAB/ Simulink.

Fuzzy PI Control of Trapezoidal Back EMF Brushless DC Motor Drive Based on the Position Control Optimization Technique

In this article, a novel methodology has been created based on optimized fuzzy PI controller using position control optimization (PCO). This proposed PCO algorithm ensures better control of brushless direct current motor (BLDCM) in order to reduce steady-state error and oscillation as well as improve the system response by optimizing the speed and position of rotor. The suitability of this technique has been simulated in different stages, so as to infer the optimization in results. The main motivation of this paper is to get better efficiency and optimum response from BLDCM, by comparing its performance characteristics with existing methods. The detailed investigation research through simulation is carried out using MATLAB/Simulink. However, in order to obtain well-defined results, the PCO technique was applied and the performance obtained was highly optimized than previously applied techniques. Through the simulations, the proposed approach can outperform the existing approaches such as PSO and moth-flame algorithm (MFA).

Solar PV Array Fed Single Stage BLDC Motor Drive for Water Pumping System

A single-stage photovoltaic-fed field-oriented controlled brushless DC (BLDC) motor drive for water pumping using a 2-degree of freedom (DoF) controller is presented in this paper. The proposed 2-DoF controller consists of a feedback and feedforward loop design. A feedback loop is used to maintain stability and desired performance, in which the PI controller is utilized for controlling the DC voltage at the outer loop, which generates the necessary speed reference. A Fuzzy logic controller is then used in the inner loop to achieve a faster speed response of the BLDC motor. Further, the performance of the system is made faster by incorporating dynamic feed-forward control. MATLAB Simulink is used to design and simulate the system. The OPAL-RT simulator is used to validate the system’s performance in real-time.

Parameter Tuning Method for the Controller of Brushless DC Motor Based on Coyote Algorithm

Parameter Tuning Method for the Controller of Brushless DC Motor Based on Coyote Algorithm

Chaos control and characterization of brushless DC motor via integral and differential fractal-fractional techniques

ABSTRACT Although brushless DC motors have been preferably used in wide industrial applications on the basis of superior properties and stable operation, the stability of brushless DC motors is found to be dependent on their chaotic characteristics and initial operating conditions. Owing to such characteristics, this article presents the chaos control and chaotic characteristics of brushless DC motors through newly defined mathematical techniques, so-called fractal-fractional differentiations. Mathematical modeling of the governing equations of the brushless DC motor has been developed by means of Caputo, Caputo-Fabrizio and Atangana-Baleanu fractal-fractional differential operators. The sensitive initial conditions and vibrant parameters have been analyzed for the comparative performance and assessment of the brushless DC motor. The numerical simulations of fractal-fractionalized governing equations of the brushless DC motor have been performed by means of the Adams-Bashforth-Moulton method using MATLAB package. Finally, the graphical illustrations have been underlined for the proposed Caputo, Caputo-Fabrizio and Atangana-Baleanu fractal-fractional differential operators subject to the chaotic behaviors investigated for the brushless DC motor.

Optimal Tuning of the Speed Control for Brushless DC Motor Based on Chaotic Online Differential Evolution

The efficiency in the controller performance of a BLDC motor in an uncertain environment highly depends on the adaptability of the controller gains. In this paper, the chaotic adaptive tuning strategy for controller gains (CATSCG) is proposed for the speed regulation of BLDC motors. The CATSCG includes two sequential dynamic optimization stages based on identification and predictive processes, and also the use of a novel chaotic online differential evolution (CODE) for providing controller gains at each predefined time interval. Statistical comparative results with other tuning approaches evidence that the use of the chaotic initialization based on the Lozi map included in CODE for the CATSCG can efficiently handle the disturbances in the closed-loop system of the dynamic environment.

Design and Control of Brushless DC Motor Drives for Refrigerated Cabinets

The purpose of this study is to develop a variable frequency brushless DC motor drive for the compressors of refrigerated cabinets. It is based on the microcontroller unit (MCU) produced by Renesas Co., Ltd. using the space vector pulse width modulation (SVPWM) for the modulation of the inverter. In addition, at the AC power supply side of the inverter developed, a circuit for suppressing electromagnetic interference (EMI) and a power factor corrector (PFC) are integrated to control the power factor (PF) at the AC power supply side to be above 0.95, which is far better than the commercially available inverters with a power factor of only 0.5. Finally, an intelligent variable frequency control approach based on the extension theory is designed to classify the rotational speed difference and the rate of change in rotational speed difference between the rotational speed commands and the actual rotational speed of the compressor into 20 zones. Then, for the rotational speed difference and the rate of change in rotational speed difference actually measured, their correlations to the 20 zone categories are calculated to determine an appropriate rotational speed command. The temperature of the refrigerated cabinets can quickly be determined to reach the set target value. The proposed extension speed control is simple in computation and does not require much learning data, making it easy to implement. Furthermore, the drive developed is verified by actual testing and its performance is compared to the compressor drives of the refrigerated cabinets commercially available. It is proved that the performance of the drives developed is indeed far better than that of the drives commercially available.

SCHEMING OF CONTROLLER FOR SINGLE STAGE SOLAR PV FED BLDC MOTOR-DRIVEN WATER PUMP

To optimize the solar photovoltaic (PV) generated power using a maximum power point tracking (MPPT) technique, a DC-DC conversion stage is usually required in solar PV-fed water pumping which is driven by a brushless DC (BLDC) motor. This power reformation stage leads to an increased cost, size, difficulty, and decreased efficiency. As a unique solution, this work addresses a single-stage solar PV energy conversion system feeding a BLDC motor pump, which eliminates the DC-DC conversion stage. A simple control technique capable of operating the solar PV array at its peak power using a common voltage source inverter (VSI), is proposed for BLDC motor control. The proposed control eliminates the BLDC motor phase current sensors. No supplementary control is associated with the speed control of the motor pump and its soft start. The speed is controlled through the optimum power of the solar PV array. The suitability of the proposed system is exhibited through its performance evaluation using MATLAB/Simulink-based simulated results. keywords: MPPT, solar PV array, BLDC motor, Water pump, Voltage source inverter (VSI)

Effective Torque Ripple Reduction of Permanent Magnet Brushless DC Motor

To reduce commutation torque ripple, a model predictive control (MPC) for permanent brushless DC motors (BLDCM) is presented (CTR). Torque ripples cause vibration noise and decrease efficiency. The suggested MPC system is constructed by forecasting the phase current with the aim of minimizing the BLDCM's CTR and taking into consideration the CTR sources. The method presented in this paper is a unique methodology for suppressing CTR over the whole speed range, avoids more complex current controllers or modulation models, and overcomes the challenges of commutated-phase-current control. The ideal switching state is instantly selected and implemented during the next sample period according to the preset cost function in order to match the slope rates of outgoing and incoming phase currents during commutation, ensuring the minimum of commutation torque ripple. The modelling and experiment findings show that the suggested method can effectively reduce CTR over a wide speed range and achieve the better CTR minimization performance. The results are then compared to the outcomes of various torque ripple reduction(TRR) techniques.

ARTIFICIAL INTELLIGENCE BASED ON THE OPTIMAL STRATEGY OF MULTILEVEL CONVERTER FOR BRUSHLESS DC MOTOR

This paper presents an interesting novelty in the implementation of artificial intelligence (AI) to apply multi-level converter control, the best strategy for the Brushless DC motor control (BLDC). The interesting highlight of this research is the importance of bringing artificial intelligence (AI) to develop multi-level converter mechanisms using the artificial neural network algorithm. The neural network is a branch of artificial intelligence and is used to detect the magnitude of the input voltage from batteries. The operation of this DC-DC voltage conversion mechanism detects the output voltage and current to control the operation of the multi-level conversion mechanism supplied with six switched three-phase converters (SSTPC) to the BLDC motor controller. For this BLDC motor control mechanism, the neural network algorithm detects the Hall Effect signal to generate a PWM signal to control the action of the SSTPC. Notwithstanding, the prototype mechanism of this research is divided into two parts, the first being the conversion control mechanism multi-level, which is an essential part of voltage regulation. The second is the BLDC motor torque and speed control mechanism. This torque and speed control uses the Hall Effect signal detection principle and processes it with a neural network algorithm to generate a PWM signal to control the SSTPC activity. This neural network algorithm is processed with a DSP-TMS320C2000 microcontroller. However, the results of the prototype mechanism tested; found the importance of artificial intelligence (AI) for developing multi-level conversion mechanisms using artificial neural network algorithms with comparison simulations with programs MATLAB/Simulink. Found that a multi-level conversion control mechanism can control the voltage according to the objectives. In addition, SSTPC can also control the torque and speed of BLDC Motors. Therefore, this research result is a confirmation sign as satisfactory and can be further developed.

An Effective Sustainable Control of Brushless DC Motor using Firefly Algorithm – Artificial Neural Network based FOPID Controller

This paper proposes a Fractional purchase PID (FOPID) controller based on Firefly Algorithm-Artificial Neural Network (FA-ANN) to effectively control both the speed and torque of Brushless DC Motor (BLDCM). (BLDCM). The traditional PID controller produces sluggish response and is not efficient. In order to overcome the demerits associated with typical controller, an intelligent FOPID controller is proposed. A Modified Firefly Algorithm (FA) is implemented to attain ideal gain parameters of the proposed controller. To enhance MFF performance, the randomized parameters are updated by ANN. The proposed controller is simulated in Matlab/Simulink platform. The functional analysis of this proposed controller is demonstrated and compared with the existent schemes namely genetic algorithm GA-ANN and FA techniques. The experimental prototype with the intended technique is designed at the same time, and the results of the experiments are verified.

Commutation Torque Reduction Strategy of Brushless DC Motor Based on Single-Input Dual-Output Cuk Converter

Based on the Single-Input Dual-Output (SIDO) Cuk converter, a novel commutation torque ripple suppression strategy is proposed for a brushless DC motor (BLDCM). Two voltage scalars are constructed, according to the operating principle of SIDO Cuk converter and BLDCM, and applied to the non-commutation and commutation periods, respectively, of BLDCM; the commutation torque ripple in the full speed range is effectively reduced, and this occurs without the need to switch the control strategy according to the speed range. The inverter in the proposed strategy is controlled by the pulse amplitude modulation (PAM) during both non-commutation and commutation periods, and the voltage spike damage caused by the inverter chopping to the motor can be minimized. In addition, the multiple outputs of the SIDO Cuk converter improve the utilization of the DC power for the BLDCM control system. The experimental results verify the effectiveness of the proposed strategy.

An enhanced whale optimized fractional order piλ controller based power quality improvement for sensorless brushless dc motor under dynamic operating conditions

This paper presents an Enhanced Whale Optimization Algorithm (EWO) approach for tuning to perfection of Fractional Order Proportional Integral and integral order Controller (FOPI λ) is used to sensorless speed control of permanent magnet Brushless DC (PMBLDC) motor under the operating dynamic condition such as (i) speed change by set speed command signal (ii) varying load conditions, (iii) integrated conditions and (iv) controller parameters uncertainty. On the other hand, it deals with a reduced THD (Total Harmonic Distortion) under dynamic operating conditions to improve the power quality for the above control system. Here present are three optimization techniques, namely (i) Enhanced Whale Optimization (EWO), (ii) Invasive Weed Optimization (IWO), and (iii) Social Spider Optimization (SSO) for fine-tuning of the FOPI λ controller parameters with reduction of THD. The proposed optimization algorithm optimized FOPI λ controller are compared under various BLDC motor operating conditions. Based on the results of MATLAB/Simulink models, the proposed algorithms are evaluated. Here, both the simulation and the results of the experiments are validated for the proposed controller technique. It demonstrates that the effectiveness of the proposed controllers is completely validated by comparing the three intelligent optimization techniques mentioned above. The EWO optimized FOPI λ controller for speed control of sensorless PMBLDC motor clearly outperforms the other two intelligent controllers by minimizing the time domain parameters, THD, performance Indices error, convergence time, control efforts, cost function, mean and standard deviation.

Design and Implementation of an Electromechanical Brake System

Nowadays, hydraulic brakes are already being replaced by electromechanical brakes (EMB) to improve quick-response brakes, efficient fuel consumption, environmentally sound, simple maintenance, and enhanced safety design. It is suggested that the electromechanical brake will be one of the most important brake systems in the future. This study focuses on designing and implementing an electromechanical brake based on a brushless DC (BLDC) motor and position controller to generate and control the required braking force at a variable friction coefficient between disc and pad. A feedback controller equipped with a measuring sensor is usually utilized to control this type of brake. Thus, three controllers for current, speed, and position were implemented in successive loops to control the motor movement. This system has current, speed, and force sensors. Due to implementation difficulties and cost issues of braking, the clamping sensor should be replaced with a position sensor with some modification where a position controller has been designed and implemented. The results showed that the clamping force of the brake system can follow the target accurately and it has good performance. Also, it is shown that this system can adjust the brake force more accurately and quickly compared with the traditional.

Dynamic Simulation and Conceptual Layout Study on a Quad-Plane in VTOL Mode in Wind Disturbance Environment

Quadrotor fixed-wing hybrid vertical take-off and landing (VTOL) UAV, the so-called Quad-Plane, is susceptible to wind disturbance during the VTOL mode, which reduces its stability and limits its application. In order to dynamically analyze its response characteristics to wind disturbance and effectively optimize the wind disturbance rejection performance in VTOL mode, a dynamic flight simulation system based on the 6-DoF equations is established, in which the aerodynamic model of the Quad-Plane is established based on the wind tunnel test, the axial and lateral forces and moments of the rotor in wind disturbance are obtained through CFD simulation, and the Brushless DC (BLDC) motor, wind disturbance, and flight controller are modeled based on actual characteristics. The simulation system is verified and validated by comparing the simulation results with test results of a 5 kg real Quad-Plane. Using this system, the response characteristics of the Quad-Plane to the discrete and continuous wind disturbance are studied. In addition, the influences of major conceptual layout parameters that affect the wind disturbance rejection performance, such as take-off weight, weight distribution, Center of Gravity (CG) position, rotor incline angle, arm length, and arm angle, are studied. Finally, the approaches on designing a Quad-Plane with better wind disturbance rejection performance during the conceptual layout design are presented.