Search results

The conventional two-level inverter suffers from harmonics, higher direct current (DC) link voltage requirement, higher dv/dt and heating of the rotor. This study aims to overcome by using a multilevel inverter for brushless DC (BLDC) drive.

This paper presents a comparative analysis of the conventional two-level and three-level multilevel inverter for electric vehicle (EV) application using BLDC drive.

A three-level Active Neutral Point Clamped Multilevel inverter (ANPCMLI) is proposed in this paper which provides DC link voltage control. Simulation studies of the multilevel inverter and BLDC motor is carried out in MATLAB.

The ANPCMLI fed BLDC simulation results shows that there is the significant reduction in the BLDC motor torque ripple, switching stress and harmonic distortion in the BLDC motor fed ANPCMLI compared to the conventional two-level inverter. A prototype of ANPCMLI fed BLDC drive along with field programmable gate array (FPGA) control is built and MATLAB simulation results are verified experimentally.

Switching power converters for photovoltaic (PV) applications with high gain are rapidly expanding. To obtain better voltage gain, low switch stress, low ripple and cost-effective converters, researchers are developing several topologies.

It was decided to use the particle swarm optimization approach for this system in order to compute the precise PI controller gain parameters under steady state and dynamic changing circumstances. A high-gain q- ZS boost converter is used as an intermittent converter between a PV and brushless direct current (BLDC) motor to attain maximum power point tracking, which also reduces the torque ripples. A MATLAB/Simulink environment has been used to build and test the positive output quadratic boost high gain converters (PQBHGC)-1, PQBHGC-8, PQBHGC-4 and PQBHGC-3 topologies to analyse their effectiveness in PV-driven BLDC motor applications. The simulation results show that the PQBHGC-3 topology is effective in comparison with other HG cell DC–DC converters in terms of efficiency, reduced ripples, etc. which is most suitable for PV-driven BLDC applications.

The simulation results have showed that the PQBHGC-3 gives better performance with minimum voltage ripple of 2V and current ripple of 0.4A which eventually reduces the ripples in the torque in a BLDC motor. Also, the efficiency for the suggested PQBHGC-3 for PV-based BLDC applications is the best with 99%.

This study is the first of its kind comparing the different topologies of PQBHGC-1, PQBHGC-8, PQBHGC-4 and PQBHGC-3 topologies to analyse their effectiveness in PV-driven BLDC motor applications. This study suggests that the PQBHGC-3 topology is most suitable in PV-driven BLDC applications.

When phase windings of brushless DC motor are switched, additional voltage drops across inductances of main circuit appear. These drops lead to, among other effects, increase of torque‐speed curve slope. The discussed research has been aimed at working out a simple and precise method of identifying torque‐speed characteristic of PM BLDC motor. The elaborated method takes into account the influence of windings switching and motor inductances on motor torque‐speed characteristic. In order to assess the results, extensive test simulations of models implemented in Matlab/Simulink software have been run. Results of analysis and test simulations have been compared with lab test results of two real PM BLDC motors.

Analytical calculations take into consideration phenomena occurring during windings switch‐overs and impact of inductance on emerging voltage and rotational speed drops. It has been pointed out that on account of main circuit inductance, the average value of source current is less than average value of equivalent current generating electromagnetic torque. For analysis sake it has been assumed when windings are being switched‐over the current is kept constant; the motor parameters have also been assumed to be constant.

A novel and accurate method of determining torque‐speed characteristics of PM BLDC motor has been worked out. This method has been investigated with the help of motor computer models implemented in Matlab/Simulink software and the obtained results have been subsequently compared with results of laboratory tests of two commercially available PM BLDC motors.

The object of the research was brushless DC motor with permanent magnet excitation. The impact of windings switch‐overs on torque‐speed curves of the motor has been analysed. Analytical method which makes it possible to determine torque‐speed curve of this motor very easily has been elaborated. Computer model of PM BLDC motor for Matlab/Simulink software has also been worked out. Extensive simulations helping to verify the proposed method have been run. Results of analysis and simulation tests have been verified by means of laboratory tests of two commercially available PM BLDC motors.

PM BLDC motors are used more and more widely. The new method of determining PM BLDC motors torque‐speed curves will facilitate analysis and design of drive systems utilizing these motors and will also speed up calculations.

The presented method of determining torque‐speed curves of PM BLDC motor is novel and much more precise than methods commonly used nowadays. Recognized methods usually neglect impact of inductance on motor properties.

The puspose of this paper, a novel systematic design of fractional order proportional integral derivative (FOPID) controller-based speed control of sensorless brushless DC (BLDC) motor using multi-objective enhanced genetic algorithm (EGA). This scheme provides an excellent dynamic and static response, low computational burden, the robust speed control.

The EGA is a meta-heuristic-inspired algorithm for solving non-linearity problems such as sudden load disturbances, modeling errors, power fluctuations, poor stability, the maximum time of transient processes, static and dynamic errors. The conventional genetic algorithm (CGA) and modified genetic algorithm (MGA) are not very effective in solving the above-mentioned problems. Hence, a multi-objective EGA optimized FOPID (EGA-FOPID) controller is proposed for speed control of sensorless BLDC motor under various conditions such as constant load conditions, varying load conditions, varying set speed (Ns) conditions, integrated conditions and controller parameters uncertainty.

This systematic design of the multi-objective EGA-FOPID controller is implemented in MATLAB 2020a with Simulink models for optimal speed control of the BLDC motor. The overall performance of the EGA-FOPID controller is observed and evaluated for computational burden, time integral performance indexes, transient and steady-state characteristics. The hardware experiment results confirm that the proposed EGA-FOPID controller can precisely change the BLDC motor speed is desired range with minimal effort.

The conventional real time issues such as nonlinearity characteristics, poor controllability and stability.

It is clearly evident that out of these three intelligent controllers, the EGA optimized FOPID controller gives enhanced performance by minimizing the time domain parameters, performance Indices error and convergence time. Also, the hardware experimental setup and the results of the proposed EGA-FOPID controller are presented.

It shows the effectiveness of the proposed controllers is completely verified by comparing the above three intelligent optimization algorithms. It is clearly evident that out of these three intelligent controllers, the EGA optimized FOPID controller gives enhanced performance by minimizing the time domain parameters, performance Indices error and convergence time. Also, the hardware experimental setup and the results of the proposed EGA-FOPID controller are presented.

This study aims to calculate eddy current losses in permanent magnets of BLDC machine in the generator mode of operation with no‐load.

Stator slot openings and special design of the stator poles cause changes in the magnetic flux density changes in permanent magnets. The stator windings are not connected to an outer source and no currents flow in them. The induced eddy currents in permanent magnets are dependent solely on the stator geometry. Analytical approach to calculate the eddy current density distribution in permanent magnets is based on known distribution of magnetic flux density in the air‐gap of BLDC. The magnetic flux density distribution is obtained from magneto‐static finite element model of BLDC. For verification of analytical approach the eddy current density distribution in permanent magnets is also calculated by magneto‐transient finite element model of BLDC.

The eddy current losses in PM obtained with the FEM indicate additional heating of the BLDC machine at high rotational speeds even when it operates at no load. When some special stator designs (the side of the air gap) are needed, the losses in PMs and their heating increase.

To get more precise results, the proposed analytical method for eddy current losses calculation in PM should be further analyzed. More geometric parameters of the BLDC design should be introduced to analytical formulations, especially those which affect variations in reluctance.

When some special stator designs (the side of the air gap) are needed, the losses in PMs should be observed. This is particularly recommended at higher rotation velocities. Any kind of magnetic flux density change induces eddy currents and together with them also power losses. These losses give rise to additional heating of PM. With this, the temperature‐dependent working characteristic of PM (second quadrant of the B‐H curve) moves toward the coordinate origin point. The overall machine performance is reduced. The presented work gives the view about happenings in permanent magnets regarding induced eddy current losses. It is a useful tool for fast estimation and reduction of eddy current losses in PM due to stator geometry.

The value of the paper is the closed view about happenings in permanent magnets regarding induced eddy currents and the calculation of eddy current losses in rotor permanent magnets of BLDC due to stator design. The originality is in the analytical approach to calculate the eddy current losses based only on known magneto‐static flux density distribution in air‐gap of BLDC.

The purpose of this paper is to develop a generalized observer and controller for brushless direct current (BLDC) motor to make the system more robust for parameter variations, load torque and speed tracking.

A robust interconnection and damping assignment passivity-based control (IDA-PBC) technique for BLDC motor is introduced in this paper. The IDA-PBC is used to obtain the reference voltages for pulse width modulation (PWM) control. The immersion and invariance (I&I) observer is used to estimate the load torque and speed of the BLDC motor. At the time of starting, the motor rotates in arbitrary direction, and sometimes, because of the cogging action, it may take a huge current. Therefore, a new start-up method is proposed for the BLDC motor, which maintains the alignment of the rotor.

From the simulation and experimental results, it can be seen that the proposed controller and observer satisfactorily work for parameter variations, load torque and speed tracking.

The authenticity of the proposed technique is tested experimentally on two different BLDC motors using low-cost 32-bit STM32F407VG microcontroller. The response of the proposed technique is evaluated by changing motor parameters such as stator resistance, inductance, flux linkage constant and torque constant.

The principal intention behind the activity is to regulate the speed, current and commutation of the brushless DC (BLDC) motor. Thereby, the authors can control the torque.

In order to regulate the current and speed of the motor, the Multi-resolution PID (MRPID) controller is proposed. The altered Landsman converter is utilized in this proposed suppression circuit, and the obligation cycle is acclimated to acquire the ideal DC-bus voltage dependent on the speed of the BLDC motor. The adaptive neuro-fuzzy inference system-elephant herding optimization (ANFIS-EHO) calculation mirrors the conduct of the procreant framework in families.

Brushless DC motor's dynamic properties are created, noticed and examined by MATLAB/Simulink model. The performance will be compared with existing genetic algorithms.

The presented approach and performance will be compared with existing genetic algorithms and optimization of different structure of BLDC motor.

The efficient speed controller is found to be an important requirement to run the motor for the brushless direct current (BLDC) motor. This requirement is considered as superior, as it may increase the operating speed and system efficiency. In the existing methods, proportional plus integral (PI) controller has been included because of its simple architecture. But the PI controller produces load disturbance, control complexity and some parametric (Proportional plus integral) variations. The purpose of this proposed controller is to overcome the problems produced by PI controller in BLDC motor.

The proposed BLDC motor is developed with fixed order H-infinity controller. In this architecture, both the weight functions and transfer functions were included to design the controller. This controller has been included in this BLDC to detect the rotor position. The optimal position of rotor is identified by introducing particle swarm optimization algorithm.

The torque that obtained in the motor is highly reduced by this proposed controller and also enhances the speed. The BLDC motor is modelled in a MATLAB environment.

The performance of the torque, speed and back electro-motive force is analysed and compared with the existing controllers such as fuzzy proportional plus integral plus derivative, sensing algorithm and fuzzy proportional plus derivative controller.

Simulation results show that the proposed technique gives better results than the other existing controllers.

This paper deals with magnetic field calculations and model‐based prediction of electromagnetic torque pulsations in a brushless DC (BLDC) motor.

The impact of a Halbach‐like magnetization and a multipolar excitation of permanent magnets are analysed. The measurement results from the prototype motors are well‐compared with those obtained from the model calculations. It is shown that the cogging torque in the motor with the multipolar excitation of permanent magnets is reduced six times as compared with the conventional BLDC motor.

The proposed method provides high accuracy of the analysis of coupled electromagnetic phenomena. The comparison between measured and calculated values of electromagnetic torque, cogging torque and EMF shows a very good agreement.

Reduction of the machine cogging torque is essential for practical applications of DC motors, in particular in the robotics industry.

This paper shows that multipolar excitation contributes to essential reduction of the cogging torque in a BLDC motor. This is confirmed by high‐quality numerical models of the motor, positively verified in experiments with motor prototypes.

The purpose of this paper is to propose a multi-objective particle swarm optimization (MOPSO) algorithm based design optimization of Brushless DC (BLDC) motor with a view to mitigate cogging torque and enhance the efficiency.

The suitability of MOPSO algorithm is tested on a 120 W BLDC motor considering magnet axial length, stator slot opening and air gap length as the design variables. It avails the use of MagNet 7.5.1, a Finite Element Analysis tool, to account for the geometry and the non-linearity of material for assuaging an improved design framework and operates through the boundaries of generalized regression neural network (GRNN) to advocate the optimum design. The results of MOPSO are compared with Multi-Objective Genetic Algorithm and Non-dominated Sorting Genetic Algorithm-II based formulations for claiming its place in real world applications.

A MOPSO design optimization procedure has been enlivened to escalate the performance of the BLDC motor. The optimality in design has been out reached through minimizing the cogging torque, maximizing the average torque and reducing the total losses to claim an increase in the efficiency. The results have been fortified in well-distributed Pareto-optimal planes to arrive at trade-off solutions between different objectives.

The rhetoric theory of multi objective formulations has been reinforced to provide a decisive solution with regard to the choice of the design obtained from Pareto-optimal planes.

The incorporation of a larger number of design variables together with an orientation to thermal and vibration analysis will still go a long way in bringing on board new dimensions to the fold of optimality in the design of BLDC motors.

The proposal offers a new perspective to the design of BLDC motor in the sense it be-hives the facility of a swarm based approach to optimize the parameters in order that it serves to improve its performance. The results of a 120 W motor in terms of lowering the losses, minimizing the cogging torque and maximizing the average torque emphasize the benefits of the GRNN based multi-objective formulation and establish its viability for use in practical applications.