Bldc Motors

The reliability and performance of a system with minimum life-cycle cost have become quite prominent in engineering systems. With increasing industrial applications, machines are operating in intricate conditions with higher uncertainty, causing greater vulnerability of system failure. This paper reports fault-related information of Brushless DC Motor (BLDC motor) in non-stationary operating conditions and presents several analyses to diagnose the faults. Fault diagnosis is the most crucial and important part of system prognostics which helps to increase the remaining useful life (RUL) and prevent catastrophic failures. Having both electrical and mechanical characteristics present in a BLDC motor, it shows several faults in different operating conditions. These faults cause a significant change in the vibration of the Motor. This paper deals with the anomaly detection of BLDC motor in non-stationary speed conditions using vibration signal analysis as well as extraction of several Condition Indicators (CI).

A motor that retains the characteristics of a dc motor but eliminates the commutator and the brushes is called a Brushless DC motor.Brushless DC(bldc) motors can in many cases replace conventional DC motors. They are driven by dc voltage but current commutation is done by solid state switches i.e., the commutation is done electronically. BLDC motors are available in many different power ratings,from very small motors as used in hard disk drives to large motors in electric vehicles. Three phase motors are most common but two phase motors are also found in many applications. The BLDC motors have many advantages over brushed DC motors. A few of these are:  Higher speed ranges  Higher efficiency  Better speed versus torque characteristics  Long operating life  Noiseless operation  Higher dynamic response

Electrical equipment often has at least one motor used to rotate
or displace an object from its initial position. There are a variety
of motor types available in the market, including induction
motors, servomotors, DC motors (brushed and brushless), etc.
Depending upon the application requirements, a particular
motor can be selected. However, a current trend is that most
new designs are moving towards Brushless DC motors,
popularly known as BLDC motors.

Electric vehicle (EV) is one of the effective solutions to
control emission of greenhouses gases in the world. It is of interest
for future transportation due to its sustainability and efficiency by
automotive manufacturers. Various electrical motors have been used
for propulsion system of electric vehicles in last decades. In this
paper brushed DC motor, Induction motor (IM), switched reluctance
motor (SRM) and brushless DC motor (BLDC) are simulated and
compared. BLDC motor is recommended for high performance
electric vehicles. PWM switching technique is implemented for speed
control of BLDC motor. Behavior of different modes of PWM speed
controller of BLDC motor are simulated in MATLAB/SIMULINK.
BLDC motor characteristics are compared and discussed for various
PWM switching modes under normal and inverter fault conditions.
Comparisons and discussions are verified through simulation results.

Electric vehicle (EV) due to its running zero
emission, sustainability and efficiency is of interest for future
transportation. In-wheel technology has been one of the main
research concentration points in last decade. BLDC motor is on
demand for in-wheel application because of its high efficiency,
torque/speed characteristics, high power to size ratio, high
operating life and noiseless operation. In this paper direct
torque control (DTC) switching technique of BLDC motor for
EV propulsion system is proposed and simulated in MATLAB/
SIMULINK. The Simulation results show effective control of
torque and remarkable reduction of torque ripple amplitude as
compared to conventional reported switching techniques.
Improvements of in-wheel motor’s torque controllability result
to have more efficient and safer electric vehicle. The simulation
results of proposed switching system are satisfactory and show
correct performance of system.

Brushless Direct Current (BLDC) motors have gained popularity in recent years due to their high-power density. Many type of speed controller techniques have been developed and Proportional Integral Derivative (PID) controller has been the most widely used. However, PID's performance deteriorates during nonlinear loads conditions. Over the past five years, controllers have been developed to overcome this limitations in BLDC speed control, however the solutions are focusing on forward motoring only. In this paper, a speed controller for BLDC with seamless speed reversal using Modified Fuzzy Gain Scheduling is proposed. The proposed controller regulates the speed using Fuzzy Gain Scheduling 49 base rules. The controller was tested for six test cases and compared to PID and Self-Tuning Fuzzy PID controller. It is found out the proposed controller yields lowest steady state error, ess of 0.025 % during step-changing speed test case. Overall, Modified Fuzzy Gain Scheduling BLDC speed controller outperforms the other two similar controllers in variable speed conditions. The controller has potential to be used as bidirectional drive in highly dynamic load conditions. Abstrak Mutakhir ini motor arus terus tanpa berus (BLDC) telah mendapat perhatian komuniti system kawalan kerana prestasinya. Pelbagai jenis pengawal laju dihasilkan, Proportional Integral Derivative (PID) menjadi pilihan utama. Prestasi PID merosot ketika beban tidak linear. Pengawal laju lain telah dikembangkan untuk mengatasi had ini sejak lima tahun kebelakangan ini berfokus pada permotoran ke hadapan sahaja. Dalam kertas ini, Penjadualan Fuzzy Gain yang diubah suai untuk pengawal kelajuan BLDC dengan pembalikan arah yang lancar menggunakan comutasi secara berterusan adalah dicadangkan. Pengawal ini menggunakan 49 peraturan Penjadualan Fuzzy Gain. Pengawal ini telah diuji dengan enam kes ujian dan dibandingkan dengan pengawal laju PID dan Self-Tuning PID Fuzzy. Pengawal laju ini mempunyai steady state error, ess of 0.025 % yang rendah ketika ujian berubah laju. Keseluruhanya, pengawal kelajuan Fuzzy Gain Penjadualan yang diubah suai mengatasi prestasi pengawal laju yang lain ketika keadaan laju boleh ubah. Pengawal laju ini mempunyai pontensi untuk digunakan sebagai pemacu dwiarah ketika beban yang bersifat dinamik.

"Electric vehicle (EV) due to its running zero emission, sustainability and efficiency is of interest for future transportation. In-wheel technology has been one of the main research concentration points in last decade. BLDC motor is on demand for in-wheel application because of its high efficiency, torque/speed characteristics, high power to size ratio, high operating life and noiseless operation. In this paper direct torque control (DTC) switching technique of BLDC motor for EV propulsion system is proposed and simulated in MATLAB/ SIMULINK. The Simulation results show effective control of torque and remarkable reduction of torque ripple amplitude as compared to conventional reported switching techniques. Improvements of in-wheel motor’s torque controllability result to have more efficient and safer electric vehicle. The simulation results of proposed switching system are satisfactory and show correct performance of system."

This paper discusses about design and analysis of double stator slotted rotor (DSSR) BLDC motor for electric bicycle application. Usually single stator (SS) BLDC motor is used in an electric bicycle. This type of motor has low performance and need to be charged regularly. The objective of this research is to design and analysis DSSR motor that have high torque. At starts, design specification for the electric bicycle is calculated. Next, design process for DSSR is carried out by using the desired parameter. Lastly, analysis for double stator slotted rotor is simulated using FEM. Result for average back emf, average inductance, inner stator flux density, outer stator flux density, average torque and estimate torque constant is obtained. Result for average torque from FEM archieve the requirement of motor torque for DSSR design where the maximum average torque is 16.2 Nm. This research will give benefit to mankind and society in term of environment protection and energy consumption.

The existing mixer grinder comprises of the universal motor operating in alternating current supply due to high starting torque characteristics and simple controlling of the speed. The absence of brushes and the reduction of noise in the Brushless DC (BLDC) extends its lifetime and makes it ideal in a mixer grinder. A novel solar-powered BLDC motor drive for mixer grinder is presented in this paper. A DC-DC boost converter has been utilised to operate a PV (photovoltaic) array at its highest power. The proposed hysteresis current control BLDC system has been developed in the MATLAB. A performance comparison is made using the commercially available mixer grinder along with the simulated proposed system.

With the rising economy, fuel demand also increases. In today's world, fossil fuels are the major contribution to meeting these demands. However, it is not going to be the same scenario in the next decades as the fossil fuels levels are depleting there is a need for an alternative fuel that will satisfy energy requirements and will be a sustainable source in coming years. In the automotive industry petrol and diesel have been major fuels in driving vehicles. Although electric vehicles are going to be replaced by IC engines. Electric vehicles have lower fuel costs as compared to internal combustion engines but because of limited charging stations vehicles are bound to drive within certain distances. With the implementation of regenerative braking in electric vehicles, it is possible to charge batteries when the vehicle is breaking and thus increasing driving distance. This paper presents a simulation of control of BLDC motor with regenerative braking.

To take full advantage of the high reliability of brushless DC motors (BLDCMs), an electronic control unit with equally high reliability is mandatory. In this paper, a solution is proposed for cost and reliability drawbacks associated with integrated BLDCM controllers by using reconfigurable technology to implement control logic. An embedded DSP design for FPGAs is presented that is able to drive BLDCMs using a minimum of external components and implementing optic coupling between logic and power electronics. Secondly, the reliability of the proposed implementation is compared to the performance of commercial BLDCM controllers.

— In textile industry many processes require speed synchronization of more than one motors involved in the process. Rolling of cloth should be synchronized with the speed of weaving spindle to avoid damage and motor speed synchronization is vital in conveyor belt driven by multiple motors. Abrupt load variations may cause hunting or oscillatory behavior in d. c. machines. This behavior can be detrimental to the process. The digitally controlled d. c. machines can have much aggravated phenomenon owing to poor sampling period selection. Traditionally processes are synchronized through mechanical transmission system consisting of a line shaft gears, pullers etc. This project is synchronization of multiple motors using wireless technology. This project uses radio frequency to synchronize motor speeds. One motor acts as transmitter and all the rest as receivers. Thus, if a particular speed is set in the transmitter then all other motors speed would be matched to the same speed of the main motor. The mode of communication is radio frequency. BLDC motors used operate on the basis of PWM control. Each motor has a closed loop feedback mechanism providing RPM reference by a shaft mounted IR sensor arrangement whose output is fed to the controller in the circuit. A display unit displays the full speed and one can enter the desired percentage with help of a keypad to obtain the required speed for all the motors. Manpower and time is also saved in this system. Keywords— Micro controller, IR sensor, RF module, BLDC Motors and LCD.

The hardware implementation of sensorless brushless direct current motor drive incorporating H-infinity control strategy with optimized weights by particle swarm optimization in the speed control is carried out in this work. The methodology involved in the design of brushless direct current (BLDC) motor control with sensorless position detection technique, the design of Hinfinity speed controller, steps involved in particle swarm optimization for optimizing coefficients of its weights and the hardware implementation is discussed in detail in this paper. Texas Instruments microcontroller board C2000 Delfino Launchpad LAUNCHXL F28377S and driver BOOSTXL DRV8301 are used for realization of the speed controller. The code is developed using C2000 hardware support package in MATLAB/SIMULINK platform. A comprehensive performance analysis is accomplished during starting of the motor and during the fast application and removal of load. This strategy is found to be robust resulting in faster load disturbance rejection and better reference speed tracking. The experimental results of the proposed strategy are compared with that of conventional proportionalintegral (PI) controller. The time domain parameters are also compared. It is found that the proposed strategy exhibits better performance characteristics during transients and sudden disturbances in load.

Several problems are faced by today’s generation. One of them is the increase in pollution in our everyday life. Each of us can play a part in reducing this by using some environmentally friendly method such as cycles which requires mechanical force. Another way to accomplish this is by using electricity to produce this mechanical force i.e. electric motor. In this paper BLDC motor driven electric skateboard is designed with mathematical calculation, verified with simulation and developed as a experimental setup.

This paper presents a control scheme for speed control system in brushless dc (BLDC) motor to be utilized for electric motorbike. While conventional motorbikes require engine and fuel, electric motorbikes require DC motor and battery pack in order to be powered up. The limitation with battery pack is that it will need to be recharged after a certain period and distance. As the recharging process is time consuming, a PID controller is designed to maintain the speed of the motor at its optimum state, thus ensuring a longer lasting battery time (until the next charge). The controller is designed to track variations of speed references and stabilizes the output speed accordingly. The simulation results conducted in MATLAB/SIMULINK® shows that the motor, equipped with the PID controller was able to track the reference speed in 7.8x10-2 milliseconds with no overshoot. The result shows optimistic possibility that the proposed controller can be used to maintain the speed of the motor at its optimum speed

The primary objective of the project is to design a geared electric bike powered using BLDC (brush-less DC motor). As the number of internal combustion engine powered vehicles on the roads throughout the world increases at an increasing rate each year, the dependence on oil-based fuel grows almost unchecked. The increased use of non-renewable fossil fuels causes environmental problems such as: the "greenhouse effect" and health problems. To move away from this dependence on fossil fuel an efficient and non-pollution effective vehicle has to be developed. The aim of this study is to investigate how to design a simple, cost effective model of geared electric motorcycle with BLDC motor as engine and high-powered battery packs. This can be implemented by removing the internal combustion engines piston head, the exhaust system and other unnecessary components from the IC engine powered motorcycle and replaced by a BLDC motor, an intelligent controller, battery pack, cabling system and monitoring instruments.

This paper focuses on the development of a prototype of thruster motor speed controller which exhibits robust performance for an Autonomous underwater vehicle. H infinity based speed controller with particle swarm optimized weights for a sensorless BLDC motor which is used as electrical thruster has been simulated in MATLAB/ SIMULINK and implemented using TI C2000 Delfino LaunchPad LaunchXL-F28377S and BoostXL DRV 8301. A performance comparison in reference tracking has been done with conventional PI controller and experimental results have been discussed in detail. The percentage variation in speed with respect to reference speed of proposed strategy has been observed to be 0.65% whereas it is 1.1% with PI controller. It has also been found that the proposed control strategy exhibits smooth starting with better reference tracking and less torque ripples.

This paper presents a new controller for speed control problem of the BLDC motors. The nonlinear
model of the motor is approximated by implementation of fuzzy rules. The uncertainties are considered
in the fuzzy system. Using this model and linear matrix inequality (LMI) optimization, a robust
controller for purpose of speed control of the motor has been designed and applied to it. The
effectiveness of the designed controls demonstrated through simulation results.

Brushless DC (BLDC) motors are one of the most widely used motors for various industrial applications due to their high efficiency, high torque to weight ratio and elimination of mechanical commutator. These motors operate in wide range of speeds and necessitate precise speed control techniques, for their nonlinear model, insenseitive to parameter variations and external disturbances, when used in various sensitive applications. Conventional PI and other existing controllers produce high overshoot and increased rise time and settling time. The performance of BLDC motor is enhanced using a Fuzzy Sliding Mode Controller (FSMC) whose gain is intelligently varied with the help of a Fuzzy Inference System (FIS). For this purpose, a suitable FSMC is designed, simulated and implemented using FPGA. The simulation results are validated using Hardware in the loop (HIL) simulation as well as actual hardware implementation. Great improvement in the transient performance is achieved when compared to chatter free SMC, Fuzzy PI and conventional PI controller.

Today motor control systems are used by engineers use for both digital and analog technologies to conquer past challenges including motor speed control, rotation direction, drift and motor fatigue. The application of MCUs has enabled this generation of engineers the opportunity to dynamically control motor actions so that they respond to environmental stresses and conditions. This will help to provide a longer operational lifetime and reduce maintenance which means lower cost. Currently, motor manufactures are gravitating towards 3-Phase BLDC motors because they provide more torque for less power and have a longer operating time due to no direct contact from the commutator and electrical terminals such as is found in the brushed motors. Regrettably, the use of 3-Phase motor control adds additional complexity compared to brushed DC or AC motors and the relationship between digital and analog components becomes very important.
This whitepaper discusses a summary of the concerns that should be factored in when using analog components and microcontroller in a 3-Phase BLDC motor application. It also covers the suitable power management devices and power level shifters that enable the microcontrollers to drive motors form power sources from 12V all the way up to 300V DC voltages.

Brushless DC (BLDC) motors, bearing the characteristics of permanent magnet synchronous machines, have gained immense popularity in industrial applications due to its excellent efficiency and ease in control over conventional DC motors. Stator related faults are the most common types of faults in BLDC motors while operating under a higher loading and complex condition. Conventional machine learning (ML) classifiers such as-Support Vector Machines (SVM), k-nearest neighbors (KNN), Naïve Bayes (NB) classifiers fail to obtain optimum accuracy when there are abrupt changes in health states of the BLDC motor. Especially the classification of weak health features ends up with an erroneous result. Boosting techniques allow adding weights to weak features and a better result in classification. This study presents an improved stator related fault classification of BLDC Motor using AdaBoost technique. Several parameters of AdaBoost algorithm are optimized and implemented along with Random Forest (RF) classifier in order to determine a developed algorithm for fault classification.

Several problems are faced by today’s generation. One of them is the increase in pollution in our everyday life. Each of us can play a part in
reducing this by using some environmentally friendly method such as cycles which requires mechanical force. Another way to accomplish this is by using electricity to produce this mechanical force i.e. electric motor.  In this paper
BLDC motor driven electric skateboard is designed with mathematical
calculation, verified with simulation and developed as a experimental setup.

This work presented two fuzzy logic (FL) schemes for speed-controlled brushless DC motors. The first controller is a Type 1 FL controller (T1FLC), whereas the second controller is an interval Type 2 FL controller (IT2FLC). The two proposed controllers were compared in terms of system dynamics and performance. For a fair comparison, the same type and number of membership functions were used for both controllers. The effectiveness of the structures of the two FL controllers was verified through simulation in MATLAB/SIMULINK environment. Simulation result showed that IT2FLC exhibited better performance than T1FLC.

Aquaponics system needs very high electricity for the aeration of the system moreover as pumping of water. The proposed system using alternative energy as a source of energy for designing and developing standalone Aquaponics system with longer life, less maintenance and better performance. The fundamentals building components of Aquaponics system are solar PV array, a zeta converter together with two voltage source inverter and two Brushless DC (BLDC) motors with a paddle wheel aerator and pump load coupled to their shaft. The proposed system improves the efficiency and control the speed of BLDC motor. This method is especially useful for rural areas that have a substantial amount of solar radiation and haven't any access to grid system. The proposed system is mean to induce satisfactory system performance even under dynamic conditions. Suitability of the proposed system for various perturbations is evaluated by simulating the proposed system using MATLAB/Simulink.

Brushless Direct Current (BLDC) motors have attracted a lot of attention due to their performance capabilities. The Proportional Integral (PID) controller remained popular due to its simplicity. However, PID's performance deteriorates during nonlinear loads conditions. Controllers have been developed to overcome the limitations of the PID controllers but focused on forwarding motor only. Furthermore, lack of literature regarding the bidirectional speed control of BLDC motor has been reported. In this paper, a Hybrid Fuzzy-PID speed controller for BLDC with seamless speed reversal using direct commutation switching scheme was proposed. The controller uses Fuzzy rule base and the switching scheme for bidirectional operations. MATLAB/Simulink was used to develop and test the controller. The controller was tested for several test cases and compared to a ZN-Tuned PID controller. The controller performed efficiently for all the test cases and has better results compared to the PID con...

Brushless Direct Current (BLDC) motors have gained popularity in recent years due to their high-power density. Many type of speed controller techniques have been developed and Proportional Integral Derivative (PID) controller has been the most widely used. However, PID’s performance deteriorates during nonlinear loads conditions. Over the past five years, controllers have been developed to overcome this limitations in BLDC speed control, however the solutions are focusing on forward motoring only. In this paper, a speed controller for BLDC with seamless speed reversal using Modified Fuzzy Gain Scheduling is proposed. The proposed controller regulates the speed using Fuzzy Gain Scheduling 49 base rules. The controller was tested for six test cases and compared to PID and Self-Tuning Fuzzy PID controller. It is found out the proposed controller yields lowest steady state error, e ss of 0.025 % during step-changing speed test case. Overall, Modified Fuzzy Gain Scheduling BLDC speed con...