Security Drone for Surveillance in Military

This study details the design and testing of a custom test rig for evaluating the performance of both open and shrouded rotors. The rig includes a two-axis load cell that is directly connected to the rotor to measure the rotor thrust separated from the total thrust when testing shrouded rotors and ensure accurate torque measurements, independent of external structural influences. Moreover, a main load cell is used to measure the total thrust for both configurations (open and shrouded rotor), as it is connected to the entire setup. Rotor RPM is monitored by capturing the voltage frequency from the BLDC motor, controlled using a Pololu Maestro Controller through the electronic speed controller. A shunt resistance is used to calculate the current through the electric Brushless Direct Current (BLDC) motor and by measuring the voltage, the electric power is calculated. By combining both mechanical and electrical power measurements, the BLDC motor’s efficiency is calculated. Automated data collection is conducted using National Instruments DAQ systems, with averaged measurements of thrust, torque, RPM, current, and voltage. Two rotors are tested to obtain performance data for both open and shrouded configurations. Additionally, a computational study is carried out to account for the aerodynamic effects of the rig’s structural elements. Uncertainty analysis is employed to assess the reliability of the experimental results by quantifying the numerical errors associated with both random and systematic errors encountered during the rotor’s performance evaluation.

Electric vehicles are currently being developed with the concept of saving energy and environmentally responsible. Electric vehicles use electric motors as the main driving motor. The electric motor which is currently increasingly used is the Brushless Direct Current (BLDC) motor. The BLDC motor controller is more expensive than the price of the BLDC motor itself. The BLDC motor controller has a working temperature range when working. The purpose of this study was to analyze the effect of variations in load values and the speed of electric vehicles on the temperature of the BLDC motor controller. This research was conducted by the experimental method by giving a treatment, then evaluating the effect caused on an object of research. The results showed that there was an influence of load value variations on the BLDC motor controller temperature. Values that look significant are at speeds of 0.5 m/sec and 2.5 m/sec starting from 3 kg to 5 kg. There is no influence on the variation of speed values on the temperature of the BLDC motor controller. The temperature value is stable at 2 kg and 3 kg loads with speed variations from 0.5 m/sec to 2.5 m/sec. Simultaneously variations in load and speed values affect the temperature of the BLDC motor controller by 57.7% with the lowest temperature value at 0.5 m/s and a load of 1 kg with a temperature of 33.34℃ and the highest temperature value at a speed of 2.5 m/sec and a load of 5 kg with a temperature of 37.58℃. Keywords: Electric vehicles, controllers, BLDC motors, temperature.

Brushless Direct Current (BLDC) motor is superior to carbon brushed DC motors, such as high efficiency, more speed range, less maintenance, longer life etc. This is because BLDC motor has electronic commutation and thus, does not have to overcome friction unlike the brushed DC motor. Thus, they find application in many areas such as Electric Vehicles and Robotics. However, a disadvantage of BLDC motor is that it requires a controller for electronic commutation which can be expensive and also increases the complexity of the implementation. The BLDC motors which are controlled by classical controllers suffer from problems of parametric variation during commutation and torque ripple in the output. The project aims to design a Robust controller for BLDC motor speed control so as to improve the output of BLDC motor.

Brushless Direct Current (BLDC) Motor is an electromagnetic device that converts electrical energy into mechanical energy. BLDC motor is a type of motor used in electric cars and does not need brush for magnetic field replacement (commutation), but is carried out electronically commutated. In BLDC motor, temperature in the motor play important role on motor performance such as maximum power and efficiency. In this research the development of liquid cooling of BLDC motor is described. Development starts from the design, computation using software and the realization of the motor design results. The construction of a brushless DC motor is very similar to that of an ac motor, known as permanent magnet synchronous motor. The stator consisting of a core and copper windings forming a core and armature unit. There are 2 identical stators to form the BLDC.

High speed permanent magnet (PM) brushless dc (BLDC) motors have increasingly been used in a wide range of commercial and industrial applications, while low rotor loss and reliable rotor dynamic feature of the motor are essential requirements. Due to the high power densities, the high speed PM BLDC motors' unit volume losses are high, and also it is difficult to disperse heat, thus, the rotor losses are no longer negligible compared to the conventional-speed machines and must be considered in the design process. Besides, the rotors of high speed PM BLDC motors are subject to the resonance vibration, limiting the maximum operation speed. This paper describes the design and analysis of a high speed PM BLDC motor with surface mounted magnets for a rated power of 10kW at 70,000 rpm. Influences of the stator and rotor structures as well as magnet materials on the motor's electromagnetic performance and rotor dynamic property are analyzed. Both analytical and FEA methods are adopted to calculate the motor losses and rotor resonance modals with different motor configurations.

The advancements in the field of materials and force gadgets, coupled with the increased affordability of highperformance processors, have led to a widespread adoption of Brushless Direct Current (BLDC) motors across various industries. These applications range from household appliances to automotive, aerospace, and medical sectors. The widespread use of may be attributed to its manifold advantages over various types of engines, such as its superior efficiency, robust power output, extended operational lifespan, relatively quiet operation, and broader range of achievable speeds. Due to the increasing adoption of Brushless Direct Current (BLDC) motors in many real-life applications as a replacement for traditional motors, this paper aims to compile and evaluate a comprehensive list of control algorithms employed for BLDC motor control. This study discusses several ways for managing speed and current, including hysteresis band control, variable DC-link voltage control, and Pulse Width Modulation (PWM) control schemes. The optimization of Proportional-Integral-Derivative (PID) gains for these controlling techniques is achieved through the utilization of the particle swarm optimization (PSO) algorithm. By employing Fast Fourier Transform (FFT) analysis to examine the controller behavior through frequency analysis of the output signals and calculating the Total Harmonic Distortion (THD), a more advantageous control method may be determined.

This paper presents a single-stage isolated power factor corrected power supply (SSIPP) fed permanent magnet brushless DC (BLDC) motor drive. An advantage of fast voltage regulation with single voltage control loop of SSIPP is utilised to develop a power factor correction (PFC) based BLDC motor drive. The speed of BLDC motor is controlled by varying the DC link voltage of the voltage source inverter (VSI) feeding BLDC motor using a single voltage sensor. A boost-flyback SSIPP operating in discontinuous inductor current mode (DICM) is used for the voltage control with improved power quality at AC mains. A fundamental frequency switching of VSI is used instead of pulse width modulation (PWM) switching to avoid high frequency switching losses in it. The performance of the proposed BLDC motor drive is evaluated for wide range of speed control with power quality indices with-in the recommended limits of international power quality standards such as IEC 61000-3-2.

This paper presents the modeling and controlling of a fuzzy logic controller (FLC) for achieving improved dynamic performance of the Brushless DC (BLDC) motor drive. The performance of fuzzy and the PI controller based BLDC motor drives is investigated under the different operating conditions such as change in reference speed, parameter variations and the load disturbance. BLDC motors are used in industrial control, automation and instrumentation system applications. Based on other applications the conventional controllers like P, PI and PID controllers are used in the BLDC motor drive control systems to achieve the desired level of transient and steady state responses. However, the major problem in the conventional PI controller there is some variations in the parameter and some load disturbances are occur and do not yield the better transient and the steady state responses under the operating conditions. In this paper, the modeling and controlling of fuzzy logic controller is presented its performance and it compared with the PI controller shows the error capability and usefulness of the fuzzy controller in the control applications.

A new method for optimizing the fuzzy PID controller, based on an artificial electric field algorithm (AEFA), is proposed in this paper, aiming at improving the stability indicator of the Brushless DC (BLDC) motor for the small satellite attitude control flywheel. The BLDC motor is the basic part of the small satellite attitude control flywheel. In order to accurately control the attitude of the small satellite, a good motor control system is very important. Firstly, the mathematical model of the BLDC motor is established and the BLDC motor speed control system using traditional PID control is designed. Secondly, considering that the small satellite speed control system is a nonlinear system, a fuzzy PID control is designed to solve the shortcomings of the fixed parameters of the traditional PID control. Finally, we find that the control accuracy of the fuzzy PID control will change with the range of the input. Therefore, we introduce the AEFA to optimize fuzzy PID to achieve high-precision attitude control of small satellites. By simulating the BLDC motor system, the proposed fuzzy PID controller based on AEFA is compared with the traditional PID controller and the fuzzy PID controller. Results from different controllers show that the proposed control method could effectively reduce steady state error. In addition, the proposed fuzzy PID–AEFA controller has the better anti-jamming capability.

Analysis of the demagnetized permanent magnets in BLDC motor is presented in this paper. Automotive, aerospace, consumer, medical and industrial applications are the fastest growing markets for Brushless DC (BLDC) Motor. BLDC motor has high efficiency, high power density, and low maintenance cost. Still, due to overloading the motor, lots of faults can occur in stator, rotor, bearings and permanent magnets. In this paper, focus has been given on faults in permanent magnets. Modeling of demagnetized BLDC motor is presented using MATLAB/SIMULINK and AWT (Analytic Wavelet Transform) analysis is also done to find time frequency ridges. Test results show that stator current peak increases as magnets are demagnetized.

This paper represents a fast approach for reduction of torque ripple on brushless DC (BLDC) motor. From a classic motor model, a mathematics component of torque ripple is extracted. To reduce the ripple component, a small modification of PWM and an open-loop control algorithm are made in the inverter of BLDC motor. At last, our paper describes and analyzes the simulation results of this approach by using PSIM. Without any sensors or advanced controllers, this approach can work in most BLDC motor drivers just after software update.

Brushless Direct Current (BLDC) motors have been used in a wide range of fields. In some critical applications, failures in these machines can cause operational disasters and cost lives if they are not detected in advance. The classical methods for detecting incipient faults in BLDC motors perform processing of the current signal to obtain the required information. In this work, the SAC-DM (Signal Analysis based on Chaos using Density of Maxima) technique is applied for the first time in the diagnosis of failures of electromechanical systems from sound signals. Wavelet Multiresolution Analysis (WMA) is used to separate a chaotic signal component from the sound emitted by the motor. This work demonstrates that it is feasible to perform dynamic eccentricity diagnosis in BLDC motors by identifying variations of the SAC-DM of the sound signal. The technique exposed in this work requires low computational cost and achieves high success rate. To validate the method, tests were carried out on a small BLDC motor normally used in Unmanned Aerial Vehicle (UAV), demonstrating the ability of the method to detect the speed of the motor in 95.89% of the cases and to detect eccentricity problems at a fixed speed in 88.34% of the cases.

A brushless direct current (BLDC) motor has high reliability and a long life because it eliminates mechanical friction, and compensates for the defects of a direct-current (DC) motor by removing the brush and commutator. Compared to a DC motor, BLDC motor has the excellent efficiency because there is no voltage drop or friction loss of the brush. However, when the motor is operated for a long time with a high output, the internal motor temperature rises, and the copper-winding temperature increases. The temperature rise of the internal motor affects the resistance of the copper winding and the performance of the permanent magnet. This study investigates the efficiency of a 500 W BLDC motor with a varying air flow rate. The temperature rise and efficiency of the BLDC motor are studied by applying inlet flow rates of 0, 30 and 50 L/min during a 20 min load test. The temperature rise is very high at 0 L/min and the efficiencies are calculated as 81.9%, 82% and 82.7%. This study can be used as a basic study on the optimal air flow rate to the internal motor.

A brushless direct current (BLDC) motor is widely used in automotive and industrial applications due to its low noise and high performance. However, traditional BLDC motor control relies on Hall-effect sensors, which increase costs, enlarge motor dimensions, and risk errors from sensor failures. This research focuses on implementing a sensorless control system for a 350W, 48V BLDC motor. The goal is to achieve stable operation at a set speed of 250 rpm, with a steady-state error ≤3%, under varying loads from 0 Nm to 2.7 Nm. Using the Ziegler-Nichols PID tuning method, the study was conducted in the Electrical Machinery Laboratory at Bandung State Polytechnic. The results show that the sensorless control system effectively maintains setpoint speeds of 90 rpm, 120 rpm, 200 rpm, and 250 rpm. At 250 rpm, the system achieved an average steady-state error of 2.44% using PID parameters Kp = 3.13, Ki = 8.69, and Kd = 0.25. The motor’s output power ranged from 136.88W at minimum load to 297.92W at maximum load, demonstrating improved efficiency and system performance

Brushless direct current (BLDC) motors are frequently used in dynamic applications. A Brushless DC Motor is similar to a Brushed DC Motor, except that as the names indicate, they are electronically commutated rather than using brushes for commutation. Brushes are utilized in conventional brushed direct current motors to transmit power to the rotor while they rotate in a fixed magnetic field. Small Brushless DC Motors have flourished as a result of current power electronics and microprocessor technology, both in terms of price and performance. This paper will discuss the history of BLDC motors, their different types, construction, operating principles, and several control mechanisms for driving BLDC motors in various industrial applications. Keywords: BLDC Motor, Pulse Width Modulation (PWM), Hall Effect Sensors, Sensorless control, Rotor, Stator, Back Emf, Trapezoidal Control, Sinusoidal Control, Field Oriented Control