Torque Analysis of 2 KW BLDC (Brushless Direct Current) Motor with Speed Variations in Electric Cars E-Falco

The motor releases torque and power to drive an electric car by carrying the load from a start position until it travels at the desired speed. The KMLI E-Falco electric car uses a BLDC type electric motor with a power capacity of 2 kW. To find out the amount of torque of a 2 kW BLDC motor when driving with variations in speed, it can be done by manual calculations using the torque equation and doing a dynotest test. The dynotest results show that the motor torque at the speed: 1 km/h is 1 Nm, 10 km/h is 131 Nm, 13 km/h is 228 Nm, 20 km/h is 225 Nm, 30 km/h is 219 Nm, 40 km / h is 188 Nm, 50 km / hour is 145 Nm, 60 km / h is 113 Nm, and 70 km / h is 85 Nm. From the results of the dynotest, it shows that the peak torque occurs at a speed of 13 km / h at 228 Nm. Racing software installed in the controller can increase the motor torque by four times at a speed variation of 13-70 km/h based on the results of the dynotest above. Keywords: motor, BLDC, torque, speed, acceleration.

Brushless direct current motor with MV-PID controller management system based on arm microcontroller

Purpose The brushless direct current motor (BLDCM) is widely accepted and adopted by many industries instead of direct current motors due to high reliability during operation. Brushless direct current (BLDC) has outstanding efficiency as losses that arise out of voltage drops at brushes and friction losses are eliminated. The main factor that affects the performance is temperature introduced in the internal copper core windings. The control of motor speed generates high temperature in BLDC operation. The high temperature is due to presence of ripples in the operational current. The purpose is to present an effective controlling mechanism for speed management and to improve the performance of BLDCM to activate effective management of speed. Design/methodology/approach The purpose is to present an optimal algorithm based on modified moth-flame optimization algorithm over recurrent neural network (MMFO-RNN) for speed management to improve the performance. The core objective of the presented work is to achieve improvement in performance without affecting the design of the system with no additional circuitry. The management of speed in BLDCM has been achieved through reduction or minimization of ripples encircled with torque of the motor. The implementation ends in two stages, namely, controlling the loop of torque and controlling the loop of speed. The MMFO-RNN starts with error optimization, which arises from both the loops, and most effective values have been achieved through MMFO-RNN protocol. Findings The parameters are enriched with Multi Resolution Proportional Integral and Derivative (MRPID) controller operation to achieve minimal ripples for the torque of BLDC and manage the speed of the motor. The performance is increased by adopting this technique approximately 12% in comparison with the existing methodology, which is the main contributions of the presented work. The outcomes are analyzed with the existing methodologies through MATLAB Simulink tool, and the comparative analyses suggest that better performance of the proposed system produces over existing techniques, and proto type model is developed and cross verifies the proposed system. Originality/value The MMFO-RNN starts with error optimization, which arises from both the loops, and most effective values have been achieved through MMFO-RNN protocol. The parameters are enriched with MRPID controller operation to achieve nil or minimal ripples and to encircle the torque of Brushless Direct Current and manage the speed.

Performance Test of Three-Phase Brushless Direct Current Motor Axial Flux with Differences Diameter of Neodymium Type Permanent Magnet

Technology that is growing rapidly and innovations that have sprung up in the electrical field today are driving the use of electricity as a source of energy to do work. Electric motor is one component that is very popular in the industrial world and households that are useful to human life. In addition to DC motors and induction motors, there are also 3 phase brushless direct current (BLDC) motors which are a type of synchronous motor where magnetic fields are produced by rotor and stator at the same frequency. The rotor is a moving part of the brushless direct current motor which is a place of permanent magnet called a pole. This paper discusses the performance of brushless direct current 3 phase axial flux motors with different diameters of neodymium type permanent magnets. Tests carried out using neodymium permanent magnets with diameters of 15mm x 2mm and 20mm x 2mm were tested without using a load and using load. The parameters used in testing motor performance include speed, torque, and motor power with a source voltage of 12V, 16V, 20V, and 24V. The test results shows that the speed value of a BLDC motor using permanent magnets with a size of 20mm x 2mm is greater than that of permanent magnets of 15mm x 2mm. The same thing applies to the value of the power produced while, for the value of torque when the motor uses a permanent magnet of 15mm x 2mm will be greater than that of a motor using a permanent magnet of 20mm x 2mm.

Torque Control Oriented Modeling of a Brushless Direct Current Motor (BLDCM) Based on the Extended Park's Transformation

The wheeled mobile robots have recently become a better choice for repetitive tasks and especially in the agricultural field, but the existing constraint remains in its electrical motor, either in its consumption or its control. Therefore, we will focus on the Brushless Direct Current Motor (BLDCM) included on the robot wheels. Hence, the objective of this paper is to provide a model of BLDCM to have both maximum torque and a reduced torque ripple. Indeed, it is important to give a mathematical model that correctly represents the motor in three phases reference frame. To reduce the complexity of the model, we have used the extended park reference frame, which provides a biphasic representation in order to control the current using Proportional Integral Controller (PI Controller). The angular velocity of the motor is controlled using two types of regulators; ones called PI Controller and the other is Fuzzy Logic Controller (FLC) to compare its performance. The motor is attached to an inverter, which is controlled using a Full-Wave offset method. The modeling machine is done and validated using MATLAB Simulink Library. The simulation results of the modeling system are evaluated to have the profile of the wheel speed rotating freely, and the energetic efficiency of the BLDCM during functioning.