Search Results (5)

When magnetic saturation occurs during the operation of a permanent magnet (PM) slotless brushless DC motor, the material permeability will no longer be a constant value, and the neglected magnetic saturation model used for motor optimization will no longer be applicable. And considering that the increase in motor torque will lead to a high temperature rise of the winding, therefore, an electromagnetic heat coupling model applicable to the occurrence of magnetic saturation in the motor is established, and the model is utilized in combination with the particle swarm algorithm to enhance the maximum output torque of the motor. Firstly, a 100 W, 16,400 r/min high-speed PM slotless DC brushless motor is taken as the object of study, and its electromagnetic–thermal coupling model is established to derive the analytical equations for the electromagnetic torque with respect to the split ratio, the thickness of the stator yoke, the PM thickness, and the copper loss. Secondly, based on the modeling, the motor was optimized using a particle swarm algorithm to maximize the output torque and minimize the copper loss. Finally, a prototype was fabricated and verified with the prototype through no-load and load experiments. The difference between the theoretical maximum output torque and the experimental maximum output torque is less than 8%. The results show that this method can effectively predict the maximum output torque of the motor in the case of magnetic saturation, and the model is suitable for increasing the maximum output torque of slotless brushless DC motors under space constraints. Full article

This paper presents research conducted on the development of an innovative system to increase the amount of energy recovered from a high-speed kinetic energy storage based on a three-phase permanent magnet brushless (PM BLDC) motor/generator (mogen) with a flywheel-shaped rotor, compared to the efficiency obtained for standard solutions with power electronics systems. This kinetic energy storage is currently under development. In the system presented in the paper, the regulated DC output voltage of the 6T thyristor bridge is controlled with a tolerance within ±10% of the reference voltage for a variable power load. The input voltage of the rectifier is a three-phase trapezoidal-shaped voltage from the rotating mogen, whose amplitude can vary from 0 to 650 V and frequency from 0 to 250 Hz voltage. The article presents example results of simulation tests of the mogen-based kinetic energy storage model with the thyristors’ firing angle control system. As part of the research, a prototype of the rectifier was built on a laboratory scale, to confirm the validity of the assumptions regarding the synchronization and control method of the bridge using a new design of the thyristor gate drivers. Full article

With the development of reliability theory, people realized that “absolutely reliable” machines could not be made. With its incomparable advantages, the high-speed permanent-magnet brushless DC motor is usually used in the symmetrical structure of high-speed operation working systems, which at present are widely used in aerospace and other fields. The structure of the manufacturing process involves a strict processing, but in the process of work failure could still occur. No matter what field the high-speed permanent magnet brushless DC motor is applied to, it is very important to identify states and run fault diagnosis, which is of great significance to maintain the reliability of the motor and its working system. In this study, the fault diagnosis method of a high-speed permanent-magnet brushless DC motor is studied, and a combination model of modified gray wolf optimization algorithm (MGWO) and support vector machine (SVM) have been proposed for the motor fault diagnosis research. Based on the traditional gray wolf optimization (GWO) algorithm, the optimization performance of the algorithm is improved by initializing the population through a tent map and introducing a sine wave dynamic adaptive factor. Then the modified algorithm is used to optimize the internal parameters of SVM to improve the diagnostic accuracy of the model. Through the signal acquisition test, the current signals under different fault states and faultless states were collected, and the current signal data set required for the experiment is obtained. The experimental result showed that, compared with GWO or sailfish optimization (SFO) optimized SVM models, Extreme learning machine and Back Propagation neural network classical classification models, the fault diagnosis accuracy of the proposed model is the highest, proving the excellent classification performance and good robustness of the MGWO-SVM model. Full article

This paper proposes the novel idea of eliminating the front-end converters used indirect current (DC) bus voltage variation, thereby allowing for control of the speed of the brushless direct current (BLDC) motors in the two-quadrant operation of a permanent magnet brushless direct current (PMBLDC) motor, which is required for multiple bi-directional hot roughing steel rolling mills. The first phase of steel rolling, the manufacture of plates, strips etc., using hot slabs from the continuous casting stage, is carried out for thickness reduction, before the same is sent to the finishing mill for further mechanical processing. The hot roughing process involves applying high, compressive pressure, using a hydraulically operated mechanism, through a pair of backup rolls and work rolls for rolling. Overall, the processes consist of multiple passes of forward and reverse rolling at increasing roll speeds. The rolling process was modeled, taking into account parameters like roller dimensions, angle and length of contact, and rolling force, at various temperatures, using actual data obtained from a steel mill. From this data, speed and torque profiles at the motor shaft, covering the entire rolling process, were created. A profile-based feedback controller is proposed for setting the six-pulse inverter frequency and parameters of the pulse width modulated (PWM) waveform for current control, based on Hall sensor position, and the same is implemented for closed loop operation of the brushless direct current motor drive system. The performance enhancement of the two different controllers was also evaluated, during the rolling of 1005 hot rolled (HR) steel, and was taken into consideration in the research analysis. The entire process was simulated in the MATLAB/Simulink platform, and the results verify the suitability of an entire-drive system for industrial steel rolling applications. Full article

Photovoltaic (PV) water pumping systems are becoming popular these days. In PV water pumping, the role of the converter is most important, especially in the renewable energy-based PV systems case. This study focuses on one such application. In this proposed work, direct current (DC) based intermediate DC-DC power converter, i.e., a modified LUO (M-LUO) converter is used to extricate the availability of power in the high range from the PV array. The M-LUO converter is controlled efficiently by utilizing the Grey Wolf Optimizer (GWO)-based maximum power point tracking algorithm, which aids the smooth starting of a brushless DC (BLDC) motor. The voltage source inverter’s (VSI) fundamental switching frequency is achieved in the BLDC motor by electronic commutation. Hence, the occurrence of VSI losses due to a high switching frequency is eliminated. The GWO optimized algorithm is compared with the perturb and observe (P&O) and fuzzy logic based maximum power point tracking (MPPT) algorithms. However, by sensing the position of the rotor and comparing the reference speed with the actual speed, the speed of the BLDC motor is controlled by the proportional-integral (PI) controller. The recent advancement in motor drives based on distributed sources generates more demand for highly efficient permanent magnet (PM) motor drives, and this was the beginning of interest in BLDC motors. Thus, in this paper, the design of a high-gain boost converter optimized by a GWO algorithm is proposed to drive the BLDC-based pumping motor. The proposed work is simulated in MATLAB-SIMULINK, and the experimental results are verified using the dsPIC30F2010 controller. Full article