dc motor
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2022 ◽  
Vol 166 ◽  
pp. 108415
Author(s):  
Grzegorz Kudra ◽  
Jose M. Balthazar ◽  
Angelo M. Tusset ◽  
Grzegorz Wasilewski ◽  
Bartosz Stańczyk ◽  
...  

2022 ◽  
Author(s):  
Irving Morgado-González ◽  
Jose Angel Cobos-Murcia ◽  
Marco Antonio Marquez-Vera ◽  
Omar Arturo Dominguez-Ramirez

Abstract This research proposes to obtain a mathematical model that describes the dynamic operation of a brushed DC motor, to obtain a state function considering the electrical, mechanical, and thermal effects of the DC motor. The dynamic evolution of the proposed function is evaluated by simulation using Matlab software, and by applying different values of the step type inputs for the brushed motor excitation employing pulse width modulation (PWM) to obtain a wide range of operations. Experimental results show that the developed state function, provides a reliable approximation to estimate the voltage, armature current, mechanical torque, and temperature of the brushed DC motor, showing an error percentage of 0.2%.


Author(s):  
Abhas Kanungo ◽  
Monika Mittal ◽  
Lillie Dewan ◽  
Vikas Mittal ◽  
Varun Gupta
Keyword(s):  

2022 ◽  
pp. 157-179
Author(s):  
Arezki Fekik ◽  
Mohamed Lamine Hamida ◽  
Hamza Houassine ◽  
Hakim Denoun ◽  
Sundarapandian Vaidyanathan ◽  
...  

2022 ◽  
Vol 1211 (1) ◽  
pp. 012004
Author(s):  
V N Antipov ◽  
A D Grozov ◽  
A V Ivanova

Abstract The paper deals with the development and simulation results of the switched reluctance motor for electric drive of mine battery electric locomotives instead of the DRT-14 DC motor. The switched reluctance motor parameters are obtained based on numerical calculation of the magnetic field by QuickField program and are embedded in MATLAB/Simulink model of a switched reluctance motor created for 8/6 magnetic system configuration. SRM-14-615 has the mechanical characteristics as DC motor DRT-14 and meets the required operating modes as part of the AM8D mine battery electric locomotive. Also two types of models using methods and techniques of the artificial intelligence theory are presented: a model with a fuzzy control system in the Fuzzy Logic Toolbox package and a model with a neural network control system in the Neural Network Toolbox package.


2021 ◽  
Vol 14 (4) ◽  
pp. 383-393
Author(s):  
Zhengrong Wang ◽  
Rennian Li ◽  
Gaoping Xu ◽  
Wei Han ◽  
Mingkuo Bian ◽  
...  

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