An Improvement in Dynamic Behavior of Single Phase PM Brushless DC Motor Using Deep Neural Network and Mixture of Experts
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F23%3A10254573" target="_blank" >RIV/61989100:27240/23:10254573 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10162182" target="_blank" >https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10162182</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ACCESS.2023.3289409" target="_blank" >10.1109/ACCESS.2023.3289409</a>
Alternative languages
Result language
angličtina
Original language name
An Improvement in Dynamic Behavior of Single Phase PM Brushless DC Motor Using Deep Neural Network and Mixture of Experts
Original language description
Brushless DC motors play a vital role as a workhorse in many applications, especially home appliances. In the competitive world of the day, a brushless DC motor is a wise choice for many applications because of its high power density, a simple driving circuit, and high efficiency. Accordingly, demonstrating the feasibility of a new controller on this type of motor has undoubtedly paramount importance. Two methods of speed controllers, namely linear-quadratic regulator, and proportional-integral-derivative, are mixed using a mixture of experts (MoE) for a single-phase PM brushless DC external rotor motor. The dynamic model of the SP PM BLDC ER motor characterizes the behavior of the motor, involving cogging torque and electromotive force (EMF) gained from 2D finite element analyses. The motor is supplied by a pulse width modulation inverter with a constant voltage source. The results disclose that the SP PM BLDC performance is enhanced and more robust during load disturbance. ANSYS and MATLAB environments are used for obtaining finite element analysis and dynamic analysis of single-phase PM brushless DC external rotor motors, respectively. The merits of the proposed approach are validated through implementing a low-scale experimental setup.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20200 - Electrical engineering, Electronic engineering, Information engineering
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Access
ISSN
2169-3536
e-ISSN
2169-3536
Volume of the periodical
11
Issue of the periodical within the volume
June 2023
Country of publishing house
US - UNITED STATES
Number of pages
12
Pages from-to
64260-64271
UT code for WoS article
001021935000001
EID of the result in the Scopus database
2-s2.0-85163499389