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Yutana Jewajinda. Deep ANN-based RF-MRAS for speed-sensorless indirect field oriented control of induction motor drive for electric vehicles. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2025.
Deep ANN-based RF-MRAS for speed-sensorless indirect field oriented control of induction motor drive for electric vehicles
Name: Panupan Moungsri
Organization :
Silpakorn University. Faculty of Engineering and Industrial Technology
Name: Chaiwut Choorak
Organization :
Silpakorn University. Faculty of Engineering and Industrial Technology
Email :
choorak_c@silpakorn.edu
Name: Yutana Jewajinda
Organization :
Silpakorn University. Faculty of Engineering and Industrial Technology
keyword:
Speed control of electric motors
LCSH:
Artificial intelligence
LCSH:
Induction motors
LCSH:
Electric vehicles
LCSH:
Motor vehicle driving
Abstract:
This paper applies a deep neural network to rotor
flux-based field-oriented control of an induction motor drive for
electric vehicles. The proposed technique uses a deep neural
network in a model reference adaptive system (MRAS) to
estimate rotor speed. The proposed MRAS consists of a
reference and adaptive model with a learning mechanism. The
proposed MRAS with a deep neural network allows an accurate
approximation of non-linearity and increases the system's
response time. The performance of the proposed approach is
validated on different scenarios, namely, vehicle acceleration
conditions, constant speed, uneven road surface conditions, and
deceleration modes. The dynamic performance is simulated in
MATLAB/Simulink. The experimental results demonstrate the
proposed method's advantages over conventional PI-based
approaches for controlling sensorless induction drives for
electric vehicles.
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Created:
2025
Modified:
2025-06-19
Issued:
2025-06-19
บทความ/Article
application/pdf
BibliograpyCitation :
In Electrical Engineering Academic Association (Thailand) and King Mongkut's University of Technology North Bangkok. Department of Electrical and Computer Engineering. 13th International Electrical Engineering Congress (iEECON 2025) (P06291). Bangkok : Electrical Engineering Academic Association (Thailand), 2025
eng
©copyrights King Mongkut's University of Technology North Bangkok
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ใช้เวลา
0.034201 วินาที
Panupan Moungsri
| Title | Contributor | Type |
|---|---|---|
| Deep ANN-based RF-MRAS for speed-sensorless indirect field oriented control of induction motor drive for electric vehicles
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Panupan Moungsri;Chaiwut Choorak;Yutana Jewajinda | บทความ/Article |
Chaiwut Choorak
| Title | Contributor | Type |
|---|---|---|
| Deep ANN-based RF-MRAS for speed-sensorless indirect field oriented control of induction motor drive for electric vehicles
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Panupan Moungsri;Chaiwut Choorak;Yutana Jewajinda | บทความ/Article |
Yutana Jewajinda
| Title | Contributor | Type |
|---|---|---|
| Hybrid multi-population evolution based on genetic algorithm and regularized evolution for neural architecture search
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Phanomphon Yotchon;Yutana Jewajinda | บทความ/Article | |
| Deep ANN-based RF-MRAS for speed-sensorless indirect field oriented control of induction motor drive for electric vehicles
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Panupan Moungsri;Chaiwut Choorak;Yutana Jewajinda | บทความ/Article |