scholarly journals Online MTPA Control Strategy for DTC Synchronous-Reluctance-Motor Drives

2011 ◽  
Vol 26 (1) ◽  
pp. 20-28 ◽  
Author(s):  
Silverio Bolognani ◽  
Luca Peretti ◽  
Mauro Zigliotto
Keyword(s):  
Control Strategy ◽  
Motor Drives ◽  
Synchronous Reluctance Motor ◽  
Reluctance Motor

Enhanced Emotional and Speed Deviation Control of Synchronous Reluctance Motor Drives

2019 ◽  
Vol 34 (2) ◽  
pp. 604-612 ◽  
Author(s):  
Ehsan Daryabeigi ◽  
Ahmad Mirzaei ◽  
Hossein Abootorabi Zarchi ◽  
Sadegh Vaez-Zadeh
Keyword(s):  
Motor Drives ◽  
Synchronous Reluctance Motor ◽  
Reluctance Motor

Deviation Model-Based Control of Synchronous Reluctance Motor Drives With Reduced Parameter Dependency

2019 ◽  
Vol 34 (7) ◽  
pp. 6697-6705 ◽  
Author(s):  
Ehsan Daryabeigi ◽  
Ahmad Mirzaei ◽  
Hossein Abootorabi Zarchi ◽  
Sadegh Vaez-Zadeh
Keyword(s):  
Motor Drives ◽  
Model Based Control ◽  
Model Based ◽  
Synchronous Reluctance Motor ◽  
Reluctance Motor ◽  
Parameter Dependency

Taguchi-EM-AI Design Optimization Environment for SynRM Drives in Traction Applications

2021 ◽  
Vol 35 (11) ◽  
pp. 1372-1373
Author(s):  
A.A. Arkadan ◽  
N. Al Aawar
Keyword(s):  
Design Optimization ◽  
Search Algorithm ◽  
Motor Drives ◽  
Computational Time ◽  
Synchronous Reluctance Motor ◽  
Reluctance Motor ◽  
Motor Drive System ◽  
Taguchi Orthogonal Arrays ◽  
Optimization Search

Multi-objective design optimization environments are used for electric vehicles and other traction applications to arrive at efficient motor drives. Typically, the environment includes characterization modules that involve the use of Electromagnetic Finite Element and State-Space models that require large number of iterations and computational time. This work proposes the utilization of a Taguchi orthogonal arrays method in conjunction with a Particle Swarm Optimization search algorithm to reduce computational time needed in the design optimization of electric motors for traction applications. The effectiveness of the Taguchi method in conjunction with the optimization environment is demonstrated in a case study involving a prototype of a Synchronous Reluctance Motor drive system.

Sign in / Sign up

Export Citation Format

Share Document