Combined Signal-Injection and Flux-Linkage Approach for Sensorless Control of Switched Reluctance Machines

Author(s):  
Diogo Pinto ◽  
Julien Pelletier ◽  
Wei Peng ◽  
Johan Gyselinck
2020 ◽  
Vol 6 (1) ◽  
pp. 26-36
Author(s):  
Ana Camila Ferreira Mamede ◽  
José Roberto Camacho ◽  
Rui Esteves Araújo

The main objective of modeling a switched reluctance machine is to derive a mathematical function to relate the outputs to the inputs. Due to the nonlinear relationship between the variables of torque, flux linkage, current and angular position of the rotor, Switched Reluctance Machine (SRM) modeling is a very challenging task and an open problem. Modeling is usually done in two situations, modeling a single machine, or modeling a set of machines. Each one must fulfill different requirements. This work presents a survey of different SRM modeling approaches, evaluating its advantages and limitations when modeling a single machine or a set of machines.


2020 ◽  
Vol 35 (3) ◽  
pp. 2787-2798 ◽  
Author(s):  
Lefei Ge ◽  
Iliya Ralev ◽  
Annegret Klein-Hessling ◽  
Shoujun Song ◽  
Rik W. De Doncker

Author(s):  
Shoujun Song ◽  
Jixi Zhong ◽  
Lefei Ge ◽  
Xujing Zhao ◽  
Ruiqing Ma ◽  
...  

2021 ◽  
Author(s):  
Md Ehsanul Haque ◽  
Anik Chowdhury ◽  
Okan Boler ◽  
Shuvajit Das ◽  
Yilmaz Sozer ◽  
...  

Electronics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 405
Author(s):  
Marcelo Vinícius de Paula ◽  
Tárcio André dos Santos Barros

Assessing the flux linkage is an important feature for electric machines, including switched reluctance machines. However, sensor calibration errors and noise impose a problem known as drift, which is caused by the integration process used to estimate the flux linkage. This paper proposes a flux linkage estimation with a drift cancellation technique. The technique accounts for the switched reluctance machine’s working and driving principles. Simulation and experimental results are used to validate the proposed method. Additionally, a goodness-of-fit analysis is performed to support the outcomes. A R 2 factor of 0.9823 is found between the experimentally and simulation-estimated flux linkage. The results indicate that the method works properly and may be further used in control techniques and iron losses estimation.


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