Saturable and Decoupled Constant-Parameter VBR Model for Six-Phase Synchronous Machines in State-Variable Simulation Programs

2019 ◽  
Vol 34 (4) ◽  
pp. 1868-1880 ◽  
Author(s):  
Navid Amiri ◽  
Seyyedmilad Ebrahimi ◽  
Juri Jatskevich ◽  
Hermann W. Dommel
2020 ◽  
Vol 35 (1) ◽  
pp. 119-129
Author(s):  
Navid Amiri ◽  
Seyyedmilad Ebrahimi ◽  
Yingwei Huang ◽  
Juri Jatskevich ◽  
Steven D. Pekarek

2012 ◽  
Vol 27 (3) ◽  
pp. 634-645 ◽  
Author(s):  
Mehrdad Chapariha ◽  
Liwei Wang ◽  
Juri Jatskevich ◽  
Hermann W. Dommel ◽  
Steven D. Pekarek

2017 ◽  
Vol 32 (2) ◽  
pp. 548-559 ◽  
Author(s):  
Navid Amiri ◽  
Seyyedmilad Ebrahimi ◽  
Mehrdad Chapariha ◽  
Juri Jatskevich ◽  
Hermann W. Dommel

2015 ◽  
Vol 30 (2) ◽  
pp. 441-452 ◽  
Author(s):  
Mehrdad Chapariha ◽  
Francis Therrien ◽  
Juri Jatskevich ◽  
Hermann W. Dommel

2019 ◽  
Vol 2019 (17) ◽  
pp. 3609-3613 ◽  
Author(s):  
Riccardo Antonello ◽  
Luca Peretti ◽  
Fabio Tinazzi ◽  
Mauro Zigliotto

1994 ◽  
Vol 4 (10) ◽  
pp. 1999-2012 ◽  
Author(s):  
Nabil Derbel ◽  
Mohamed B.A. Kamoun ◽  
Michel Poloujadoff

2020 ◽  
Vol 64 (1-4) ◽  
pp. 431-438
Author(s):  
Jian Liu ◽  
Lihui Wang ◽  
Zhengqi Tian

The nonlinearity of the electric vehicle DC charging equipment and the complexity of the charging environment lead to the complex and changeable DC charging signal of the electric vehicle. It is urgent to study the distortion signal recognition method suitable for the electric vehicle DC charging. Focusing on the characteristics of fundamental and ripple in DC charging signal, the Kalman filter algorithm is used to establish the matrix model, and the state variable method is introduced into the filter algorithm to track the parameter state, and the amplitude and phase of the fundamental waves and each secondary ripple are identified; In view of the time-varying characteristics of the unsteady and abrupt signal in the DC charging signal, the stratification and threshold parameters of the wavelet transform are corrected, and a multi-resolution method is established to identify and separate the unsteady and abrupt signals. Identification method of DC charging distortion signal of electric vehicle based on Kalman/modified wavelet transform is used to decompose and identify the signal characteristics of the whole charging process. Experiment results demonstrate that the algorithm can accurately identify ripple, sudden change and unsteady wave during charging. It has higher signal to noise ratio and lower mean root mean square error.


2012 ◽  
Vol 132 (9) ◽  
pp. 922-930 ◽  
Author(s):  
Hirofumi Aoki ◽  
Tadashi Fukami ◽  
Kazuo Shima ◽  
Toshihiro Tsuda ◽  
Mitsuhiro Kawamura

Sign in / Sign up

Export Citation Format

Share Document