An online identification method for both stator-and rotor resistances of induction motors without rotational transducers

2000 ◽  
Vol 47 (4) ◽  
pp. 842-853 ◽  
Author(s):  
In-Joong Ha ◽  
Sang-Hoon Lee
Keyword(s):  
Induction Motors ◽  
Online Identification ◽  
Identification Method

scholarly journals Online diagnosis of supercapacitors using extended Kalman filter combined with PID corrector

2021 ◽  
Vol 12 (3) ◽  
pp. 1521
Author(s):  
Zoubida Bououchma ◽  
Jalal Sabor
Keyword(s):  
Electrochemical Impedance ◽  
New Method ◽  
Specific Power ◽  
Attractive Alternative ◽  
State Of Health ◽  
Energy Storage Devices ◽  
Good Efficiency ◽  
Storage Devices ◽  
Online Identification ◽  
Identification Method

<span>Supercapacitors are electrical energy storage devices with a high specific power density, a long cycle life and a good efficiency, which make them attractive alternative storage devices for various applications. However, supercapacitors are subject to a progressive degradation of their perfor-mance because of aging phenomenon. Therefore, it is very important to be able to estimate their State-of-Health during operation. Electrochemical Impedance Spectroscopy (EIS) is a very recog-nized technique to determine supercapacitors’ state-of-health. However, it requires the interrup-tion of system operation and thus cannot be performed in real time (online). In this paper, a new online identification method is proposed based on extended Kalman observer combined with a complementary PID corrector. The proposed method allows to accurately estimating supercapacitor resistance and capacitance, which are the main indicators of supercapacitor state-of-health. The new online identification method was applied for two voltage/current profiles using two different supercapacitors. The resistance/capacitance estimated by the new method and the conventional EKF were compared with those obtained by an experimental offline method. In comparison with conventional EKF, the capacitance obtained by the new method is significantly more accurate.</span>

MICROCONTROLLER BASED ONLINE IDENTIFICATION OF VARIABLE PARAMETERS IN INDUCTION MOTORS

1995 ◽  
Vol 23 (3) ◽  
pp. 353-360 ◽  
Author(s):  
ZUORONG ZHANG ◽  
GRAHAM E. DAWSON ◽  
TONY R. EASTHAM
Keyword(s):  
Induction Motors ◽  
Variable Parameters ◽  
Online Identification
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