Novel version of bi input-extended Kalman filter for speed-sensorless control of induction motors with estimations of rotor and stator resistances, load torque, and inertia
Küçük Resim Yok
Tarih
2016
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEY
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
This study aims to develop a novel version of bi input-extended Kalman filter (BI-EKF)-based estimation technique in order to increase the number of state and parameter estimations required for speed-sensorless direct vector control (DVC) systems, which perform velocity and position controls of induction motors (IMs). For this purpose, all states required for the speed-sensorless DVC systems, besides the stator resistance R-s, the rotor resistance R-r, the load torque t(L) including the viscous friction term, and the reciprocal of total inertia 1/j(T), are simultaneously estimated by the novel BI-EKF algorithm using the measured phase currents and voltages. The effectiveness of the proposed speed-sensorless DVC systems is tested by simulations under the challenging variations of R-s, R-r, t(L), j(T), and velocity/position reference. Later, the state and parameter estimations of the novel BI-EKF algorithm are confirmed with real-time experiments in a wide speed range. Finally, in both transient and steady states, a satisfactory estimation and control performance that make this study unique are achieved.
Açıklama
Anahtar Kelimeler
Induction motor, extended Kalman filter, sensorless control, rotor-stator resistance estimation, load torque estimation, inertia estimation
Kaynak
TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES
WoS Q Değeri
Q4
Scopus Q Değeri
Q3
Cilt
24
Sayı
5
