GKF ile ASM’nin eş-zamanlı stator ve rotor direnci kestirimleri

Yıl 2024, Cilt: 30 Sayı: 6, 771 - 778, 29.11.2024

Recep Yıldız , Murat Barut , Rıdvan Demir

Öz

Bu makalede, asenkron motor (ASM) sürücü sistemlerinin parametre
değişimlerine bağlı kestirim başarımlarının kötüleşmesi problemini
çözmek için genişletilmiş Kalman filtresine (GKF) dayalı yeni bir durum
ve parametre gözlemleyicisi tasarlanmıştır. Önerilen GKF tabanlı
gözlemleyici algoritması, ölçülen stator akımları ve rotor mekanik hızı
kullanılarak stator akımlarının ve rotor akılarının stator duran eksen
bileşenlerinin, rotor mekanik hızının, viskoz sürtünme terimi dâhil yük
momentinin, rotor direncinin, stator direncinin ve sistemin toplam
eylemsizliğinin tersinin eş-zamanlı kestirimlerini gerçekleştirmektedir.
Böylece, dirençlerin frekans ve sıcaklık bağımlı değişimlerinin
gözlemleyicide güncellenmek üzere kestirilmesi ASM sürücüsünün
kontrol başarımının iyileştirilmesi sağlar. Ek olarak, gözlemleyicinin
dinamik başarımını artırmak için mekanik parametreler olan yük
momenti ve sistemin toplam eylemsizliğinin tersi de kestirilmektedir.
Önerilen gözlemleyicinin kestirim başarımı ve ASM sürücüsünün
sağlamlığı, hız referansı ve parametrelerdeki değişimleri içeren zorlu
senaryolar altında test edilmektedir. Ayrıca, dokuzuncu dereceden
önerilen gözlemleyicinin kestirim başarımı, ölçülen hızı doğrudan
kullanarak aynı elektriksel parametreleri kestiren altıncı dereceden
GKF’nin kestirim başarımı ile karşılaştırılmıştır. Özetle, benzetim
sonuçları önerilen ASM sürücüsünün etkinliğini açıkça ortaya
koymaktadır.

Anahtar Kelimeler

Genişletilmiş Kalman filtresi, Asenkron motor, Rotor ve stator direnci kestirimi, Durum ve parametre kestirimi

Online stator and rotor resistance estimations of IM by using EKF

Öz

In this paper, a state and parameter observer, based on a novel extended
Kalman filter (EKF), is designed to solve the parameter variations
dependent estimation performance deterioration of induction motor
(IM) drive systems. The proposed EKF based observer algorithm
performs online estimation of the rotor mechanical speed, stator
stationary axis component of the stator currents and rotor fluxes, stator
resistance, rotor resistance, reciprocal of the total inertia of the system,
and load torque including viscous friction term in a single EKF by using
measured rotor mechanical speed and stator currents. Thus, frequency
and temperature-dependent variations of the resistances are estimated
to be updated in the observer, which leads to control performance
enhancement of the IM drive. Moreover, to rise the dynamic
performance of the observer, the load torque and reciprocal of the total
inertia of the system which are mechanical parameters are also
estimated. To verify the robustness of the IM drive and the estimation
performance of the proposed observer, they have been tested under
challenging scenarios including changes in parameters and speed
reference. Moreover, the estimation performance of the proposed ninth
order observer is compared with that of a sixth order EKF estimating
the same electrical parameters by using directly measured speed.
Ultimately, the simulation results obviously reveal the efficacy of the
proposed IM drive.

Anahtar Kelimeler

Extended Kalman filter, Induction motor, Rotor and stator resistance estimation, State and parameter estimation

Kaynakça

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