Perancangan Adaptive Extended Kalman Filter Untuk Speed Sensorless Control Motor Induksi di Unit Penggerak Kereta Api PT INKA

Anisa, Fadila (2020) Perancangan Adaptive Extended Kalman Filter Untuk Speed Sensorless Control Motor Induksi di Unit Penggerak Kereta Api PT INKA. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Dewasa ini, motor induksi banyak digunakan pada bidang transportasi sebagai penggerak berbasis listrik. Salah satu aplikasinya yaitu sebagai penggerak kereta listrik. Informasi kecepatan sangat dibutuhkan untuk sistem pengendalian kecepatan dengan struktur umpan balik (closed loop) sehingga dipasang sensor kecepatan. Akan tetapi sensor memiliki keterbatasan resolusi dan harga yang relative mahal. Untuk menggantikan peran sensor digunakan metode speed sensorless dengan berbasis observer sehingga dapat diaplikasikkan pada speed sensorless control induction motor. Pada Tugas Akhir ini, dirancanglah speed sensorless control pada motor induksi di unit penggerak kereta api PT. INKA menggunakan algoritma Adaptive Extended Kalman Filter (AEKF) sebagai estimator dan Direct Torque Control sebagai sistem pengendalian kecepatan tanpa sensor. Hasil pemodelan plant pada tegangan masukan 380 Volt motor induksi menunjukkan arus dan fluks konstan pada nilai 4,41 A dan 1,135 Wb di 0,35 detik. Hasil uji open loop respon kecepatan plant konstan pada 157,0796275 rad/s di detik ke 0,4 dan kecepatan keluaran estimator konstan pada 157,0796250 rad/s di detik yang sama. Nilai rata-rata error estimator 0,000058% dan rata-rata RMSE 0,0331.Hal ini menunjukkan algoritma AEKF sangat baik digunakan sebagai estimator kecepatan. Selain itu pengujian sistem kontrol dilakukan pada kecepatan 50 rpm, 80 rpm, dan 100 rpm untuk kecepatan rendah serta 350 rpm, 500 rpm, dan 650 rpm untuk kecepatan sedang. Hasil pengujian sistem kontrol menunjukkan tidak ada yang memiliki error steady state lebih dari 5% sehingga dapat dikatakan speed sensorless control yang telah dirancang dapat bekerja dengan baik.
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Nowadays, induction motors are widely used in the field of transportation as electric based movers. One application is as an electric train driver. Speed information is needed for a speed control system with a feedback structure (closed loop) so that a speed sensor is installed. However, the sensor has a high resolution and a relatively expensive price. To take the role of the sensor, the observer-based sensorless method is used so that it can be applied to the sensorless control of the speed of the induction motor. In this Final Project, sensorless speed control is designed on the induction motor in the drive unit PT. INKA uses the Adaptive Extended Kalman Filter (AEKF) algorithm as an estimator and Direct Torque Control as an sensorless speed control system. The results of plant modeling at the 380 Volt input voltage of the induction motor show a constant current and flux at a value of 4.41 A and 1.135 Wb at 0.35 seconds. The results of the open loop response of the plant speed response are constant at 157.0796275 rad / s at 0.4 seconds and the output speed estimator is constant at 157.0796250 rad / s at the same second. The average of error is 0,000058% and the average of RMSE is 0,0331. It show the AEKF algorithm very well to be used as a speed estimator. In addition, control system testing is carried out at speeds of 50 rpm, 80 rpm and 100 rpm for low speeds and 350 rpm, 500 rpm and 650 rpm for medium speeds. The results of the control system test prove that no one has a steady state error of more than 5% which can be approved by the speed sensorless control that has been designed is work properly.

Item Type:	Thesis (Other)
Additional Information:	RSF 629.836 Ani p-1 2020
Uncontrolled Keywords:	Adaptive Extended Kalman Filter, Direct Torque Control, Motor Induksi, Speed Sensorless Control.
Subjects:	T Technology > TF Railroad engineering and operation > TF872 Rails (Track) T Technology > TJ Mechanical engineering and machinery > TJ1058 Rotors T Technology > TJ Mechanical engineering and machinery > TJ217 Adaptive control systems T Technology > TJ Mechanical engineering and machinery > TJ223 PID controllers
Divisions:	Faculty of Industrial Technology and Systems Engineering (INDSYS) > Physics Engineering > 30201-(S1) Undergraduate Thesis
Depositing User:	Fadila Anisa
Date Deposited:	03 Jan 2024 08:17
Last Modified:	03 Jan 2024 08:17
URI:	http://repository.its.ac.id/id/eprint/74514

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