Harapan, Muhamad Jordan Toyimullah (2026) Desain Dan Analisis Konverter DC-DC Dengan Metode Kontrol Arus Berbasis Artificial Neural Network Untuk Mitigasi Arus Harmonik Pada Stasiun Pengisian Kendaraan Listrik. Other thesis, Institut Teknologi Sepuluh Nopember.
![[thumbnail of 5022221147-Undergraduate_Thesis.pdf]](http://repository.its.ac.id/style/images/fileicons/text.png) |
Text
5022221147-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only Download (4MB) | Request a copy |
Abstract
Penelitian ini merancang dan menganalisis sistem pengisian daya baterai EV (Electric Vehicle) dengan daya 7 kW menggunakan PFC Boost Converter yang dikontrol dengan metode Artificial Neural Network (ANN) untuk menekan Total Harmonic Distortion (THD) dan meningkatkan Power Factor (PF), serta Buck Converter CC-CV untuk pengisian baterai. Sistem terdiri dari front-end AC-DC PFC Boost Converter menggunakan ANN pada average current mode control untuk menjaga arus input sinusoidal sefase dengan tegangan input, serta back-end DC-DC Buck Converter dengan kontrol PI untuk metode pengisian Constant Current-Constant Voltage (CC-CV) pada baterai BYD Atto 3. Simulasi dilakukan menggunakan MATLAB/Simulink. Hasil penelitian menunjukkan bahwa kontroler ANN berhasil menekan THD arus input dari 88,21% (tanpa PFC) menjadi 2,35% (mode CC) dan 2,34% (mode CV), serta meningkatkan true power factor dari 0,5408 menjadi 0,9992. Training ANN voltage loop mencapai korelasi R = 0,99978 dengan konvergensi 11 epoch, sedangkan current loop mencapai R = 0,94946 dengan best validation MSE = 0,18584. Sistem CC-CV berhasil mengisi baterai dengan aman melalui transisi otomatis dari CC ke CV pada tegangan 450 V dengan laju penurunan arus 229 mA/s.
========================================================================================================================================
This research designs and analyzes a 7 kW EV (Electric Vehicle) battery charging system using a PFC Boost Converter controlled by Artificial Neural Network (ANN) to suppress Total Harmonic Distortion (THD) and improve Power Factor (PF), as well as a Buck Converter CC-CV for battery charging. The system consists of a front-end AC-DC PFC Boost Converter using ANN on average current mode control to maintain sinusoidal input current in-phase with the input voltage, and a back-end DC-DC Buck Converter with PI control for Constant Current-Constant Voltage (CC-CV) charging method on a BYD Atto 3 battery. Simulation is performed using MATLAB/Simulink. The results show that the ANN controller successfully suppressed input current THD from 88.21% (without PFC) to 2.35% (CC mode) and 2.34% (CV mode), and improved true power factor from 0.5408 to 0.9992. ANN voltage loop training achieved correlation R = 0.99978 with convergence in 11 epochs, while current loop achieved R = 0.94946 with best validation MSE = 0.18584. The CC-CV system successfully charged the battery safely through automatic transition from CC to CV at 450 V with current decay rate of 229 mA/s.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | PFC Boost Converter, Artificial Neural Network, Total Harmonic Distortion, Power Factor, CC-CV, Buck Converter, EV Charging Station. |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK2943 Battery chargers. |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20201-(S1) Undergraduate Thesis |
| Depositing User: | Muhamad Jordan Toyimullah Harapan |
| Date Deposited: | 22 Jul 2026 08:52 |
| Last Modified: | 22 Jul 2026 08:52 |
| URI: | http://repository.its.ac.id/id/eprint/136436 |
Actions (login required)
 |
View Item |