Desain Dan Simulasi Model Predictive Control Pada Sistem Pembagian Daya Untuk Kendaraan Listrik Hibrida Fuel Cell - Baterai

Bijana, Muhammad Rasyendria Rangga (2022) Desain Dan Simulasi Model Predictive Control Pada Sistem Pembagian Daya Untuk Kendaraan Listrik Hibrida Fuel Cell - Baterai. Other thesis, Institut Teknologi Sepuluh Nopember.

Text 07111840000047Undergraduate_Thesis.pdf - Accepted Version Download (3MB)

Abstract

Penelitian Tugas Akhir ini meniliti performansi implementasi Model Predictive Control (MPC) pada sistem manajemen energi dari kendaraan listrik hibrida fuel cell – baterai. Dilakukan tiga variasi parameter pada kontroler MPC yaitu variasi nilai horizon, objective function, dan pembobotan pada objective function. Pada pengujian variasi nilai horizon kontroler MPC yang didesain menunjukan bahwa semakin tinggi nilai horizon yang digunakan SOC dan SOC akhir semakin cepat dan semakin mendekati SOC optimal yang ditentukan dengan kompensasi konsumsi hidrogen yang lebih tinggi. Pengujian variasi objective function menunjukan bahwa objective function yang diimplementasikan pada kontroler MPC mempengaruhi karakteristik respon sistem, Ditemui pada pengujian objective function penggunaan daya fuel cell optimal menghasilkan keluaran daya fuel cell dengan jangkauan efisiensi kerja 57% - 60% bila dibandingkan dengan objective function lainnya yang bekerja pada jangkauan efisiensi 49.2% - 57%. Terakhir pada pengujian variasi nilai pembobotan ditemui bahwa semakin tinggi pembobotan pada sebuah ekspresi pada objective function maka optimizer akan semakin mempenalisasi ekspresi tersebut sehingga solver akan meminimalkan ekspresi tersebut dalam proses optimasi, Maka dari itu pemberian nilai parameter kontroler MPC perlu diperhatikan agar karakteristik respon sesuai dengan desian yang diinginkan. Perlu diketahui pada penelitian ini tidak digunakan model prediksi kecepatan sehingga diasumsikan bahwa kecepatan telah diketahui tanpa adanya ketidakpastian.
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This Final Project research investigates the performance of the implementation of Model Predictive Control (MPC) on Energy Management System (EMS) used in Fuel Cell Hybrid Electric Vehicle (FCHEV). Simulation has been done with three MPC parameter variations which are horizon length variation, objective function variation, and weighting value variation. Simulation of the variation horizon length shows that the higher the horizon length used, the faster SOC get to the optimal SOC and the final SOC will be closer to optimal SOC that been determined in compensation of higher hydrogen consumption. Simulation of the variation of objective function showed that the objective function terms will affect the system response characteristic, the simulation of objective function for maximizing fuel cell efficiency showed that the output fuel cell power used is working on higher efficiency range which is 57% - 60% in comparison with other objective function which range on 49.2% - 57%. Lastly on Simulation of the variation of weighting value showed that the higher value used on one term in objective function the more penalized it will get by the solver, so the solver will minimize that term more on optimization process. That is why there is need to consider the system design in order to choose the right tuning value for MPC parameter. However, this final project research does not include speed prediction model, but it assumes that the speed is known without uncertainties.

Item Type:	Thesis (Other)
Additional Information:	RSE 629.893 2 Bij d-1 • 2022
Uncontrolled Keywords:	Model Predictive Control, Kendaraan Listrik Hibrida Fuel Cell – Baterai, Sistem Manajemen Energi, Pembagian Daya, SOC
Subjects:	T Technology > TJ Mechanical engineering and machinery > TJ217.6 Predictive Control T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK2931 Fuel cells T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK2941 Storage batteries
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20201-(S1) Undergraduate Thesis
Depositing User:	- Davi Wah
Date Deposited:	02 Oct 2024 05:24
Last Modified:	02 Oct 2024 05:24
URI:	http://repository.its.ac.id/id/eprint/115718

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