Desain Kontroler Berbasis Algoritme PSO untuk Stasiun Pengisian Daya pada Electric Vehicle dengan Baterai NiMH

Enola, Nuh (2022) Desain Kontroler Berbasis Algoritme PSO untuk Stasiun Pengisian Daya pada Electric Vehicle dengan Baterai NiMH. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Kendaraan listrik merupakan suatu penemuan yang tengah berkembang pesat saat ini. Berbagai penelitian mengenai kendaraan listrik tidak berhenti dilakukan, termasuk mengenai sistem pengecasan. Banyak jenis baterai yang digunakan untuk kendaraan listrik, salah satunya adalah baterai NiMH. Penelitian mengenai bagaimana mengoptimalkan pengecasan baterai juga telah banyak dilakukan, salah satunya dengan memanfaatkan intelligent algorithm. Namun, cara ini jarang diimplementasikan secara real-time dan hanya melalui bantuan software komputer. Pada tugas akhir ini, dibahas mengenai implementasi intelligent algorithm PSO (Particle Swarm Optimization) sebagai metode pengoptimalan secara real time pada charger controller dengan harapan mampu memberikan solusi terkait pengoptimalan pengecasan sesuai kebutuhan pengguna. Untuk 3 kondisi pengecasan pengoptimalan pada prototype menghasilkan perhitungan dengan error cost masing-masing 0.33%, 7.22%, dan 5.55% dibandingkan dengan hasil pada simulasi. Dengan nilai ini, implementasi PSO pada sistem real-time telah mencapai tingkat keberhasilan sebesar 95%.
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Electric vehicles are an invention that is currently developing rapidly. Various studies on electric vehicles do not stop, including the charging system. Many types of batteries are used for electric vehicles, including NiMH Battery. There is also a lot of research on how to optimize battery charging, one of which is by using intelligent algorithms. However, this method is rarely implemented in real-time and only through the help of the computer software. In this final project, we discuss the implementation of the intelligent algorithm PSO (Particle Swarm Optimization) as a real time optimization method on the charger controller with the hope of providing solutions according to the user needs . For the 3 optimization charging conditions the Prototype results in calculations with error costs of 0.33%, 7.22%, and 5.55%, respectively, compared to the results in the simulation. With this value, the implementation of PSO in real time systems has achieved a 95% success rate.

Item Type:	Thesis (Other)
Additional Information:	RSE 629.836 Eno d-1
Uncontrolled Keywords:	NiMH, PSO, Kendaraan Listrik, Charger Controller
Subjects:	T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL220 Electric vehicles and their batteries, etc.
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20201-(S1) Undergraduate Thesis
Depositing User:	- Davi Wah
Date Deposited:	11 Sep 2024 04:29
Last Modified:	11 Sep 2024 04:29
URI:	http://repository.its.ac.id/id/eprint/115538

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