Haikal, Muhammad (2021) Optimasi Sistem Penyimpan Energi Hibrida Baterai-Ultracapacitor Pada Mobil Listrik Menggunakan Metode Neural Network. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
![[thumbnail of Buku Tugas Akhir_Muhammad Haikal_07111740000138.pdf]](http://repository.its.ac.id/style/images/fileicons/text.png) |
Text
Buku Tugas Akhir_Muhammad Haikal_07111740000138.pdf - Accepted Version Restricted to Repository staff only until 1 October 2023. Download (2MB) | Request a copy |
Abstract
Mobil listrik merupakan teknologi masa depan yang sekarang berkembang secara sangat pesat. Salah satu bagian dari mobil listrik adalah sistem penyimpan energi. Sistem penyimpan energi berfungsi sebagai sumber energi yang menggerakkan mobil listrik. Pada umumnya sistem penyimpan energi menggunakan baterai karena kapasitasnya yang besar. Namun, baterai juga memliki kelemahan. Baterai tidak mampu dengan efisien untuk mengatasi kebutuhan daya maksimum yang tinggi dalam periode singkat dan tidak mampu menyerap secara efisien energi yang ada pada proses regenerative braking. Salah satu cara mengatasi hal ini adalah dengan mengkomplemen baterai menggunakan ultracapacitor. Ultracapacitor cocok digunakan karena memiliki karakteristik yang bertolak belakang dengan baterai dan dapat mengatasi kebutuhan daya maksimum yang tinggi. Kedua tipe media penyimpan ini disatukan penggunaanya pada mobil listrik sehingga didapat sistem penyimpan energi hibrida. Kemudian agar sistem penyimpan energi hibrida bekerja dengan optimal dibutuhkan strategi kontrol. Strategi kontrol bertujuan mengatur aliran daya dari komponen-komponen mobil listrik. Dengan menggunakan neural network bisa didapatkan strategi aliran daya yang lebih teroptimasi. Salah satu aliran daya yang dapat dioptimasi adalah aliran daya dari baterai ke ultracapacitor atau daya trickle charging. Dengan menggunakan sistem penyimpan energi hibrida baterai-ultracapacitor serta menerapkan strategi pengaturan aliran daya berbasis neural network dapat dilakukan penghematan energi pada baterai.
================================================================================================
Electric car is a future technology that is rapidly improving. One of the
important parts of an electric car is the energy storage system. The energy
storage system function is to provide the energy that moves the electric
car. Usually, battery is use as the energy storage system because of its
large capacity. Even so battery also has its share of weakness. Battery
cannot efficiently handle high amount of power needed at a short period
of time and battery cannot efficiently absorb the energy produce during
the regenerative braking processes. One way to handle this weakness is
by complementing battery with ultracapacitor. Ultracapacitor is suitable
to be use because it has the opposite characteristic of battery, and it can
handle high power. By combining both storage systems in an electric car
we will get a hybrid energy storage system. We will also need an optimal
control strategi so that the hybrid energy storage system will work
optimally. Control strategi is used to control the power flow between the
various components in an electric car. One of the power flows that can be
optimized is the power flow from battery to ultracapacitor or power trickle
charging. By using a hybrid energy storage system battery-ultracapacitor
and by implementing a power flow strategy using neural network
improved the efficiency of the battery energy.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | Baterai, Ultracapacitor, Neural Network, Sistem Penyimpan Energi Hibrida, Optimasi, Mobil Listrik |
| Subjects: | A General Works > AI Indexes (General) A General Works > AI Indexes (General) T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL152.5 Motor vehicles Driving 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: | Muhammad Haikal |
| Date Deposited: | 18 Aug 2021 16:21 |
| Last Modified: | 18 Aug 2021 16:21 |
| URI: | http://repository.its.ac.id/id/eprint/87398 |
Actions (login required)
 |
View Item |