Suhada, Sultan (2025) PENGOPTIMALAN ESTIMASI STATE OF CHARGE PADA BATERAI KENDARAAN LISTRIK MENGGUNAKAN KONSUMSI DAYA BERDASARKAN METODE EQUIVALENT CIRCUIT MODEL DAN GREY WOLF OPTIMIZER. S2 thesis, Universitas Mercu Buana Jakarta - Menteng.
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Abstract
Peningkatan kinerja Sistem Manajemen Baterai (Battery Management System/BMS) dalam menentukan State of Charge (SoC) sangat penting untuk mencegah over charging dan over discharging. Oleh karena itu, penelitian ini bertujuan untuk mengoptimalkan sistem manajemen baterai pada bagian State of Charge saat baterai dipengaruhi oleh berbagai faktor, seperti umur baterai yang sudah lama atau gangguan eksternal pada rangkaian output. Penelitian ini membahas penurunan kapasitas baterai berdasarkan konsumsi daya per detik menggunakan metode Equivalent Circuit Model (ECM) serta optimasi dengan algoritma Grey Wolf Optimizer (GWO) selama 600 detik dan 3600 detik. Tiga model dibandingkan: SoC aktual, estimasi SoC metode ECM, dan estimasi SoC metode ECM dan GWO. Pada durasi 600 detik, ECM memberikan error 0,08% dengan akurasi 93,36% terhadap SoC aktual. Setelah optimasi menggunakan GWO, error turun menjadi 0% dengan akurasi 100%. Pada durasi 3600 detik, ECM menunjukkan error 1,15% dan akurasi 63,77%, sementara GWO menurunkan error menjadi 0,04% dengan akurasi 99,95%. Melalui kombinasi ECM sebagai metode monitoring dan GWO sebagai metode optimasi adaptif, sistem manajemen baterai mampu mempertahankan akurasi estimasi SoC meskipun terjadi penyimpangan akibat faktor massa pemakaian. Penelitian ini berhasil menggambarkan kondisi baterai yang menyimpang dari kondisi aktual, namun dapat dikembalikan ke kondisi optimal dengan optimasi yang lebih unggul dibandingkan penelitian sebelumnya. Improving the performance of the Battery Management System (BMS) in determining the State of Charge (SOC) is very important to prevent over charging and over discharged. Therefore, this study aims to optimize the battery management system in the State of Charge section when the battery is influenced by various factors, such as a long battery life or external disorders in the output circuit. This study discusses a decrease in battery capacity based on power consumption per second using the Equivalent Circuit Model (ECM) method as well as optimization with the Gray Wolf Optimizer (GWO) algorithm for 600 seconds and 3600 seconds. Three models compared to: actual SOC, ECM SOC estimation, and ECM and GWO SOC estimates. In the duration of 600 seconds, ECM gave an error of 0.08% with an accuracy of 93.36% to the actual SOC. After optimization using GWO, the error dropped to 0% with 100% accuracy. In the duration of 3600 seconds, ECM showed an error of 1.15% and accuracy 63.77%, while GWO decreased error to 0.04% with an accuracy of 99.95%. Through the combination of ECM as a method of monitoring and GWO as a method of adaptive optimization, the battery management system is able to maintain the accuracy of the SOC estimation despite deviations due to mass of use. This study succeeded in describing the condition of the battery that deviated from the actual condition, but can be returned to optimal conditions with superior optimization compared to previous research..
| Item Type: | Thesis (S2) |
|---|---|
| NIM/NIDN Creators: | 55423110004 |
| Uncontrolled Keywords: | Battery Management System, Equivalent Circuit Model, Grey Wolf Optimizer, Kapasitas baterai, State of Charge Battery Capacity, Battery Management System, Equivalent Circuit Model, Gray Wolf Optimizer, State of Charge |
| Subjects: | 600 Technology/Teknologi > 620 Engineering and Applied Operations/Ilmu Teknik dan operasi Terapan > 621 Applied Physics/Fisika terapan |
| Divisions: | Pascasarjana > Magister Teknik Elektro |
| Depositing User: | ARDIFTA DWI AFRIANI |
| Date Deposited: | 02 Aug 2025 03:57 |
| Last Modified: | 02 Aug 2025 03:57 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/96474 |
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