Implementasi Pengujian Kapasitas Baterai Dengan Sistem Pengambilan Keputusan Klasifikasi Kelulusan Baterai Lithium-ion Menggunakan Metode Fuzzy Logic

Nurazizah, Safira (2023) Implementasi Pengujian Kapasitas Baterai Dengan Sistem Pengambilan Keputusan Klasifikasi Kelulusan Baterai Lithium-ion Menggunakan Metode Fuzzy Logic. Diploma thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Balai Standardisasi dan Pelayanan Jasa Industri (BSPJI) Surabaya melakukan pengujian pada baterai untuk mengeluarkan sertifikat Standar Nasional Indonesia (SNI). Proses pengujian kapasitas baterai lithium-ion pada panduan SNI IEC 61960:2015 tertulis salah satu pengujian pada baterai dilakukan untuk mengetahui kapasitas baterai. Sejauh ini, pengujian kapasitas baterai di BSPJI Surabaya dilakukan secara manual. Pengambilan data secara manual menyebabkan ketidakefektifan pengujian dari segi waktu serta kurangnya ketelitian dan kepresisian pada data hasil pengujian. Setelah pengujian selesai data pengujian di analisa untuk hasil kelulusan. Penelitian ini dibuat untuk mengatasi masalah tersebut dengan membangun ‘Implementasi Pengujian Kapasitas Baterai Dengan Sistem Pengambilan Keputusan Klasifikasi Kelulusan Baterai Lithium-ion Menggunakan Metode Fuzzy Logic’. Prinsip kerja dari sistem yang dibuat melakukan otomatisasi, pengambilan data dan pengambilan keputusan kelulusan dari pengujian kapasitas baterai lithium-ion. Proses pengujian kapasitas baterai menggunakan arduino mega 2560 untuk melakukan cut-off charging dan discharging pada pengujian baterai. Sistem pengambilan keputusan menggunakan metode fuzzy logic. Pemilihan metode fuzzy logic pada penelitian ini dikarenakan fuzzy logic dapat memberikan suatu keputusan akhir dalam melakukan pembentukan himpunan fuzzy untuk input pengujian baterai kondisi 1 (kinerja peluahan 20℃), pengujian baterai kondisi 2 (kinerja peluahan -20℃) dan pengujian baterai kondisi 3 (kinerja peluahan tingkat tinggi 20℃) dengan memberikan penegasan output dari komposisi aturan-aturan yang hasilnya akurat. Hasil penelitian Proyek Akhir ini diketahui bahwa penambahan faktor koreksi pada sensor tegangan dan arus mampu mengurangi nilai error sebesar 0,47% menjadi 0,16% untuk sensor tegangan dan mampu mengurangi nilai error sebesar 3,64% menjadi 0,9% untuk sensor arus. Nilai ketelitian dan kepresisian berdasarkan perhitungan Relative Standard Deviation (RSD) nilai RSD sebesar 1,35% yang berarti baterai memiliki nilai yang presisi. Dan terakhir, penerapan logika fuzzy pada sistem yang telah dibangun dapat memberikan hasil pengambilan keputusan mengenai klasifikasi kelulusan pada pengujian kapasitas baterai lithium-ion.
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The Standardization and Industrial Services Institute of Surabaya conducts testing on batteries to issue the Indonesian National Standard (SNI) certificate. The process of testing the capacity of lithium-ion batteries follows the guidelines of SNI IEC 61960:2015, which includes a test to determine the battery capacity. Currently, the battery capacity testing at SISI Surabaya is done manually. Manual data collection has led to inefficiencies in terms of time and a lack of accuracy and precision in the test results. This research aims to address these issues by developing the 'Implementation of Battery Capacity Testing with Decision-Making System for Classification of Lithium-ion Battery Passing Using Fuzzy Logic Method'. The system operates through automation, data collection, and decision-making for the classification of lithium-ion battery passing based on the battery capacity testing. The battery capacity testing process employs Arduino Mega 2560 to perform cut-off charging and discharging during the tests. The decision-making system utilizes the fuzzy logic method. Fuzzy logic is chosen for this research because it can provide a final decision by forming fuzzy sets for input data from three different battery conditions: condition 1 (performance at 20℃), condition 2 (performance at -20℃), and condition 3 (performance at high discharge rate at 20℃). The fuzzy logic system gives accurate output by asserting rules. The findings of this Final Project research show that the addition of correction factors to voltage and current sensors reduces the error value from 0.47% to 0.16% for the voltage sensor and from 3.64% to 0.9% for the current sensor. The precision and accuracy, calculated based on Relative Standard Deviation (RSD), result in an RSD value of 1.35%, indicating precise battery values. Lastly, the implementation of fuzzy logic in the developed system provides decision-making results for the classification of passing in lithium-ion battery capacity testing.

Item Type:	Thesis (Diploma)
Uncontrolled Keywords:	Decision Making System, Battery Capacity Testing , Fuzzy logic, Charging Discharging, Sistem Pengambilan Keputusan, Pengujian Kapasitas Baterai, Fuzzy logic, Charging Discharging
Subjects:	Q Science > QA Mathematics > QA9.64 Fuzzy logic T Technology > T Technology (General) > T58.62 Decision support systems T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK2861 Electric relays T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK2941 Storage batteries
Divisions:	Faculty of Vocational > 36304-Automation Electronic Engineering
Depositing User:	Safira Nurazizah
Date Deposited:	29 Aug 2023 01:45
Last Modified:	29 Aug 2023 01:45
URI:	http://repository.its.ac.id/id/eprint/103494

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