Implementasi Fuzzy Inference System untuk Pengstabilan Arus pada Baterai Lithium di Electric Vehicle

Arizal Mujibtamala Nanda Imron(1*), Satryo Budi Utomo(2), Dimas Aldy Darmawan(3), Bambang Sri Kaloko(4), Zilvanhisna Emka Fitri(5)

(1) Universitas Jember
(2) Universitas Jember
(3) Universitas Jember
(4) Universitas Jember
(5) Politeknik Negeri Jember
(*) Corresponding Author

Abstract


The application of renewable energy in electric vehicles (EVs) is a crucial aspect that requires careful consideration. It is essential to understand the capacity characteristics of lithium polymer batteries to develop effective testing procedures. These procedures should involve monitoring the battery's voltage, current, and temperature during the discharge process with a lamp loading of 5 watts. The results of research prove that fuzzy control is an effective method for minimising the increase in battery temperature by stabilising the current used by the battery. The fuzzy control system effectively regulated a battery with a capacity of 3300 mAh and a voltage of 11.1 Volts, maintaining a stable current of 0.3 A from the 3rd minute until the battery reached its maximum capacity at the 63rd minute. Furthermore, the implementation of fuzzy control has been observed to delay the temperature rise in the battery. Specifically, the use of fuzzy control enables a delay in the temperature rise time by approximately 14 minutes when compared to the system without control. The temperature rise has a significant impact on the discharge speed of lithium polymer batteries.

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References


Y. E. Wibowo and J. Windarta, Kondisi Gas Bumi Indonesia dan Energi Alternatif Pengganti Gas Bumi, J. En. Baru & Terbarukan, vol. 3, no. 1, pp. 114, Mar. 2022, doi: 10.14710/jebt.2022.10042.

M. A. Hakim, E. Heriana, M. A. Hakim, and S. Sukmara, Perancangan Kendaraan Kampus dengan Penggerak Motor Listrik, TECHNOMA, vol. 1, no. 2, 2022.

J. Xing, B. Leard, and S. Li, What does an electric vehicle replace?, Journal of Environmental Economics and Management, vol. 107, p. 102432, May 2021, doi: 10.1016/j.jeem.2021.102432.

T. P. Cahyono, T. Hardianto, and B. S. Kaloko, PENGUJIAN KARAKTERISTIK BATERAI LITHIUM-ION DENGAN METODE FUZZY DENGAN BEBAN BERVARIASI, JAEI, vol. 6, no. 3, p. 82, Dec. 2020, doi: 10.19184/jaei.v6i3.19708.

M. Adaikkappan and N. Sathiyamoorthy, Modeling, state of charge estimation, and charging of lithium?ion battery in electric vehicle: A review, Intl J of Energy Research, vol. 46, no. 3, pp. 21412165, Mar. 2022, doi: 10.1002/er.7339.

W. Chen, J. Liang, Z. Yang, and G. Li, A Review of Lithium-Ion Battery for Electric Vehicle Applications and Beyond, Energy Procedia, vol. 158, pp. 43634368, Feb. 2019, doi: 10.1016/j.egypro.2019.01.783.

U. Nursusanto, K. Khairunnisa, and H. Hartoyo, Real Time Battery Monitoring Control in Mini Generating System, JEE, vol. 6, no. 2, pp. 96104, Nov. 2022, doi: 10.21831/jee.v6i2.54299.

J. A. Sanguesa, V. Torres-Sanz, P. Garrido, F. J. Martinez, and J. M. Marquez-Barja, A Review on Electric Vehicles: Technologies and Challenges, Smart Cities, vol. 4, no. 1, pp. 372404, Mar. 2021, doi: 10.3390/smartcities4010022.

D. Harjono, W. Widodo, H. Sugiarto, and A. Bakar, Analisis Kapasitas Dan Pengisian Baterai Pada Mobil Listrik Ponecar, ELIT, vol. 3, no. 1, pp. 110, Apr. 2022, doi: 10.31573/elit.v3i1.378.

D. D. Suranto, S. Anwar, M. Nuruddin, A. Rofii, and A. T. Zain, Analisa Perancangan dan Pengujian Kendaraan Listrik Roda Dua dengan Variasi Pembebanan, j-proteksion. j. kaji. ilm. dan. teknologi. teknik. mesin., vol. 7, no. 2, pp. 4753, Feb. 2023, doi: 10.32528/jp.v7i2.8927.

A. Y. B. Dawe, Electricity Monitoring System based on Fuzzy Logic and Internet of things, IOTA, vol. 1, no. 2, pp. 6380, May 2021, doi: 10.31763/iota.v1i2.459.

R. Septiani and I. G. Waluyo, RANCANG BANGUN SISTEM DETEKSI TITIK KEBAKARAN DENGAN METODE FUZZY LOGIC BERBASIS IOT PADA MTS AL-DZIKRI, OKTAL : Jurnal Ilmu Komputer Dan Sains, vol. 2, no. 2, pp. 450459, 2023.

K. W. Aji, A. G. Putrada, S. Prabowo, and M. A. Saputra, Water Discharge and River Depth Measurement Using Fuzzy Logic Based on Internet of Things, RESTI, vol. 4, no. 3, pp. 384391, Jun. 2020, doi: 10.29207/resti.v4i3.1785.

A. Rianto and J. Kusanti, Identifikasi Kerusakan Dini Otomatis Komponen Elektronika Berbasis Arus Dengan Mikrokontrol Arduino Uno, Jurnal FORTECH, vol. 4, no. 2, pp. 3339, Dec. 2023, doi: 10.56795/fortech.v4i2.4206.

V. Gupta, M. Sharma, R. K. Pachauri, and K. N. D. Babu, A Low-Cost Real-Time IOT Enabled Data Acquisition System for Monitoring of PV System, Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, vol. 43, no. 20, pp. 25292543, Oct. 2021, doi: 10.1080/15567036.2020.1844351.




DOI: http://dx.doi.org/10.30998/faktorexacta.v18i3.26372

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