THE ROLE OF THE INTERNET OF THINGS (IOT) IN ELECTRIC VEHICLE MANAGEMENT AND MAINTENANCE
DOI:
https://doi.org/10.33480/jitk.v10i4.6298Keywords:
battery, electric vehicle, internet of things, machine learningAbstract
The growing adoption of electric vehicles (EVs) as an eco-friendly alternative to fossil fuel-based vehicles necessitates more advanced management and maintenance systems. The Internet of Things (IoT) presents significant potential to enhance EV management by enabling real-time monitoring and data analysis through interconnected sensors and technologies. This research investigates the integration of IoT in electric vehicle systems, focusing on real-time battery health monitoring, early detection of technical issues, and route optimization for improved energy efficiency. The study employs a system design and testing approach, supported by descriptive-analytical analysis using data from case studies, literature reviews, surveys, and interviews. Findings indicate that IoT implementation in EVs yields notable advantages. Real-time battery health tracking provides accurate performance insights, achieving a 92% accuracy rate in predicting battery degradation. Technical problem detection through sensor analysis enables timely maintenance, leading to a 30% reduction in vehicle downtime. Furthermore, IoT-based route optimization improves energy efficiency, reducing energy consumption by 15% and extending battery lifespan by 20% compared to traditional systems. These results underscore the practical benefits of IoT in enhancing EV performance and operational efficiency. The system enables users and service providers to make informed decisions regarding vehicle maintenance and usage, promoting better understanding of battery conditions. Ultimately, the application of IoT technology contributes to extending battery life, minimizing vehicle downtime, and supporting broader efforts in energy efficiency and carbon emission reduction
Downloads
References
International Energy Agency (IEA), “Global EV Outlook 2022”, 2022, Available online: https://www.iea.org/reports/global-ev-outlook-2022. (Accessed on 28 June 2024).
N. V. Emodi, U. B. Akuru, M. O. Dioha, P. Adoba, R. J. Kuhudzai, & O. Bamisile, “The Role of Internet of Things on Electric Vehicle Charging Infrastructure and Consumer Experience”, Energies, vol. 16, 4248 2023.
Mera, Z., & Bieker, G. (2023). Comparison of the life-cycle greenhouse gas emissions of combustion engine and electric passenger cars and two-wheelers in Indonesia. The International Council on Clean Transportation.
Ou, S., Lin, Z., He, X., Przesmitzki, S., & Bouchard, J. (2020). Modeling charging infrastructure impact on the electric vehicle market in China. Transportation Research Part D: Transport and Environment, 81, 102248.
Hasan, M. R., & Mustafi, N. N. (2022). Environmental impacts of the use of electric vehicles. Environmental Claims Journal, 34(1), 56-79.
T. T. Salsabila and H. F. Ramadhan, “EM-IOT: Sistem Monitoring Baterai dan Location Tracking Berbasis IoT pada Motor Listrik”, Thesis: Universitas Islam Indonesia, 2022.
F. N. Zain, M. E. Martawati, and F. Rohman, “Pengembangan Sistem Monitoring Kapasitas Baterai Kendaraan Listrik Berbasis Internet of Things”, Jurnal Aplikasi Dan Inovasi Ipteks SOLIDITAS, vol. 6, pp. 92-97, 2023.
Khalid, M., Ahmad, F., Panigrahi, B. K., & Al-Fagih, L. (2022). A comprehensive review on advanced charging topologies and methodologies for electric vehicle battery. Journal of Energy Storage, 53, 105084.
Zhang, Z., Dong, H., Wang, L., Wang, Y., & He, X. (2024). Tracing Root Causes of Electric Vehicle Fires. Energy Technology, 12(12), 2400931.
M. Harizaj and I. Bisha, “Integration in Internet of Things of Electric Vehicle Charging Infrastructure”, Engineering Applications, vol. 2, pp. 136-145, 2023.
H. Herdiayansyah, “Inovasi Terkini dalam Teknik Elektro: Dari IoT hingga Kendaraan Listrik”, Repoteknologi, vol. 2, 2022.
K. S. S. Liyakat, “IoT in Electrical Vehicle: A Study”, Journal of Control and Instrumentation Engineering, vol. 2, pp. 15-21, 2023.
M. Z. Bisri & I. Anzhory, “Alat Monitoring Getaran Motor Listrik Induksi 1 Phase Berbasis Internet of Think (IoT)”, Innovative Technologica: Methodical Research Journal, vol. 3, 2024.
G. F. Savari, V. Krishnasamy, J. Sathik, Z. M. Ali, and S. H. A. Aleem, “Internet of Things Based Real-Time Electric Vehicle Load Forecasting and Charging Station Recommendation”, ISA Transactions, vol. 97, pp. 431-447, 2022.
M. A. F. Arkaan & F. Utaminingrum, “Sistem Deteksi Permukaan Jalan pada Kursi Roda Pintar dengan Metode MobileNetV2”, Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, vol. 7, pp. 608-612, 2023.
Von Rueden, L., Mayer, S., Beckh, K., Georgiev, B., Giesselbach, S., Heese, R., ... & Schuecker, J. (2021). Informed machine learning–a taxonomy and survey of integrating prior knowledge into learning systems. IEEE Transactions on Knowledge and Data Engineering, 35(1), 614-633.
Taherdoost, H. (2021). Data collection methods and tools for research; a step-by-step guide to choose data collection technique for academic and business research projects. International Journal of Academic Research in Management (IJARM), 10(1), 10-38.
K. Eshankulov, G. Turdiyeva, M. Ismoilova, G. Murodova, & R. Murodova, “Algorithm for the Integration of Software Modules Based on the Ontological Approach”, Information Technologies and Intelligent Decision Making Systems, 2021.
H. A. Goh, C. K. Ho, & F. S. Abas. “Front-end Deep Learning Web Apps Development and Deployment: A Review”, Applied Intelligence, vol 53, pp. 15923-15945, 2023.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Callista Fabiola Candraningtyas, Fikri Arkan Maulana, Sapta Suhardono
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
-a.jpg)
-b.jpg)
