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A Systematic Literature Review of Risk Assessment Methodologies for Battery Electric Vehicles

Automotive Experiences · Vol. 8 No. 1 (2025) · hlm. 46–71

DOI
10.31603/ae.12835
ISSN
2615-6636, 2615-6202
Terbit
2025-03-09
Penerbit
Universitas Muhammadiyah Magelang
Bahasa
en

Abstrak

This systematic literature review investigates risk assessment methodologies for Battery Electric Vehicles (BEVs), highlighting their diversity and effectiveness in addressing emerging safety challenges. With the rapid global adoption of BEVs, there is an increasing need for robust methodologies to assess risks such as thermal runaway (TR), degradation, and operational failures. This review highlights techniques such as fuzzy failure mode and effect analysis (FMEA), hybrid neural networks, bayesian networks (BN), and entropy weight methods. These tools effectively identify and mitigate risks; however, they face challenges in providing holistic, system-level safety assessments and adapting to long-term, real-world conditions. Unlike previous works, this study integrates interdependent BEV subsystems into unified risk models and examines underexplored areas such as maritime transport safety. The transport of BEVs by vessels presents unique risks, including high humidity and confined cargo spaces, which intensify the battery safety challenges. Tools like FMEA and real-time monitoring systems are critical to mitigate these risks. The findings highlight the growing reliance on real-time diagnostics and advanced algorithms for enhancing BEV safety and reliability. By identifying gaps and proposing recommendations, this review aims to support the development of standardized frameworks to ensure BEV safety across various environments and operational scenarios, contributing to their continued global adoption.

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Subaryata SubaryataAfiliasi tidak diketahui8
Mutharuddin MutharuddinAfiliasi tidak diketahui4
Novi IrawatiAfiliasi tidak diketahui4
Indra KurniawanAkademi Komunitas Perkebunan Yogyakarta4
Siti Hidayanti Mutia KurniaAfiliasi tidak diketahui4
Prastya Rizky RamadhanAfiliasi tidak diketahui4
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Tris HandoyoAfiliasi tidak diketahui4
Alexander Christantho BudimanAfiliasi tidak diketahui2
Nurul Aldha Mauliddina SiregarAfiliasi tidak diketahui2
Irfan AnsoriAfiliasi tidak diketahui2
Tetty Sulastri MardianaAfiliasi tidak diketahui2
Djoko Wahyu KarmiadjiBadan Pengkajian dan Penerapan Teknologi2
M. RosyidiAfiliasi tidak diketahui2
Hastiya Annisa FitriAfiliasi tidak diketahui2
Tetty Sulastry MardianaAfiliasi tidak diketahui2
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Yudan WhulanzaAfiliasi tidak diketahui1
Abdul HapidBadan Pengkajian dan Penerapan Teknologi1
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Sumber metadata: OAI-PMH (metadata jurnal) http://journal.unimma.ac.id/index.php/AutomotiveExperiences/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en">A Systematic Literature Review of Risk Assessment Methodologies for Battery Electric Vehicles</dc:title>
	<dc:creator xml:lang="en">Gusti, Ayudhia Pangestu</dc:creator>
	<dc:creator xml:lang="en">Waskito, Dwitya Harits</dc:creator>
	<dc:creator xml:lang="en">Kaleg, Sunarto</dc:creator>
	<dc:creator xml:lang="en">Bowo, Ludfi Pratiwi</dc:creator>
	<dc:creator xml:lang="en">Pratama, Angjuang</dc:creator>
	<dc:creator xml:lang="en">Maulani, Defi Rizki</dc:creator>
	<dc:creator xml:lang="en">Varadita, Ayumi Putri</dc:creator>
	<dc:creator xml:lang="en">Nugroho, Sinung</dc:creator>
	<dc:creator xml:lang="en">Wiguna, I Kadek Candra Parmana</dc:creator>
	<dc:subject xml:lang="en">Battery Electric Vehicles</dc:subject>
	<dc:subject xml:lang="en">Electric Vehicles</dc:subject>
	<dc:subject xml:lang="en">Risk Assessment</dc:subject>
	<dc:subject xml:lang="en">Risk Analysis</dc:subject>
	<dc:subject xml:lang="en">Safety Protocols</dc:subject>
	<dc:description xml:lang="en">This systematic literature review investigates risk assessment methodologies for Battery Electric Vehicles (BEVs), highlighting their diversity and effectiveness in addressing emerging safety challenges. With the rapid global adoption of BEVs, there is an increasing need for robust methodologies to assess risks such as thermal runaway (TR), degradation, and operational failures. This review highlights techniques such as fuzzy failure mode and effect analysis (FMEA), hybrid neural networks, bayesian networks (BN), and entropy weight methods. These tools effectively identify and mitigate risks; however, they face challenges in providing holistic, system-level safety assessments and adapting to long-term, real-world conditions. Unlike previous works, this study integrates interdependent BEV subsystems into unified risk models and examines underexplored areas such as maritime transport safety. The transport of BEVs by vessels presents unique risks, including high humidity and confined cargo spaces, which intensify the battery safety challenges. Tools like FMEA and real-time monitoring systems are critical to mitigate these risks. The findings highlight the growing reliance on real-time diagnostics and advanced algorithms for enhancing BEV safety and reliability. By identifying gaps and proposing recommendations, this review aims to support the development of standardized frameworks to ensure BEV safety across various environments and operational scenarios, contributing to their continued global adoption.</dc:description>
	<dc:publisher xml:lang="en">Universitas Muhammadiyah Magelang</dc:publisher>
	<dc:date>2025-03-09</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unimma.ac.id/AutomotiveExperiences/article/view/12835</dc:identifier>
	<dc:identifier>10.31603/ae.12835</dc:identifier>
	<dc:source xml:lang="en">Automotive Experiences; Vol. 8 No. 1 (2025); 46-71</dc:source>
	<dc:source>2615-6636</dc:source>
	<dc:source>2615-6202</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unimma.ac.id/AutomotiveExperiences/article/view/12835/5713</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2025 Ayudhia Pangestu Gusti, Dwitya Harits Waskito, Ludfi Pratiwi Bowo</dc:rights>
</oai_dc:dc>