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AI Safety Assurance in Electric Vehicles: A Case Study onAI-Driven SOC Estimation
RISE Research Institutes of Sweden, Safety and Transport, Electrification and Reliability.ORCID iD: 0000-0001-6901-4986
RISE Research Institutes of Sweden, Safety and Transport, Electrification and Reliability.ORCID iD: 0000-0003-4069-6252
RISE Research Institutes of Sweden, Safety and Transport, Electrification and Reliability.ORCID iD: 0009-0003-0563-079X
RISE Research Institutes of Sweden, Safety and Transport, Electrification and Reliability.ORCID iD: 0000-0001-7933-3729
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2025 (English)In: EVS 38 - Proceedings / [ed] EVS, 2025Conference paper, Published paper (Refereed)
Abstract [en]

Integrating Artificial Intelligence (AI) technology in electric vehicles (EV) introduces unique challenges for safety assurance, particularly within the framework of ISO 26262, which governs functional safety in the automotive domain. Traditional assessment methodologies are not geared toward evaluating AI-based functions and require evolving standards and practices. This paper explores how an independent assessment of an AI component in an EV can be achieved when combining ISO 26262 with the recently released ISO/PAS 8800, whose scope is AI safety for road vehicles. The AI-driven State of Charge (SOC) battery estimation exemplifies the process. Key features relevant to the independent assessment of this extended evaluation approach are identified. As part of the evaluation, robustness testing of the AI component is conducted using fault injection experiments, wherein perturbed sensor inputs are systematically introduced to assess the component's resilience to input variance.

Place, publisher, year, edition, pages
2025.
Keywords [en]
Artificial Intelligence, AI, electric vehicles, EV, safety assurance, ISO 26262, functional safety, independent assessment, AI safety, road vehicles, State of Charge, SOC, battery estimation, robustness testing, fault injection
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:ri:diva-78774OAI: oai:DiVA.org:ri-78774DiVA, id: diva2:1994821
Conference
The 38th International Electric Vehicle Symposium & Exposition
Projects
SUNRISE 101069573RELIANT 20220130
Funder
EU, Horizon Europe, 101069573Available from: 2025-09-03 Created: 2025-09-03 Last updated: 2025-09-23Bibliographically approved

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fulltext(1129 kB)138 downloads
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Skoglund, MartinWarg, FredrikMirzai, AriaThorsén, AndersFolkesson, Peter

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