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AI Safety Assurance in Electric Vehicles: A Case Study onAI-Driven SOC Estimation
RISE Research Institutes of Sweden, Säkerhet och transport, Elektrifiering och pålitlighet.ORCID-id: 0000-0001-6901-4986
RISE Research Institutes of Sweden, Säkerhet och transport, Elektrifiering och pålitlighet.ORCID-id: 0000-0003-4069-6252
RISE Research Institutes of Sweden, Säkerhet och transport, Elektrifiering och pålitlighet.ORCID-id: 0009-0003-0563-079X
RISE Research Institutes of Sweden, Säkerhet och transport, Elektrifiering och pålitlighet.ORCID-id: 0000-0001-7933-3729
Vise andre og tillknytning
2025 (engelsk)Inngår i: EVS 38 - Proceedings / [ed] EVS, 2025Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

sted, utgiver, år, opplag, sider
2025.
Emneord [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
HSV kategori
Identifikatorer
URN: urn:nbn:se:ri:diva-78774OAI: oai:DiVA.org:ri-78774DiVA, id: diva2:1994821
Konferanse
The 38th International Electric Vehicle Symposium & Exposition
Prosjekter
SUNRISE 101069573RELIANT 20220130
Forskningsfinansiär
EU, Horizon Europe, 101069573Tilgjengelig fra: 2025-09-03 Laget: 2025-09-03 Sist oppdatert: 2025-09-23bibliografisk kontrollert

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Skoglund, MartinWarg, FredrikMirzai, AriaThorsén, AndersFolkesson, Peter

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