Demonstrates enhanced hazard analysis in electric vehicles, suggesting improved safety evaluations.
With the increasing complexity of electrical and electronic (E/E) components in modern powertrains, functional safety requires more systematic assessment methods. This paper presents a simulation-based approach for automated Hazard Analysis and Risk Assessment (HARA) of battery electric vehicles in accordance with ISO 26262. The method combines operational-situation parameters, including vehicle speed, road surface, vehicle gap, and road inclination, to define a structured set of hazardous events. Severity, Exposure, and Controllability are evaluated using rule-based criteria, including a dedicated Controllability rule set for longitudinal motion hazards. Quantitative erroneous acceleration and deceleration thresholds associated with different ASILs are derived using a bisection search algorithm, enabling quantifiable and testable safety goals. Comparison with manual HARA reveals systematic biases: low speed does not necessarily imply improved Controllability due to shorter vehicle gaps, while Severity may be underestimated at low speeds because of high instantaneous electric-machine torque. The maximum ASIL is often identified similarly by simulation and experts, whereas lower-ASIL hazardous events may lack consistency and coverage in manual HARA. As a practical application, the approach can be integrated into existing automotive safety workflows as a HARA support tool, improving the consistency of lower-ASIL events while allowing engineers to focus on maximum ASIL cases.
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Morozov et al. (2026) studied this question.
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