Cyber-Physical Co-Design Reliability Framework for ASIL-D Automotive Sensor ECUs with Integrated Hardware–Software Fault Tolerance and Security

The extended complexity of the electronics control units (ECUs) of autonomous and electric cars makes it necessary to implement fault-tolerant designs that comply with the ISO26262ASIL-D. The paper will discuss how hardware-software co-design is used in guaranteeing the safety and reliability of automotive sensor ECUs. The systematic review of 21 articles published between 2021 and 2025 lists integrated strategies related to redundancy, virtualisation, artificial intelligence, and cybersecurity to attain the fail-operational resilience. In the research, the co-designed systems have been shown to have a 90 per cent diagnostic coverage, less than 5 ms recovery latency, and 95 per cent fault detection performance, which is much better than the traditional modular design. Hardware redundancy ensures physical resilience, and adaptive software enables the tasks and proactive fault recovery to be transmitted without difficulties. Moreover, there are cybersecurity features, including voltage-based ECU fingerprinting and root-of-trust verification, to improve the reliability of communications. This paper suggests the Co-Design Reliability Enhancement Framework (CREF) that has the capability of guaranteeing compliance with ASIL-D through the incorporation of redundancy, artificial intelligence, and fault prediction, as well as pipeline testing. The framework illustrates that cybersecurity and functional safety will need to go together, and the ideas of co-design underlie the design of the next-generation, software-defined, fault-tolerant vehicles.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-01
DOI
https://doi.org/10.5281/zenodo.18377649
Primary Topic
Safety Systems Engineering in Autonomy
Type
article
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article

Cyber-Physical Co-Design Reliability Framework for ASIL-D Automotive Sensor ECUs with Integrated Hardware–Software Fault Tolerance and Security

M.A. Quraishi
Zenodo (CERN European Organization for Nuclear Research)
Safety Systems Engineering in Autonomy
article

Cyber-Physical Co-Design Reliability Framework for ASIL-D Automotive Sensor ECUs with Integrated Hardware–Software Fault Tolerance and Security

M.A. Quraishi
article en

Abstract

The extended complexity of the electronics control units (ECUs) of autonomous and electric cars makes it necessary to implement fault-tolerant designs that comply with the ISO26262ASIL-D. The paper will discuss how hardware-software co-design is used in guaranteeing the safety and reliability of automotive sensor ECUs. The systematic review of 21 articles published between 2021 and 2025 lists integrated strategies related to redundancy, virtualisation, artificial intelligence, and cybersecurity to attain the fail-operational resilience. In the research, the co-designed systems have been shown to have a 90 per cent diagnostic coverage, less than 5 ms recovery latency, and 95 per cent fault detection performance, which is much better than the traditional modular design. Hardware redundancy ensures physical resilience, and adaptive software enables the tasks and proactive fault recovery to be transmitted without difficulties. Moreover, there are cybersecurity features, including voltage-based ECU fingerprinting and root-of-trust verification, to improve the reliability of communications. This paper suggests the Co-Design Reliability Enhancement Framework (CREF) that has the capability of guaranteeing compliance with ASIL-D through the incorporation of redundancy, artificial intelligence, and fault prediction, as well as pipeline testing. The framework illustrates that cybersecurity and functional safety will need to go together, and the ideas of co-design underlie the design of the next-generation, software-defined, fault-tolerant vehicles.

Zenodo (CERN European Organization for Nuclear Research)
Dawson College (CA), Walsh College (US)
Openalex Percentile: Top 31%
Safety Systems Engineering in Autonomy
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