Transient Fault Detection and Failure Effect Analysis Based on Design for Test and Fault Tree Analysis for Automotive Chips
Automotive-grade chips play a crucial role in the development of intelligent networked vehicles, and functional safety is a key issue of automotive-grade chips. Transient faults induced by high-energy particle radiation affect the functional safety of automotive-grade chips significantly and may lead to catastrophic accidents. Currently, research on transient faults and chip functional safety, both domestically and internationally, remains relatively fragmented, with a clear lack of comprehensive functional safety analysis and testing methods for transient faults. Requirements for the analysis of transient faults are included in the ISO 26262 standard on applications to semiconductors. This paper integrates fault probability, circuit structure, and safety objectives into the analysis and testing of transient faults, enabling the accurate identification of vulnerable components solely related to functional safety during the design phase and quantifying their safety impact. During the testing phase, the thesis focuses solely on testing the vulnerable components identified during the design phase and prioritizes test patterns based on the contribution of each test pattern, allowing for the rapid identification of safety vulnerabilities through a limited number of test patterns in the testing phase. The experimental results demonstrate that our proposed method is capable of accurately detecting transient faults associated with safety. By utilizing only 452 screened and optimized test patterns, the test results have attained a coverage rate of 97.16%. This signifies a notable 56.3% enhancement in test efficiency, with a minimal and insignificant loss of just 1.7% in coverage.
Authors
- Zhimin Tang (ORCID: https://orcid.org/0000-0001-5806-9033)
- Huiyun Li (ORCID: https://orcid.org/0000-0003-0157-1393)
- Xin-Hua Luo
- Changcheng SHAO
Institutions
- Shenzhen University (CN)
- Shenzhen Technology University (CN)
Publication Details
- Journal
- IEEE Transactions on Circuits and Systems I Regular Papers
- Published
- 2025-05-28
- DOI
- https://doi.org/10.1109/tcsi.2025.3570877
- Primary Topic
- Industrial Vision Systems and Defect Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Shenzhen Fundamental Research Program