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Markov Chain-based Reliability Analysis for Automotive Fail-Operational Systems

Journal Article
2017-01-0052
ISSN: 2574-0741, e-ISSN: 2574-075X
Published March 28, 2017 by SAE International in United States
Markov Chain-based Reliability Analysis for Automotive
                    Fail-Operational Systems
Sector:
Citation: Kohn, A., Schneider, R., Vilela, A., Dannebaum, U. et al., "Markov Chain-based Reliability Analysis for Automotive Fail-Operational Systems," SAE Intl. J CAV 1(1):41-50, 2018, https://doi.org/10.4271/2017-01-0052.
Language: English

Abstract:

A main challenge when developing next generation architectures for automated driving ECUs is to guarantee reliable functionality. Today’s fail safe systems will not be able to handle electronic failures due to the missing “mechanical” fallback or the intervening driver. This means, fail operational based on redundancy is an essential part for improving the functional safety, especially in safety-related braking and steering systems. The 2-out-of-2 Diagnostic Fail Safe (2oo2DFS) system is a promising approach to realize redundancy with manageable costs. In this contribution, we evaluate the reliability of this concept for a symmetric and an asymmetric Electronic Power Steering (EPS) ECU. For this, we use a Markov chain model as a typical method for analyzing the reliability and Mean Time To Failure (MTTF) in majority redundancy approaches. As a basis, the failure rates of the used components and the microcontroller are considered. The comparison to a non-redundant system shows a significantly higher reliability and MTTF of the redundant approaches.