Markov Chain-based Reliability Analysis for Automotive
Fail-Operational Systems 2017-01-0052
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.