Automated Dynamic Safety Evaluation of Generic Fail-Operational Mechatronic Systems

The increasing complexity of connected and distributed mechatronic systems developed for safety-critical applications, as e.g. a powertrain of automated vehicles, makes their dependability evaluation a challenging task. Moreover, precise statements about the dependability metrics are of high interest for architectural decisions in the early stages of the design process. System dynamics, possible fault combinations as well as the sequence, duration and impact of various faults and the associated system states must be considered for a realistic evaluation and quantification of the failure behavior. In order to optimize the design of generic mechatronic systems at different abstraction levels and with different component characteristics, this paper examines a method to analytically quantify the stochastic behavior of a system. The proposed approach enables to significantly increase the computational efficiency of the safety analysis of generic fail-operational mechatronic systems without loss in accuracy by automating the dynamic evaluation of convolutional integrals. The application of the proposed safety analysis is demonstrated using an exemplary system with dynamic redundancy.