Simulation-based sensitivity and worst-case analyses of automotive electronics

Abstract

Abstract-Simulation-based verification of electronic control units must face demands related to more functionality and less time to verify it. To ensure a reliable system, one must determine how the omnipresent, internal and external variations affect the target response, and find safe bounds for it. The main challenge is to optimally characterize a high number of sources of variation, with a reduced number of simulation runs. The paper conducts more efficient sensitivity and worst-case studies by applying concepts of Design of Experiments: screening to reduce the dimension of the verification space; sequential experiments for sensitivity analysis; gradient-based search for response bounds. The approach is evaluated on simulations of an airbag driver IC and compared with alternative methods.

Verification and validation of AMS systems: Towards coverage of uncertainties

“…A systematic approach to efficiently find corner cases is the use of Design of Experiments (DoE), e.g. in [25]. In this approach, statistical methods are used to analyze the existing simulation runs, and to determine inputs that likely are candidates for worst case parameters.…”

“…However, this has two problems: First, for n uncertainties it requires Therefore, a number of approaches has been investigated to overcome these issues, e.g. [25]- [28]. A systematic approach to efficiently find corner cases is the use of Design of Experiments (DoE), e.g.…”

Experimental Evaluation of Circuit Board Components Under Extreme Conditions

“…Nassif [20] showed an approach towards WCA, which leads to more realistic estimates of the electronic device and circuit performance changes. Rafaila et al [21] discussed experiment design concepts, and screening tests aimed at reducing the verification space size, whereas Maly et al [22] and Nassif et al [23] suggested a methodology for modelling random process fluctuations, together with its advantages and applications.…”