LS-SA: Developing an FMI layered standard for holistic & efficient sensitivity analysis of FMUs

Authors

  • Tobias Thummerer University of Augsburg
  • Hans Olsson Dassault Systemes AB
  • Chen Song ABB Corporate Research Center
  • Julia Gundermann ESI Germany GmbH
  • Torsten Blochwitz ESI Germany GmbH
  • Lars Mikelsons University of Augsburg

DOI:

https://doi.org/10.3384/ecp218681

Keywords:

Functional Mock-up Unit, Functional Mock-up Interface, Discontinuous, Events, Machine Learning, Scientific Machine Learning, Neural FMU, Layered Standard

Abstract

The Functional Mock-up Interface (FMI) is the standard forexchanging industrial simulation models in a variety ofdifferent applications. Although sensitivity analysis forcontinuously differentiable systems is directly supportedby the standard, for systems with state discontinuities, itis only possible to determine correct sensitivities to alimited extent. In this position paper, we investigate howsensitivity analysis for discontinuous Functional Mock-upUnits (FMUs), i.e. including state and time events, worksin theory and which additional steps are required to obtaincorrect results in practice. We further investigate thatthese steps are unnecessarily computationally intensivefrom a mathematical point of view, but cannot beimplemented in a more efficient way under the currentrestrictions of the standard. We therefore make a concreteproposal for the new layered standard sensitivity analysis(LS-SA) that remedies the current deficits of FMI in thesensitivity analysis of discontinuous systems. In this way,LS-SA opensFMI towards a variety of next-level applications —including (scientific) machine learning and optimal control— by providing fully differentiable FMUs under highcomputational performance.

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Published

2025-10-24