2025-09-09 –, Forum
We present two technologies for speeding up co-simulations under the FMI standards. By smoothing the input signals inside each FMU, the internal integrator may avoid re-initialization. This can significantly reduce the number of model and Jacobian evaluations. To further help the integrator we also propose a predictor compensation technique tailored to the input smoother. The main benefit of our technologies is the ease-of-use, requiring no model manipulations, nor any special co-simulation master algorithms. The technologies are implemented in Dymola~2025x and validated with both an academic mechanical model as well as thermo-fluid examples where we can observe performance gains with factor up to 100, and often around 5-10. One of these thermo-fluid examples is used in the \emph{OpenSCALING} research project to generate training data for constructing surrogate models, for which the input smoothing is especially important to speed up the dataset creation.
Dymola developer at Dassault Systemes since 2016.
Responsible for the numerical aspects of Modelica model simulations within Dymola.
PhD in Numerical Analysis from Lund University 2016.
Head of Software and Simulation Technologies at TLK-Thermo.
Thermofluid background and 15+ years experience in modeling, simulation and software development.
TILMedia, TIL Suite, DaVE, TLK Simulator, MoBA Automation, TISC.
Technology architecture director, working on Dymola development in a broad sense since 1992. Also active in the SSP design group and in ProSTEP ivip Smart System Engineering. Former member of ISO WG21 C++.
Oliver Lenord earned his Phd at the Mechatronics Institute of the Univ. of Duisburg, Germany. Since 2016 he is affiliated with Robert Bosch - Corporate Research. Formerly he led the simulation software development group at Bosch Rexroth and worked as product manager for Siemens PLM in California, USA. Currently he is leading the European ITEA4 project OpenSCALING (openscaling.org). Earlier he also initiated and led the German research project PHyMoS, concerned with integrating scientific machine learning with classical modeling and led the award winning ITEA3 project EMPHYSIS that delivered the new eFMI standard. He also serves as vice-chairman of the Open Source Modelica Consortium (OSMC).