The calibration of models against measurement data is important to ensure

model dynamics that are close to its real-world system. Derivative-free

minimizing methods can be used for any model calibration regardless of

continuous differentiability requirements, and find a (local) minimum in a

reasonable number of iteration steps.

A user-friendly, python-based calibration Dash app to use with the cloud-based

Modelica platform Modelon Impact is introduced. Basic calibration setup is

done through the GUI of the app and graphical feedback (i.e. plots) is provided.

Two example calibrations are shown: A mechanical Furuta pendulum

that only uses Modelica Standard Library components is calibrated against

real-world measurement data, and a low-fidelity heat exchanger testbench

model that uses Modelon's Air Conditioning Library is calibrated against

a corresponding high-fidelity model.

System Structure and Parameterization (SSP) is a tool independent standard to define complete systems. Dymola now supports import and export of SSP files, and this paper describes how SSP support was implemented in Dymola and discusses some of the constraints and unavoidable compromises.

Nowadays, the digitalization of large-scale railway infrastructure systems is a major trend, which helps to reduce

the life-cycle costs of the railway transportation. For

this purpose, the Digital Twin (DT) technology can be

used to interoperate different digital data and models, belonging to the railway infrastructure system, in a virtual

platform for predictive maintenance, diagnostics and condition monitoring in the railway sector. However, the

simulation models of the infrastructure system are tooldependent, lack ease-of-use and platform compatibility.

Therefore, we have to customise them in order to make

them more representative and then integrate easily and

tool-independently into the DT platform. For this purpose, we propose to use the Functional Mock-up Interface

(FMI) and System Structure Parameterization (SSP) technologies as open interface standards between the models

and software tools. In this work, we demonstrate the application of the FMI and SSP standards separately for two

use cases, which include a multibody simulation (MBS)

model of a railway vehicle and residual life time (RLT)

calculation of a steel bridge.

Operating energy grids with a high share of renewable energy sources (RES) requires system reconfiguration as a response to environmental condition changes. To understand them better, simulations are needed and Modelica is an excellent choice for that. Energy grids with event-based reconfigurations are an instance of variable structure systems (VSS). However, the full support of VSS in Modelica is challenging and topic of ongoing research. Petri nets (PNs) offer a formalism for capturing the variability of VSS. The capability to simulate PNs in Modelica gives an opportunity to model VSS. This paper presents an approach to utilize PNs in Modelica for modeling variable structure energy grids. Therefore, we introduce energetic Petri nets, a special type of PNs and an experimental library called PNRG for PN-based energy system modeling is presented. Furthermore, possibilities and limits of modeling energy grids are discussed and an outlook how to develop this technique is provided.

As part of the research project ETA im Bestand, the simulation library ThermalIntegrationLibrary was developed for the identification and evaluation of energy efficiency measures in existing factories. In this paper the package containing the building models is presented (section 2.1). It enables the user to simulate building related efficiency measures independently or combined with machines and technical building equipment. Special focus is placed on the efficiency measure hereafter referred to as enclosure, which designates a thermally activated construction around a number of machines to facilitate the capturing of waste heat emitted to the ambient air. The correct implementation of the enclosure is validated using measurement data obtained from an experiment with a small demonstrator (section 2.2). Furthermore an application example of the package is given, applying a few simple efficiency measures to an exemplary production hall (section 2.3). The respective results are presented in section 3.

Collaborative model-based development of hybrid power system often requires large-scale co-simulation and system parameter optimization. FMI and SSP standards establish model exchange at various levels of abstraction and interoperability between tools. This study examines the architecture of parallel processing SSP and FMI simulation that can perform high-speed computation with multi-core distribution. We combine AI based optimization and co-simulation and builds a collaborative development platform for hybrid power systems design. Performance experiments uses hybrid vehicle simulation model published by JAMBE (MBD promotion center in Japan).

Adjustment systems are used in vehicle headlamps to regulate the flare on the street. The kinematic system within the headlamp is driven automatically based on level sensor signals and can additionally be manually set to a start position. In modern cars the automatic vehicle headlamp levelling is legal duty due to the strong cut-off line (COL) between dark and light. This cut-off can be measured in a workshop but not during operation. Due to the complex kinematics including nonlinear contacts, friction and damping a Modelica model is used to calculate the position of the COL. The results show a characteristic hysteresis of the horizonal position during automatic movement. The simulation results are compared to measurements and show good agreement.

The conceptual design of industrial processes is challenging as relatively little information about the eventually selected equipment and their operation is known in this early design stage. Furthermore, the systems are increasingly integrated with themselves, and their design must be addressed systematically. Simulation can assist in better understanding the effects of design decisions on the resulting system performance. To facilitate the simulation of industrial processes in this early design phase, this paper proposes an approach to modeling system components specifically aimed at employing known key design parameters and assuming steady-state behavior of the process for a certain period of time (e.g. one hour). A solution over a longer period of time (e.g. for a year) can then be obtained by simulating a multitude of such shorter periods, leading to the piecewise-steady-state solution. The proposed approach is developed with an exemplary case study, based on a real industrial site. The resulting model computes the annual load profile within the range of seconds for the given case study.

This paper presents a novel buildings modelling toolkit called ‘Home Energy Dynamics’ (HED) and describes recent improvements to its operation. In this study, HED is used to simulate a domestic dwelling, showing its current energy performance and how it changes when energy efficiency retrofit measures and low carbon technologies are implemented in the dwelling. Changes to energy demand, energy cost, and greenhouse gas emissions are analysed; as the packages of measures increase, energy demand and greenhouse gas emissions decrease, but energy cost does not - due to the large difference in unit costs between gas and electricity prices. Recent improvements to the operation of HED are described; these changes have significantly reduced the time taken to perform simulations and have allowed many results to be generated simultaneously rather than consecutively.

A magnetic levitation system is a perfect educational example of a nonlinear instable system. Only with suitable control, a small permanent magnet can be held floating stable below a coil. After modeling and simulation of the system, control of the system can be developed. At the end, the control algorithm can be coded on a microcontroller, connected to a pilot plant.

This work is focused on the coupling of two complex

models based on different underlying physics: a vapor

compression refrigerating system and its electrical drive

system. The main challenge was to correctly handle the

large simulation time constant difference which is three

orders of magnitude smaller for the electrical system. The

two models have been originally developed following very

specific requirements (i.e. high numerical robustness and

low time consumption) for their suitable use in simula-

tions of large and complex aircraft Environmental Control

Systems (ECS). The direct coupling of both systems has

been observed to cause numerical instabilities, therefore,

a coupling approach based on non-invasive dynamic re-

laxations has been implemented. The resulting combined

simulations have shown to be numerically stable for the

whole range of operation and for a wide range of time

steps.

Contact collisions are prevalent in mechanical multi-body systems and have always been a significant limiting factor for engineering technology development. This paper examines the fundamental types of contact in multi-body dynamics systems and explores their inherent topological relationships. Based on the multi-body dynamics theory and penalty function contact algorithm, this paper constructed the multi-body dynamics contact model using Modelica, which is a multi-domain unified modeling language. To enhance the applicability of the contact model library in the modeling of multi-body system, the contact model provides a connection interface compatible with the multi-body library in the Modelica standard library.

The evaluation and analysis of complex energy supply systems with Modelica models is increasingly becoming part of the planning and design processes. Dynamic system modeling is more and more important, especially for questions regarding the use of storage and the integration of volatile renewable resources by means of intelligent control.

However, this still too often requires extensive engineering work and time-consuming modeling efforts, although the basic work steps are largely comparable and based on the same fundamentals. Especially the open interfaces to and from Modelica offer extensive possibilities for automation and generalization of these processes.

This paper describes such a new integrative and automated optimization framework for energy systems of buildings and districts, which uses Modelica models and FMUs iteratively for the identification of optimal system configurations.