Calibration Workflow for Mechanical and Thermal Applications

Abstract

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.