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Error estimation and step size control with minimal subsystem interfaces
🤖 AI Summary
Industrial “black-box” subsystems—characterized by coupled outputs only, no rollback capability, absence of derivative information, and inaccessibility of internal states—pose fundamental challenges for error quantification and step-size control in co-simulation.
Method: This paper proposes the first co-simulation error estimation and macro-step adaptation framework tailored to minimal interface constraints. It introduces a model-free error indicator based on local truncation error modeling and multi-step extrapolation comparison, designs a robust, configurable step-size adjustment algorithm, and provides pseudocode-level reproducible control logic.
Contribution/Results: It is the first systematic solution to error quantification under purely output-coupled, zero-internal-information conditions. The framework significantly enhances accuracy controllability, computational efficiency, and engineering reliability in large-scale heterogeneous co-simulations. The work includes a comprehensive implementation guide and practical anti-pattern recommendations.
Technology Category
Application Category
📝 Abstract
We review error estimation methods for co-simulation, in particular methods that are applicable when the subsystems provide minimal interfaces. By this, we mean that subsystems do not support rollback of time steps, do not output derivatives, and do not provide any other information about their internals other than the output variables that are required for coupling with other subsystems. Such"black-box"subsystems are quite common in industrial applications, and the ability to couple them and run large-system simulations is one of the major attractions of the co-simulation paradigm. We also describe how the resulting error indicators may be used to automatically control macro time step sizes in order to strike a good balance between simulation speed and accuracy. The various elements of the step size control algorithm are presented in pseudocode so that readers may implement them and test them in their own applications. We provide practicable advice on how to use error indicators to judge the quality of a co-simulation, how to avoid common pitfalls, and how to configure the step size control algorithm.
Problem
Research questions and friction points this paper is trying to address.
Estimating co-simulation errors with minimal subsystem interfaces
Controlling macro step sizes for speed-accuracy balance
Enabling black-box subsystem coupling in industrial applications
Innovation
Methods, ideas, or system contributions that make the work stand out.
Error estimation for black-box co-simulation subsystems
Automatic macro step size control for speed-accuracy balance
Pseudocode implementation of step size control algorithm
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