Co-simulation Extrapolation Using Mathematical Models

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Solution Overview

Problem

Existing co-simulation methods face challenges in accurately extrapolating coupling variables over long time intervals, leading to coupling errors and disruptions in real-time simulations, especially due to dead times caused by communication and measurement processes.

Innovation Solution

A method and simulation device that uses a mathematical model to extrapolate coupling variables, allowing for reliable prediction and compensation of dead times, enabling real-time co-simulation by determining the time behavior of subsystems and handling errors through model-based extrapolation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If signal-based extrapolation methods are used for coupling variables, then the co-simulation can be performed with simple implementation, but the extrapolation accuracy deteriorates over long time intervals

Engineering Contradiction:
ImproveEase of implementationVSAvoidExtrapolation accuracy
Core Design Contradiction:
Ease of manufactureVSMeasurement precision

Solution Approach 1:

The patent changes the fundamental parameter of extrapolation from signal-based to model-based approaches. By using mathematical models that incorporate system dynamics and physics principles, the extrapolation accuracy is significantly improved over long time intervals while maintaining computational efficiency through model reduction techniques.

Inventive Principle:
Principle #35Parameter changes

Solution Approach 2:

The patent introduces mathematical models as intermediaries between the subsystems in co-simulation. These models serve as mediators that predict coupling variables more accurately by incorporating system knowledge, thereby improving extrapolation accuracy without requiring frequent data exchange between subsystems.

Inventive Principle:
Principle #24Intermediary (Mediator)

2Measurement precision

If the sampling steps or exchange intervals are kept small to reduce coupling error, then the extrapolation accuracy improves, but the computing time increases

Engineering Contradiction:
ImproveCoupling error accuracyVSAvoidComputing time
Core Design Contradiction:
Measurement precisionVSProductivity

Solution Approach 1:

The patent applies preliminary action by using mathematical models to predict future states of coupling variables before the actual exchange time. This allows the system to prepare accurate coupling variable values in advance, reducing the need for frequent exchanges and thereby decreasing computing time while maintaining accuracy.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent employs dynamic model-based extrapolation that adapts to changing system conditions. The mathematical models dynamically adjust predictions based on current system states, allowing for accurate coupling variable estimation over variable time intervals without requiring uniformly small sampling steps.

Inventive Principle:
Principle #15Dynamics

3Loss of time

If model-based extrapolation is used to extrapolate over several coupling time steps, then real-time co-simulation becomes possible, but the device complexity increases

Engineering Contradiction:
ImproveReal-time capabilityVSAvoidSystem complexity
Core Design Contradiction:
Loss of timeVSDevice complexity

Solution Approach 1:

The patent segments the overall system into independent subsystems, each with its own mathematical model. This segmentation allows each subsystem to be simulated independently with model-based extrapolation, enabling real-time co-simulation while managing complexity through modular architecture and localized modeling efforts.

Inventive Principle:
Principle #1Segmentation

Data Source

PatentEP2987039B1Method and device for co-simulating two subsystems
Publication Date: 2020.09.23 VIRTUAL VEHICLE RES GMBH
  • EP2987039B1 patent drawingFigure 1~4
  • EP2987039B1 patent drawingFigure 3
  • EP2987039B1 patent drawingFigure 5

AI summary

In order to achieve real-time co-simulation of subsystems of a complete system (1), said subsystems being reciprocally coupled by coupling variables (y1, y2), a mathematical model (M) of the subsystems (TS1, TS2) which is valid at the actual point of operation of the complete system (1) is determined from input variables (x1, x2) and/or measurement variables (w1, w2) of said subsystems (TS1, TS2) using a data-based model identification method, and from this model (M), the coupling variables (y1, y2) are extrapolated for a subsequent coupling time step and supplied to the subsystems (TS1, TS2).