Model Preparation

Obtaining reference results, performance optimization

Moving your model from desktop simulation to real-time simulation is an iterative process that can require extensive model reconfiguration. The real-time model preparation workflow shows how to analyze and decrease the computational cost of your model on a development machine. After completing the workflow, you can determine optimal fixed-cost solver settings for simulation on a real-time target machine.


Model Preparation Objectives

Determine if your Simscape™ model is accurate enough to generate expected simulation results and fast enough to run on your real-time target machine without overruns.

Real-Time Model Preparation Workflow

Follow the real-time model preparation workflow to make your Simscape model real-time capable.

Improving Speed and Accuracy

Simulating a Simscape model in real time requires a balance of speed and accuracy that you can attain by reducing computational costs, optimizing solver configurations, or increasing processing power.

Determine Step Size

Determine the maximum step size to use for fixed-step simulation by analyzing the results from a variable-step simulation of your Simscape model.

Reduce Computation Costs

Make your Simscape model real-time capable by identifying and eliminating unnecessary, computationally costly processes such as redundant monitoring and data logging.

Reduce Fast Dynamics

To make your Simscapemodel real-time capable, decrease computational cost by reducing fast dynamics that you identify using frequency-response and pole-speed analyses.

Reduce Numerical Stiffness

Eliminate components that cause rapid changes to reduce the computation cost of simulation and to make your Simscape model real-time capable.

Reduce Zero Crossings

Eliminate components that cause zero crossings to increase the minimal step-size for fixed-step simulation and to make your Simscape model real-time capable.

Partition a Model

Partition a Simscape model for parallel processing on real-time processors.

Manage Model Variants

Select model variants for dynamic systems using variant subsystems.

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