Dymola Latest Release

Accelerate the evaluation and optimization of complex, interconnected supply systems.

Simplicity meets complexity

• Tailored model fidelity for speed and efficiency
• Requires minimum input data for fast setup
• Scalable and robust - ideal for complex, large-scale systems

Powerful multi-energy system modeling

• Flexible, ready-to-use components for interconnected supply systems
• Capture interactions between different domains

Optimize design and performance

• Perform trade-off studies to balance performance, cost and emissions
• Test and refine control strategies before implementation

Cut costs and minimize risk

• Reduce physical prototyping with simulations and hardware-in-the-loop (HiL) testing
• Build digital twins for early-stage fault detection and analysis
• Identify potential issues before they have any impact

Evaluate alternative drivetrain technologies

• Pure battery electric vehicle
• Battery with catenary/electric road system (ERS)
• Diesel-Electric
• Diesel-Electric with ERS

Typical applications

• Estimate the optimal truck speed for continuous operation using an ERS
• Simulate the integration of renewable energy sources
• Run fleet simulations for the evaluation of operation strategies
• Use Reduced Order Models (ROM) for long-term simulations

We continually improve Dymola to simulate larger and more complex models more efficiently. Much of this work is done through collaboration in the ITEA OpenSCALING project. Better code generation for duplicate functions. For example, caused by the redeclaration of media functions

More efficient declaration of arrays

• Significantly less C code generated

More efficient FMI import

• Reduced the size of the Modelica wrapper
• Greatly reduced the size of the generated C code

Adjoint derivatives for the ODE problem

• Generate analytical adjoint derivatives for the ODE problem
• Makes the function fmi3GetAdjointDerivative more efficient
• Part of handling parameter sensitivity in, for example, FMUs

A new user interface for parameter optimization is available in Dymola 2025x Refresh 1. It uses simple drag-and-drop to set up tuner parameters, criteria variables and the optimization algorithm.

Up to three parameters can be optimized with the standard Dymola license, more require the Optimization option

Monte Carlo simulation in Dymola has been enhanced to allow analysis of the entire simulation trajectory, plotting mean value, standard deviation and the prediction interval.

We have also implemented box plots of the observed variable and general sensitivity analysis with Sobol Indices. In addition, an improved random number generator with Latin Hypercube sampling is used by default.

Dymola allows you to directly browse and install Modelica libraries from GitHub.
 

• Type search keyword to get selection of libraries
• Select a release
• Install.