Dymola Latest Release
Discover what's new in the latest release of DYMOLA.
Dymola 2026x Refresh 1
Dymola 2026x Refresh 1 is generally available on 17 April 2026.
- Summary
- Model development
- Simulation
- Librairies
Summary
Model development
- Icons in the variable browser. Makes browsing of the simulation result easier.
- LEO virtual companion (AI) for model development and analysis, requires integration with 3DEXPERIENCE (Beta).
Simulation
- Integrated calibration of model parameters (new user interface).
- Parameter sweep with grouping.
- Dynamic optimization of FMUs using e.g. CasADi (Beta).
Other
- Library improvements.
- Integrated eFMI production code generation. Code generation on cloud not needed.
Model development
Icons in the variable browser
- Components are shown with icons
- Makes browsing of the simulation result easier
LEO virtual companion (AI)
- For model development and analysis
- Requires integration with 3DEXPERIENCE
- Controlled availability for evaluation
Used classes view
- Shows the currently displayed class name and line number
- Makes Used Classes more useful
Simulation
Integrated calibration of model parameters
- New and more convenient user interface
- Validate and save calibrated parameters in the model
- Can be used to generate calibration scripts
Parameter sweep with grouping
- Uses the nth value of each parameter to group variations
Dynamic optimization of FMUs
- Implemented for more advanced FMU functionality
- Aimed supporting e.g. optimization tools
- In collaboration with CasADi
- Controlled availability for evaluation
Library Improvements
Battery modules
- Aggregation of the electric models of multiple battery cells
- Improved computational performance
- Increased efficiency of large pack simulation
Sustainable supply systems
- Techno-economic assessments of components and systems
- Emission tracking per scope
- Building internal heat gains
Testing library
- Improved function checks
- Improved visuals
- Renamed test results aligned with PSTesting and junit
Dymola 2026x
Dymola 2026x is generally available as of 28 November 2025.
- Summary
- Library
- Electric Road System
- Simulation
Summary
Libraries
- Sustainable Supply Systems Library
- Modelica Standard library 4.1.0
Simulation
- Reduced the size of Modelica FMU wrapper
- More efficient code generation for arrays
- Analytical adjoint derivatives for the ODE problem
Model development
- Text editor: select a variable and open its definition
Sustainable Supply Systems Library
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
Electric Road System for Mining Operations
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
More Efficient Simulation
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
Dymola 2025x Refresh 1
Dymola 2025x Refresh 1 is generally available on 18 April 2025.
- Summary
- Parameter Optimization
- Monte Carlo Simulation
- Install Libraries from GitHub
Summary
For this new release, the main benefits relate to the following topics:
- Simplified parameter optimization user interface
- Enhanced Monte-Carlo simulation
- Download and install libraries from GitHub
- Further improved unit checking
Parameter Optimization
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
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.
Install Libraries from GitHub
Dymola allows you to directly browse and install Modelica libraries from GitHub.
- Type search keyword to get selection of libraries
- Select a release
- Install.
Dymola 2025x
- What's New in Dymola 2025x
- Model development
- Simulation
- Libraries
What's New in Dymola 2025x
For this new release, the main benefits relate to the following topics:
Model development
- Variable-length parameter arrays
- Improved parameter management
- Better Git support
Simulation
- Faster simulation of Modelica functions
- New FMI co-simulation technology
- Dymola Modelica Compiler
Libraries: TIL Suite
Parameter arrays
Variable-length parameter arrays makes it possible to represent lookup tables in native Modelica, without the use of C code and external objects.
Parameter arrays can be initialize at simulation initialization, not translation. Dymola allows such arrays to fix the size hen data is read. This is also supported in FMUs generated by Dymola.
FMI co-simulation technology
We have implemented new co-simulation technology aimed to improve performance of “heavy” FMUs with variable-step solvers. For the right model it reduces the number of f-evaluations and Jacobian evaluations.
The fundamental idea is to smooth continuous-time Real inputs by linear interpolation during the next doStep call. This means the numeric integrator can continue without costly resets, leading to larger step-size and fewer evaluations. Furthermore, a predictor compensation gives better error estimates. For a small but hard-to-solve model we get this improvement.
TIL-Suite libraries
The existing ThermalSystems library is replaced by TIL-Suite from TLK-Thermo. This change will offer more complete range of libraries and extended functionality.
It is divided into four library products at Dassault Systèmes:
- TIL Base Library
- TIL Mobile Air Conditioning Library
- TIL Hydrogen Library
- TIL Thermal Storages Library
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