Updated eFMI tutorial 2025 news.

Author: christoff-buerger

content/news/2025-07-04.md

@@ -9,7 +9,9 @@ date: 2025-07-04
 
 The recording and slides of the eFMI® Tutorial presented at the [16th International Modelica & FMI Conference](https://modelica.org/events/modelica2025/) (8th of September 2025) are now public available on [YouTube](https://youtu.be/HobYT2BYTL0) (videos) and the [eFMI website](https://www.efmi-standard.org/) (slides & videos).
 
-We had about 15 participants from 13 organizations and the feedback has been great! Close to all participants managed to follow the hands-on, for which we provided a portable Dymola & CATIA Software Production Engineering with all required tooling like compilers, libraries etc included. Many of the participants got really excited and used the unique opportunity provided by the conference to discuss the feasability of eFMI in their application domain. **We like to thank each participant for joining the tutorial and your kind feedback!**
+We had about 15 participants from 13 organizations and the feedback has been great! Close to all participants managed to follow the hands-on, for which we provided a portable Dymola & CATIA Software Production Engineering with all required tooling like compilers, libraries etc included. Many of the participants got really excited and used the unique opportunity provided by the conference to discuss the feasability of eFMI in their application domain.
+
+**We like to thank each participant for joining the tutorial and your kind feedback!**
 
 The tutorial demonstrates the current state-of-the-art of available eFMI tooling in five individual parts, including an eFMI overview, motivating example, hands-on, advanced examples and industry use-case. The respective YouTube recordings are:
  - [Part 1: eFMI® motivation and overview](https://youtu.be/HobYT2BYTL0)
@@ -18,12 +20,13 @@ The tutorial demonstrates the current state-of-the-art of available eFMI tooling
  - [Part 4: Advanced demonstrators](https://youtu.be/nkugRv_cwnA)
  - [Part 5 (industry case-study): eFMI based thermal management system (TMS) development for fuel cell electric vehicles (FCEV)](https://youtu.be/aJlEDmVOuVQ)
 
-Highlights of the tutorial are the advanced examples (Part 4), including the new `eFMI.NeuralNetworks` Modelica library, and the first application of eFMI in industrial production for the thermal management of the fuel cells of an electric vehicle (Part 5). The individual parts are:
- - **Part 1 – eFMI® motivation and overview:** High-level overview of the eFMI Standard and workflow from acausal physics models in Modelica® down to embedded target code.
- - **Part 2 – Running use-case introduction:** Comprehensible Modelica® example demonstrating the advantages and beauty of eFMI. The use-case is an electric vehicle drivetrain torque controller to reduce drivetrain vibrations, using a simple inverse model of the elastic drivetrain (virtual sensor) to feed – and thereby improve the behavior of – a off-the-shelf PI controller from the Modelica Standard Library.
- - **Part 3 – Hands-on in Dymola and Software Production Engineering:** Hands-on experience in Dymola (Dassault Systèmes) and Software Production Engineering (Dassault Systèmes) to generate an eFMU for the example of Part 2. Besides final software-in-the-loop (SiL) and recalibration tests, the generated eFMU and its various intermediate model representations are investigated, focusing on the non-functional quality criteria satisfied by the generated solution, like traceability between eFMU containers, MISRA C:2023 compliance of generated production code and other code quality criteria like static memory allocation and error handling. Also, tooling to import eFMI production code in Simulink® (The MathWorks, Inc.) as C Function blocks or to export production code as Arduino® sketch is presented.
- - **Part 4 – Advanced demonstrators:** Two advanced examples demonstrating how eFMI can help with the development of advanced hard real-time model-predictive control in safety-critical embedded environments. The first example is a battery management system (BMS) where the battery cell model is used as virtual sensor to predict the cell core tempurate, such that power requests can be limited to avoid battery damage due to overheating. The second example is a quarter car vehicle model (QVM), that is a hybrid physics and neural networks (NN) model – a so called physics-enhanced neural ordinary differential equations system (PeN-ODE) – with the unknown non-linear physics of the suspension incorporated by NN surrogate models that are well integrated with known physics of the QVM.
- - **Part 5 – Industry case-study:** Industry use-case for the eFMI based development of a thermal management system (TMS) for a fuel cell electric vehicle (FCEV).
+![eFMI® Tutorial - Part 5: FCEV](/media/news/2025-07-04-FCEV.png)
+
+![eFMI® Tutorial - Part 4: BMS](/media/news/2025-07-04-BMS.png)
+
+![eFMI® Tutorial - Part 4: Neural QVM](/media/news/2025-07-04-NeuralQVM.png)
+
+Highlights of the tutorial are Part 4, the advanced examples including the new [eFMI.NeuralNetworks Modelica library](https://github.com/modelica/efmi-testcases) and the battery management system (BMS) demonstrator presented at the DS booth ([BMS technical report](/media/resources/eFMI-Tutorial-2025-Part-4-BMS-demo.pdf)), and Part 5, the first application of eFMI in industrial production for the thermal management of the fuel cells of an electric vehicle by iVH ([presentation slides](/media/resources/eFMI-Tutorial-2025-Part-5.pdf)). Both parts show the steady progress of eFMI tooling and how we can achieve high-hanging fruits with the tooling we already have right now.
 
 If you have any general questions or feedback on what you think we need to improve or also cover in such tutorial, please contact us on our _public_ mailing list, [`efmi-info@googlegroups.com`](https://groups.google.com/g/efmi-info) (no Google account required) or write a _private_ mail to `Christoff.Buerger@3ds.com`.