FEV Software and Testing Solutions SAS
The globally operating company FEV Software and Testing Solutions with 120 employees in France and over 400 worldwide, provides cutting-edge test fields, measuring, conditioning, and control equipment as well as software solutions that help make the development process more efficient and transfer significant process steps from the road to the test rig – or even to computer simulation.
FEV-Test Systems’ model-based, collaborative development and validation framework meets the needs of development, test and calibration engineers facing the challenges of e-mobility and autonomous driving. It has replaced cumbersome and complex methodologies using numerous different techniques and tools with a revolutionary cross-disciplinary approach: a scalable platform making it possible to size and validate the Unit Under Test – such as powertrains, e-motors, power charging systems…- and its electronics at a desk before accompanying it through the subsequent phases, from the HiL and test rigs to the real life tests.
A cloud-based simulation toolchain is required to develop a predictive digital twin to support the development of advanced charging and control strategies and maximize the benefits for all stakeholders. At FEV STS SAS, we have significant experience in numerical simulation. The xMOD software developed by FEV will be extended with cloud-based capability to support the development of the predictive digital twin.
What in XL-CONNECT?
A cloud-based simulation platform will be developed and set up by FEV STS SAS. The integration process of the subcomponent models and controllers into the simulation environments will be carried out.
“The XL-CONNECT project gives us the possibility to improve our existing simulation platform and adapt it for a cloud architecture with the aim to provide to our customers a development platform for digital twin applications. This simulation platform can be used in different domains to simulate and test new design concepts before they are built, optimize production processes, and predict how a system perform in different conditions.”