1. Developing the methodology for connected and shared XIL experiments and specifying the architecture of corresponding experimental environment;
  2. Designing hardware and software components required for the realization of shared XIL experiments;
  3. Introduction of a machine learning layer in XIL subsystem models for automatic improvement of real-time (RT) model accuracy and confidence based on test setup results;
  4. Development and validation of high-confidence models suitable for the accelerated time virtual simulation, which will merge the different technologies involved and allow seamless integration and scalability keeping compatibility with Functional Mock-up Interface (FMI) approach to co-simulation;
  5. Performing case studies, which will demonstrate practical implementation of the XILforEV concept and the benefits in references cases, incl. validation of fail-safe and robustness functionality of developed systems;
  6. Developing procedures for inclusion of users into the shared experiments with consideration of Open Access and Open Science frameworks.

Structure and Work Packages