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Upscaling Product development Simulation Capabilities exploiting Artificial inteLligence for Electrified vehicles



Website containing all the publishable information related to the project. This deliverable belongs to Task 7.2. In the deliverable the main website functions will be described

Corresponding load cases for the full vehicle models to be used within the project

Definition of the load cases for the previous specified vehicles models. This deliverable will be obtained in task 5.1.

Reduced order models for aerodynamic performance prediction

This delievrable will describe the steps taken to define the reduced order models that will be obtained when the task2.2 is completed.

Requirements for aerothermal simulations reduced order model

"This report will list the requirements for the variables necessary to perform the ""offline"" phase to generate the AI/ROM models. This is in terms of which variables, the size of the dataset and the characteristics to obtain the desired accuracy in every case. This deliverable results from Task 2.1. "

Potential for ML-based acceleration in finite volume

Report of the solver algorithm review and further acceleration potential assessment, focusing on the pressure correction step for the acceleration efforts. This deliverable is a result of ST1.1.1.

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AI Enhanced Methods for Virtual Prediction of Short Circuit in Full Vehicle Crash Scenarios

Author(s): Alexandre Dumon, Michael Andres, Stefano Menegazzi, Christoph Breitfuss, Cristian Jimenez, Francisco Chinesta, Fatima Daim, Alain Tramecon
Published in: SAE Technical Paper Series, 2020
DOI: 10.4271/2020-01-0950