Uncertainty quantification for high-speed train dynamics modeling and optimization under uncertainties to limit energy consumption - Université Paris-Est Marne-la-Vallée

Uncertainty quantification for high-speed train dynamics modeling and optimization under uncertainties to limit energy consumption - Université Paris-Est Marne-la-Vallée

Controlling the energy consumption is an important stake in today’s world. In the railway field, the energy consumed by high-speed trains depends on many variables such as the driver behaviour. Significant variations have been noticed for different drivers on the same journey. To help drivers, crossing points are defined along the journey, but differences still exist. The industrial objective of this work is to define a model, able to describe the train dynamics and to propose an optimization method, which aims to minimize the energy consumption......

Julien Nespoulous, Christian Soize, Christine Fünfschilling, Guillaume Perrin. Uncertainty quantification for high-speed train dynamics modeling and optimization under uncertainties to limit energy consumption. The 15th World Congress of Computational Mechanics (WCCM 2022), Jul 2022, Yokohama, Japan. ⟨hal-03749644⟩