Title: Model Reduction of a Fuel Cell Vehicle using Energetic Macroscopic Representation under Simcenter Amesim
Written by: Achref Elkamel, Eduard-Edis Răclaru, Walter Lhomme, Daniela Chrenko, Fei Gao
Abstract: The automotive world is changing very fast, the electrification of powertrains becomes an obligation not an option. The step of simulation is one of the main steps in the road to develop the different models of electrified vehicles. Accurate and fast simulation program are one of the solutions to accelerate the process of the development of a virtual model. This paper shows how to reduce an existing dynamic model of a fuel cell electric vehicle (FCEV) to a static one and what are the main benefits behind this reduction in term of simulation time and design difficulty. The FCEV “Mobypost” range extender will be modelled and simulated using the Energetic Macroscopic Representation (EMR) under Simcenter Amesim in the Cloud which will be the technical environment during this study. The results of the static model will be compared to the dynamic one and to the measured values. The static model under Simcenter Amesim in the Cloud was simulated in 20 s compared to 9 min 15 s for the dynamic model and the error between the simulation and the measured values shows that the dynamic model has the best accuracy with ±1% but the static model also offers a good accuracy with ±2%.
Keywords: Cloud computing, Computational modeling, Roads, Hardware-in-the-loop simulation, Measurement uncertainty, Mechanical power transmission, Propulsion
DOI: 10.1109/VPPC53923.2021.9699222
Original article: https://ieeexplore.ieee.org/document/9699222
