Optimal components sizing and power management for a fuel cell electric race car using a bi-level strategy
Résumé
To improve the performances of a hydrogen hybrid vehicle, it is necessary to optimally size its components and elaborate optimal power management control between the different embedded sources. As both operations are systematically linked, it is advisable to avoid solving these optimization problems separately. In this paper, we propose a coupled method for components sizing and offline power management in a fuel cell electric racing vehicle. The bi-level strategy developed uses Nondominated Sorting Genetic Algorithms for electrical components optimal sizing and Mixed Integer Linear Programming for optimal power management control. The final results obtained show good performances and acceptable compromise between the models used, the simplifications made on the power profile, and the relevance of the preliminary design parameters.
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