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Optimal control of the power split for a fuel cell vehicle considering air path dynamics

Benjamin Pla, Pau Bares, André Aronis, Douglas Pinto, Davide Di Blasio, Tom Fletcher, Richard Burke

Research output: Contribution to journalConference articlepeer-review

Abstract

Dynamic Programming (DP) is often used to compute the optimal energy management in fuel cell vehicles (FCV) during a priori known driving cycles to benchmark different technologies or provide insight into suitable control strategies to be applied online. Due to the curse of dimensionality, using DP usually involves the use of simplified models that apply the quasi-steady approach for FC modelling, employing a map that provides the net FC power for a given current demand. While electro-chemistry processes inside the FC are much faster than the driving cycle dynamics, the response of the air-path, specially if turbocharging is used may make the quasi-steady hypothesis too optimistic. In this work, a state-of-the-art FCV model with seven states, adapted from the literature, has been calibrated using experimental data for the FC. The performance of using the quasi-steady approach for DP optimization has been assessed, leading to errors in H2 consumption above 13% for the considered cycles. Then, a model order reduction technique based on the Singular Value Decomposition (SVD) is applied to enable the use of DP on a simplified model including FC dynamics with positive results reducing the gap between the global and simplified model to levels lower than 10% and providing benefits in H2 consumption of 3.7 and 1.3% in WLTC and RDE cycles, respectively.
Original languageEnglish
Pages (from-to)91-96
Number of pages6
JournalIFAC-PapersOnLine
Volume59
Issue number5
DOIs
Publication statusPublished - 6 Aug 2025

Funding

The authors acknowledge the Agencia Estatal de Investigacion, through project Optimal Energy Management in Connected Bat-tery Electric Vehicles (PID2023-152466OB-I00), for supporting the research and development of intelligent technologies for sustainable mobility.

FundersFunder number
Agencia Estatal de Investigación
Optimal Energy Management in Connected Bat-tery Electric VehiclesPID2023-152466OB-I00

    Keywords

    • Fuel cell vehicle
    • dynamic programming
    • energy management strategy
    • model order reduction

    ASJC Scopus subject areas

    • Control and Systems Engineering

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