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https://doi.org/10.1016/j.apenergy.2023.122559
Copy DOIJournal: Applied Energy | Publication Date: Jan 5, 2024 |
Citations: 2 | License type: cc-by-nc-nd |
This study proposes a predictive equivalent consumption minimization strategy (P-ECMS) that utilizes velocity prediction and considers various dynamic constraints to mitigate fuel cell degradation assessed using a dedicated sub-model. The objective is to reduce fuel consumption in real-world conditions without prior knowledge of the driving mission. The P-ECMS incorporates a velocity prediction layer into the Energy Management System. Comparative evaluations with a conventional adaptive-ECMS (A-ECMS), a standard ECMS with a well-tuned constant equivalence factor, and a rule-based strategy (RBS) are conducted across two driving cycles and three fuel cell dynamic restrictions (|di/dt|max≤ 0.1, 0.01, and 0.001 A/cm2s). The proposed strategy achieves H2 consumption reductions ranging from 1.4% to 3.0% compared to A-ECMS, and fuel consumption reductions of up to 6.1% when compared to RBS. Increasing dynamic limitations lead to increased H2 consumption and durability by up to 200% for all tested strategies.
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