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  • 标题:Energy Management of Heavy-Duty Fuel Cell Electric Vehicles: Model Predictive Control for Fuel Consumption and Lifetime Optimization
  • 本地全文:下载
  • 作者:Alessandro Ferrara ; Michael Okoli ; Stefan Jakubek
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2020
  • 卷号:53
  • 期号:2
  • 页码:14205-14210
  • DOI:10.1016/j.ifacol.2020.12.1053
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThis paper investigates the application of a simple but effective model predictive control concept for the fuel consumption and system lifetime optimization of a heavy-duty fuel cell electric vehicle. Energy management strategies primarily help extend the fuel cell lifetime by limiting shutdowns, transients and high-power operations to avoid detrimental conditions. In this framework, the proposed online control scheme determines a significant reduction of the average fuel cell power change rate and a small fuel consumption increment with respect to the control law that minimizes the fuel consumption, computed offline through the Pontryagin’s minimum principle. These results refer to the real-world driving mission of a road freight vehicle, including the elevation gradient of the road, which highly affects the load request in downhill and uphill sections. However, this preliminary study does not include a speed prediction model, but it assumes that the speed is known without uncertainties over a relatively short time horizon.
  • 关键词:KeywordsOptimal ControlOnline Energy ManagementFCEVMPCPMPFuel Cell Degradation
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