Energy management is a critical issue for the advancement of fuel cell vehicles because it significantly influences their hydrogen economy and lifetime. This paper offers a comprehensive investigation of the energy management of heavy-duty fuel cell vehicles for road freight transportation. An important and unique contribution of this study is the development of an extensive and realistic representation of the vehicle operation, which includes 1750 hours of real-world driving data and variable truck loading conditions. This framework is used to analyze the potential benefits and drawbacks of heuristic, optimal, and predictive energy management strategies to maximize the hydrogen economy and system lifetime of fuel cell vehicles for road freight transportation. In particular, the statistical evaluation of the effectiveness and robustness of the simulation results proves that it is necessary to consider numerous and realistic driving scenarios to validate energy management strategies and obtain a robust design. This paper shows that the hydrogen economy can be maximized as an individual target using the available driving information, achieving a negligible deviation from the theoretical limit. Furthermore, this study establishes that heuristic and optimal strategies can significantly reduce fuel cell transients to improve the system lifetime while retaining high hydrogen economies. Finally, this investigation reveals the potential benefits of predictive energy management strategies for the multi-objective optimization of the hydrogen economy and system lifetime.

能源管理是燃料电池汽车发展的关键问题，因为它极大地影响了其氢经济性和寿命。本文对用于公路货运的重型燃料电池汽车的能源管理进行了全面研究。这项研究的一个重要而独特的贡献是对车辆操作进行了广泛而现实的表示，其中包括1750个小时的实际驾驶数据和可变的卡车装载条件。该框架用于分析启发式，最佳和预测性能源管理策略的潜在利弊，以最大化道路运输的氢经济性和燃料电池汽车的系统寿命。特别是，仿真结果的有效性和鲁棒性的统计评估证明，有必要考虑众多现实的驾驶方案，以验证能量管理策略并获得鲁棒的设计。本文表明，利用可获得的驾驶信息，可以将氢经济性作为单个目标最大化，与理论极限的偏差可忽略不计。此外，这项研究确定了启发式和最佳策略可以显着减少燃料电池瞬变，从而在保持高氢经济性的同时提高系统寿命。最后，这项研究揭示了预测性能源管理策略对于氢经济性和系统寿命的多目标优化的潜在好处。