Cross-scale modeling and 6E analysis of a cold storage Rankine-Carnot battery and PEMFC coupled system for liquid hydrogen maritime transportation

The maritime transportation of liquid hydrogen presents challenges related to boil-off hydrogen (BOH) generation. To address this, this paper proposes a novel CSRCB-PEMFC coupled system, designed for both sailing and loading conditions, The PEMFC generates power using BOH, while the CSRCB effectively utilizes the low-grade waste heat from the PEMFC and the cold energy contained in the BOH. The cross-scale energy flow analysis model based on heat flow topology provides a systematic approach for studying the heterogeneous energy transfer and distribution within the system. A comprehensive 6E analysis method—covering energy, exergy, exergoeconomic, exergoenvironmental, emergoeconomic, and emergoenvironmental factors—it encompasses multiple perspectives focusing on energy, exergy, economic, and environmental aspects. The results show that the proposed system achieves an efficiency of up to 51 % under sailing conditions and generates 85.45 % surplus electricity while at berth. The exergy efficiencies under the two conditions reach 51.86 % and 54.58 %, respectively, indicating good performance in controlling irreversible losses. The P2P efficiency of the CSRCB reaches 37.17 %. Meanwhile, the system's performance is influenced by operating conditions and needs to be adjusted within an appropriate range based on actual requirements. From the energy efficiency perspective, the air compressor has a significant impact on cycle efficiency. However, delving into the exergy perspective, HEX3 and HEX4 account for 5.63 % and 6.5 % of exergy losses during sailing and loading conditions, respectively. From further economic and environmental perspectives, HEX5 and P1 demonstrate economic and environmental performance worthy of optimization under sailing and berthing conditions, respectively. Therefore, focusing on a single analytical perspective may misjudge system performance. Conducting in-depth multi-perspective analysis based on the system's actual requirements ensures optimal performance.