Searching for the optimal engine speed to reduce the Energy Efficiency Operation Index (EEOI), which is an important design guide for vessels in operation, is a significant way to achieve intelligent navigation control, aiming for energy savings and emission reduction. Due to high uncertainty in the ice environment, optimization and analysis that consider uncertainty are necessary for the energy efficiency design of vessels sailing in this kind of zone. Vessels in ice areas are affected by the impact of ice loads and water velocity during navigation, which can be described by interval numbers for their simple meaning and clear boundary. This research concerns uncertainty of ice loads and water velocity in both single and multiple segments in the vessel speed optimization design process. Random statistics distribution models of the involved factors are then introduced into the interval optimization system, whose randomness is analysed. A series of cases is tested, using different interval radiuses and algorithms and other configuration parameters to analyse the influence of uncertainty. The results of optimization, with about 15% reduce of EEOI, and analysis can provide feasible guidance for vessel energy efficiency design, taking into account the uncertainty of the actual environment.

寻找最佳发动机转速以降低能效操作指数（EEOI），这是在役船舶的重要设计指南，是实现智能导航控制，节约能源和减少排放的重要途径。由于冰环境的高度不确定性，考虑不确定性的优化和分析对于在此类区域航行的船舶的能效设计是必要的。在航行期间，冰区中的船只受冰负荷和水流速度的影响，这可以用间隔号来表示，因为它们的含义简单且边界清晰。这项研究涉及船只速度优化设计过程中单段和多段冰负荷和水速的不确定性。然后将所涉及因素的随机统计分布模型引入区间优化系统，对系统的随机性进行分析。测试了一系列情况，使用不同的间隔半径和算法以及其他配置参数来分析不确定性的影响。优化结果将EEOI降低了约15％，并且考虑到实际环境的不确定性，分析可以为船舶能效设计提供可行的指导。