Increasingly, the melting of Arctic ice due to global warming has provided opportunities for commercial shipping between Asia and Europe. Given the vulnerability of the Arctic environment, especially due to emissions of short-lived pollutants from shipping activities, a more effective propulsion system with a comprehensive control strategy is required to reduce fuel consumption, thus potentially mitigating the impacts of shipping activities on the northern sea route (NSR). In this paper, a shipboard DC hybrid system powered by a combination of diesel generator sets and batteries is proposed and analysed in terms of its application on a ship in the NSR. The specific fuel consumption and various losses in the power sources were analysed to develop an efficiency-optimisation control strategy for the proposed DC hybrid power system. To evaluate the performance of the hybrid power system with the proposed optimisation control strategy, lab-scale experiments have been conducted in the Shanghai Marine Diesel Engine Research Institute to compare the proposed system with a conventional hybrid system. The experimental results indicate that the proposed DC hybrid power plant with the energy optimisation control contributes a 5.35% fuel saving compared with the DC fixed-speed diesel electric configuration during a scaled-down NSR scenario.

In order to solve the problem of incomplete consideration of voting conditions and redundancy of voting process and the excessive time consumption in the design of voting algorithm for multi-Modular redundant system, this paper proposes a method that arranges the difference between the sorted redundant modules into an upper triangular matrix and uses the upper triangular matrix to analyze the voting conditions. The upper triangular matrix covers all the information of the multi-Modular redundant system, and the points on the counter-diagonal of the upper triangular matrix have the maximum range of influence and the smallest deviation from the average calculation. Based on this, an improved plurality average voting algorithm (IPAV) is designed. For an N-Modular Redundant (NMR) system, the algorithm searches along the counter-diagonal of the upper triangular matrix and chooses the set, in which the maximum number of redundant modules satisfies n/2, to perform an averaging vote. A test method that can measure the execution time and the reliability of the algorithm is designed and tested in a Quadruple Modular Redundant system. Compared with the plurality median voter (PMV) and the adaptive majority voter (AMV), the empirical results show that IPAV has the obvious advantages of lowest time consumption and high reliability.

The growing focus on enhancing ship performance over the past decades has driven the invention of various energy-saving devices. Conducting performance analyses of these devices is essential to substantiate the claimed energy savings. However, this process is complicated by the dynamic conditions experienced by ships, such as weather and loading conditions. These factors could significantly impact the results of comparisons made between pre- and post-retrofitting performance of new energy-saving devices. This paper presents a comprehensive investigation into the performance analysis process of a general cargo vessel equipped with a Gate Rudder system, which is a twin rudder system known for its thrust-producing and energy-saving properties. A multi-input, multi-output data-driven method, utilizing in situ and weather data, is developed and applied to account for the effects of weather and loading conditions. A performance analysis is then conducted by using the data-driven models to estimate three different indicators of ship performance in terms of propulsion efficiency. The results suggest that the Gate Rudder could potentially reduce torque requirements by up to 20.70%, shaft power requirements by up to 27.58%, and fuel consumption by up to 30.35%, with the same weather and loading conditions.