Day-ahead Energy Management for Hybrid Electric Vessel with Different PEM Fuel Cell Modular Configurations

The increasing demand for decarbonization of marine transportation motivates the utilization of low-carbon resources. Among different options, fuel cells are drawing attention. The selection of fuel cell (FC) and the design of energy management strategy would have a great impact on the vessel’s operational efficiency, and thereby needs to be considered carefully. The objective of this paper is to develop energy management system (EMS) to reduce the fuel consumption of a hybrid fuel cell/battery ship. To this end, a day-ahead EMS scheme is proposed that takes full use of information including ship cruising routines and the degradation status of the fuel cell modules. The developed EMS is optimization-based and conducted off-line to provide guideline for the next-day power generation plan. In addition, three power allocating strategies across the multiple fuel cell modules are considered and compared (equal, independent, and sequential). A sequential rotation procedure is proposed to reduce the degradation rates of the fuel cell modules. Simulation results show that the proposed EMS can effectively improve the fuel economy of the hybrid ship while enhancing sufficient energy backup throughout the full voyage. In addition, comparisons between different FC configurations implies that the independent distribution has the highest fuel efficiency, and with the proposed rotation procedure, the sequential distribution can effectively improve the fuel efficiency by up to 23.2%

New concept and design of electronically controlled cylinder lubrication system for large two-stroke marine diesel engines

Lubrication of cylinders between liners and rings is one of the crucial factors that affects the efficient operation of diesel engines. Marine diesel engines usually use inferior heavy fuel oil with high sulphur content, and the acidic substances formed by fuel combustion need alkaline cylinder oil to neutralize. For the operational cost to a marine engine, besides fuel oil, cylinder oil also takes a big share. This article first analyses the advantages and disadvantages of existing cylinder lubrication systems with regard to oil injection control. Second, the control parameters and variables such as the oil injection pressure, timing, oil feed rate and reliability are analysed, and the corresponding control schemes formulated. Third, the control strategies are developed in detail. Finally, verification tests are carried out on an actual engine, with the results showing that the control strategies developed in this article provide a stable, cost-effective, creative and excellent solution for cylinder lubrication with reduced cylinder wear. A thin and uniform oil film distribution is retained on the liner surface, with savings in cylinder oil consumption, lower particulate matter emission levels and improved cylinder liner and piston rings running conditions. The experimental results show that the oil consumption could be reduced by up to 5

Design and experimental development of a new electronically controlled cylinder lubrication system for the large two-stroke crosshead diesel engines

Accurate, stable and reliable lubrication for the cylinders is very important to ensure the trouble-free operation of the marine diesel engines. A new electronically controlled cylinder lubrication system has been developed to remedy the defects of the conventional mechanical lubrication system. This new system’s design method, composition and implementation are described. The sensitivity tests are conducted on the test bench and the verification tests are also fulfilled on operating vessels. The main performance data are as follows: oil injection pressure about 3.0 MPa, oil injection timing precision 0.1 ms, oil injection duration 15 °CA or less. The oil injection concentrates onto the piston rings pack to ensure the good lubrication and neutralization, and the oil injection frequency is regulated according to engine load, the sulphur content in fuel, total base number of cylinder oil, cylinder liner running-in condition and so on. This results in the cylinder oil consumption rate falling approximately 25% compared with that of the conventional mechanical lubrication system. As a retrofit on vessels in service, the lubrication system has been fitted more than 120 main engines and has a payback period of less than 2 years

Rethinking Multi-Interest Learning for Candidate Matching in Recommender Systems

Existing research efforts for multi-interest candidate matching in recommender systems mainly focus on improving model architecture or incorporating additional information, neglecting the importance of training schemes. This work revisits the training framework and uncovers two major problems hindering the expressiveness of learned multi-interest representations. First, the current training objective (i.e., uniformly sampled softmax) fails to effectively train discriminative representations in a multi-interest learning scenario due to the severe increase in easy negative samples. Second, a routing collapse problem is observed where each learned interest may collapse to express information only from a single item, resulting in information loss. To address these issues, we propose the REMI framework, consisting of an Interest-aware Hard Negative mining strategy (IHN) and a Routing Regularization (RR) method. IHN emphasizes interest-aware hard negatives by proposing an ideal sampling distribution and developing a Monte-Carlo strategy for efficient approximation. RR prevents routing collapse by introducing a novel regularization term on the item-to-interest routing matrices. These two components enhance the learned multi-interest representations from both the optimization objective and the composition information. REMI is a general framework that can be readily applied to various existing multi-interest candidate matching methods. Experiments on three real-world datasets show our method can significantly improve state-of-the-art methods with easy implementation and negligible computational overhead. The source code will be released.Comment: RecSys 202