Abstract
In the early stages of the ship design process, the system designer must choose which type of machinery system will be used to power the ship. Hybrid power systems, which are familiar in the automotive industry, have started making a breakthrough in the marine industry. However, defining the length of the financial payback period is not trivial for ship designers, which makes it harder to adopt these more expensive technologies. The shortage of on-board machinery integration software for maritime engineers has motivated the authors of this article to develop a tool that can assist ship designers in making the right choices early in the design process. Discovering the optimal power system design for a specified vessel’s operation requires optimal machinery control. This article presents a novel method to optimise the machinery control of a system specified by the tool user. A case study is presented using a fishing boat with both diesel-mechanical and hybrid electric power systems.
Highlights
Passenger vehicles with hybrid powertrains have gained a strong foothold in the automotive industry and can be seen in the traffic
The optimal usage of fishing boat machinery is studied with a shut-off strategy, which requires the GEN to run as a spinning reserve all the time
With HEB_LT_shut-off, the first noticeable difference compared with the original shut-off strategy is that after the energy storage system (ESS) is fully charged between 2.5 and 2.7 h, cycling occurs in ESS and GEN usage until the zero speed phase ends at the 3 h mark
Summary
Passenger vehicles with hybrid powertrains have gained a strong foothold in the automotive industry and can be seen in the traffic. Rather than using a time-dependent and variant duty cycles, as in the automotive industry, the starting point in a fuel-efficient vessel propulsion system design is typically testing the static operating points in specific sea trials. Such approach is equivalent to designing an efficient hybrid vehicle for only highway speeds, for example. The energy management optimisation routine, which works at a lower level, must flexibly adapt to the design parameters regarding individual components and the system topology.
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