000007753 001__ 7753
000007753 005__ 20240626123055.0
000007753 02470 $$2doi$$a10.24868/issn.2631-8741.2020.015
000007753 035__ $$a4468539
000007753 037__ $$aGENERAL
000007753 245__ $$aMulti-objective optimisation and Energy Management: adapt your ship to every mission
000007753 269__ $$a2020-10-05
000007753 336__ $$aConference Proceedings
000007753 520__ $$aAdaptability, stealth, damage sustainability, extended range and reliability are key factors to every successful naval mission. The shipbuilding industry conceptualized and deployed a wide variety of power and propulsion architectures over the decades: from mechanical, to electrical and hybrid propulsion. The tendency towards increasingly complex propulsion and power generation systems calls for the development of intelligent control strategies, Energy Management Systems (EMSs), that can handle the complexity and exploit the increased degrees-of-freedom (DOFs) of hybrid systems, while conforming to all operational constraints. In current EMSs, the aim is to save fuel costs. However, the ability to adapt to a wide variety of missions in an ever changing world is important for naval vessels. Hence, this raises the question: Can further operational gains be achieved through the use of more sophisticated integrated control algorithm, with multiple optimization goals? The present work aims to address this issue, by developing such a control system for a naval platform. The proposed EMS can modulate shipboard energy production of a hybrid propulsion plant with hybrid power supply, considering the trade-off between multiple conflicting operating goals: fuel savings, maintenance costs of on-board assets, noise and infrared signature. A validated model of a Holland class Patrol Vessel has been utilized to test the proposed EMS. Simulation results under varying operational profiles demonstrate the applicability, validity and the advantages of the approach.
000007753 542__ $$fCC-BY-4.0
000007753 6531_ $$aEnergy Management
000007753 6531_ $$aHybrid propulsion
000007753 6531_ $$aMulti-objective optimization
000007753 7001_ $$aMitropoulou, D$$uRH Marine Netherlands BV, The Netherlands
000007753 7001_ $$aKalikatzarakis, M$$uResearch & Technology Support - Damen Schelde Naval Shipbuilding - the Netherlands
000007753 7001_ $$avan Der Klauw, T$$uNetherlands Organisation for Applied Scientific Research, TNO
000007753 7001_ $$aBlokland, AJ$$uNetherlands Defence Academy, The Netherlands
000007753 7001_ $$aGeertsma, RD$$uNetherlands Defence Academy, The Netherlands
000007753 7001_ $$aBucurenciu, AM$$uRH Marine Netherlands BV, The Netherlands
000007753 7001_ $$aDembinskas, D$$uRH Marine Netherlands BV, The Netherlands
000007753 773__ $$tConference Proceedings of iSCSS
000007753 773__ $$jiSCSS 2020
000007753 789__ $$whttps://zenodo.org/record/4468539$$2URL$$eIsIdenticalTo
000007753 85641 $$uhttps://www.imarest.org/events/inec-2020/iscss-2020$$yConference website
000007753 8564_ $$9f2b5dc51-c886-42aa-a5f8-97026c659771$$s1162754$$uhttps://library.imarest.org/record/7753/files/iSCSS_2020_Paper_29.pdf