Evaluation of energy management strategies for fuel cell/battery-powered underwater vehicles against field trial data
This study combines high-fidelity simulation models with experimental power consumption data to evaluate the performance of Energy Management Strategies (EMS) for fuel cell/battery hybrid Autonomous Underwater Vehicles (AUV). The performance criteria are energy efficiency, power reliability and syst...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-05-01
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| Series: | Energy Conversion and Management: X |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590174522000162 |
| _version_ | 1818194451600769024 |
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| author | Clemens Deutsch Ariel Chiche Sriharsha Bhat Carina Lagergren Göran Lindbergh Jakob Kuttenkeuler |
| author_facet | Clemens Deutsch Ariel Chiche Sriharsha Bhat Carina Lagergren Göran Lindbergh Jakob Kuttenkeuler |
| author_sort | Clemens Deutsch |
| collection | DOAJ |
| description | This study combines high-fidelity simulation models with experimental power consumption data to evaluate the performance of Energy Management Strategies (EMS) for fuel cell/battery hybrid Autonomous Underwater Vehicles (AUV). The performance criteria are energy efficiency, power reliability and system degradation. The lack of standardized drive cycles is met by the cost-efficient solution of synthesizing power profiles from sampled AUV field trial data. Three power profiles are used to evaluate finite-state machine, fuzzy logic and two optimization-based EMS. The results reveal that there is a trade-off between the objectives. The rigidity of the EMS determines its load-following behavior and consequently the performance regarding the objectives. Rule-based methods are particularly suitable to design energy-efficient operations, whereas optimization-based methods can easily be tuned to provide power reliability through load-following behavior. Both classes of EMS can be best-choice methods for different types of missions. |
| first_indexed | 2024-12-12T01:02:30Z |
| format | Article |
| id | doaj.art-3957371ad93241db8574016522d82fa4 |
| institution | Directory Open Access Journal |
| issn | 2590-1745 |
| language | English |
| last_indexed | 2024-12-12T01:02:30Z |
| publishDate | 2022-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Conversion and Management: X |
| spelling | doaj.art-3957371ad93241db8574016522d82fa42022-12-22T00:43:41ZengElsevierEnergy Conversion and Management: X2590-17452022-05-0114100193Evaluation of energy management strategies for fuel cell/battery-powered underwater vehicles against field trial dataClemens Deutsch0Ariel Chiche1Sriharsha Bhat2Carina Lagergren3Göran Lindbergh4Jakob Kuttenkeuler5KTH Royal Institute of Technology, Teknikringen 8, 114 28 Stockholm, Sweden; Corresponding author.KTH Royal Institute of Technology, Teknikringen 42, 114 28 Stockholm, SwedenKTH Royal Institute of Technology, Teknikringen 8, 114 28 Stockholm, SwedenKTH Royal Institute of Technology, Teknikringen 42, 114 28 Stockholm, SwedenKTH Royal Institute of Technology, Teknikringen 42, 114 28 Stockholm, SwedenKTH Royal Institute of Technology, Teknikringen 8, 114 28 Stockholm, SwedenThis study combines high-fidelity simulation models with experimental power consumption data to evaluate the performance of Energy Management Strategies (EMS) for fuel cell/battery hybrid Autonomous Underwater Vehicles (AUV). The performance criteria are energy efficiency, power reliability and system degradation. The lack of standardized drive cycles is met by the cost-efficient solution of synthesizing power profiles from sampled AUV field trial data. Three power profiles are used to evaluate finite-state machine, fuzzy logic and two optimization-based EMS. The results reveal that there is a trade-off between the objectives. The rigidity of the EMS determines its load-following behavior and consequently the performance regarding the objectives. Rule-based methods are particularly suitable to design energy-efficient operations, whereas optimization-based methods can easily be tuned to provide power reliability through load-following behavior. Both classes of EMS can be best-choice methods for different types of missions.http://www.sciencedirect.com/science/article/pii/S2590174522000162Autonomous underwater vehicle (AUV)Fuel cellHybridEnergy management strategies |
| spellingShingle | Clemens Deutsch Ariel Chiche Sriharsha Bhat Carina Lagergren Göran Lindbergh Jakob Kuttenkeuler Evaluation of energy management strategies for fuel cell/battery-powered underwater vehicles against field trial data Energy Conversion and Management: X Autonomous underwater vehicle (AUV) Fuel cell Hybrid Energy management strategies |
| title | Evaluation of energy management strategies for fuel cell/battery-powered underwater vehicles against field trial data |
| title_full | Evaluation of energy management strategies for fuel cell/battery-powered underwater vehicles against field trial data |
| title_fullStr | Evaluation of energy management strategies for fuel cell/battery-powered underwater vehicles against field trial data |
| title_full_unstemmed | Evaluation of energy management strategies for fuel cell/battery-powered underwater vehicles against field trial data |
| title_short | Evaluation of energy management strategies for fuel cell/battery-powered underwater vehicles against field trial data |
| title_sort | evaluation of energy management strategies for fuel cell battery powered underwater vehicles against field trial data |
| topic | Autonomous underwater vehicle (AUV) Fuel cell Hybrid Energy management strategies |
| url | http://www.sciencedirect.com/science/article/pii/S2590174522000162 |
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