Stochastic Power Control Strategy for Hybrid Electric Propulsion Ships Using Markov Chain-Based Operational Data Augmentation
Since power demand varies due to uncertain environmental conditions, a deterministic power control strategy for hybrid electric propulsion ships contains a limitation in securing robust performance. To overcome this limitation, this study applies a stochastic power control strategy based on the augm...
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MDPI AG
2025-06-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/13/7/1219 |
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| author | Su Bin Choi Soon Ho Hong Sun Je Kim |
| author_facet | Su Bin Choi Soon Ho Hong Sun Je Kim |
| author_sort | Su Bin Choi |
| collection | DOAJ |
| description | Since power demand varies due to uncertain environmental conditions, a deterministic power control strategy for hybrid electric propulsion ships contains a limitation in securing robust performance. To overcome this limitation, this study applies a stochastic power control strategy based on the augmented operational dataset. This study generated 150 datasets and derived the optimal control strategy set using a dynamic programming algorithm. By synthesizing a set of optimal control strategies, we divided them into a total of 10 bins according to the battery state of charge (SOC) and implemented a probabilistic map for the power distribution ratio according to the demanded power in each bin. Additionally, the memory and SOC correction factor were utilized to prevent frequent changes in power control and ensure that the SOC remains stable. This strategy resulted in a 3% improvement in efficiency compared to the deterministic method. In addition, it can be implemented in a real-time strategy utilizing stochastic maps. |
| format | Article |
| id | doaj-art-820be687b2c34c40bef9b8fc0975e8cf |
| institution | Kabale University |
| issn | 2077-1312 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-820be687b2c34c40bef9b8fc0975e8cf2025-08-20T03:58:30ZengMDPI AGJournal of Marine Science and Engineering2077-13122025-06-01137121910.3390/jmse13071219Stochastic Power Control Strategy for Hybrid Electric Propulsion Ships Using Markov Chain-Based Operational Data AugmentationSu Bin Choi0Soon Ho Hong1Sun Je Kim2Department of Autonomous Vehicle System Engineering, Chungnam National University, Daejeon 34134, Republic of KoreaDepartment of Autonomous Vehicle System Engineering, Chungnam National University, Daejeon 34134, Republic of KoreaDepartment of Autonomous Vehicle System Engineering, Chungnam National University, Daejeon 34134, Republic of KoreaSince power demand varies due to uncertain environmental conditions, a deterministic power control strategy for hybrid electric propulsion ships contains a limitation in securing robust performance. To overcome this limitation, this study applies a stochastic power control strategy based on the augmented operational dataset. This study generated 150 datasets and derived the optimal control strategy set using a dynamic programming algorithm. By synthesizing a set of optimal control strategies, we divided them into a total of 10 bins according to the battery state of charge (SOC) and implemented a probabilistic map for the power distribution ratio according to the demanded power in each bin. Additionally, the memory and SOC correction factor were utilized to prevent frequent changes in power control and ensure that the SOC remains stable. This strategy resulted in a 3% improvement in efficiency compared to the deterministic method. In addition, it can be implemented in a real-time strategy utilizing stochastic maps.https://www.mdpi.com/2077-1312/13/7/1219hybrid electric propulsion shipspower control strategyoperational profileMarkov chainstochastic control |
| spellingShingle | Su Bin Choi Soon Ho Hong Sun Je Kim Stochastic Power Control Strategy for Hybrid Electric Propulsion Ships Using Markov Chain-Based Operational Data Augmentation Journal of Marine Science and Engineering hybrid electric propulsion ships power control strategy operational profile Markov chain stochastic control |
| title | Stochastic Power Control Strategy for Hybrid Electric Propulsion Ships Using Markov Chain-Based Operational Data Augmentation |
| title_full | Stochastic Power Control Strategy for Hybrid Electric Propulsion Ships Using Markov Chain-Based Operational Data Augmentation |
| title_fullStr | Stochastic Power Control Strategy for Hybrid Electric Propulsion Ships Using Markov Chain-Based Operational Data Augmentation |
| title_full_unstemmed | Stochastic Power Control Strategy for Hybrid Electric Propulsion Ships Using Markov Chain-Based Operational Data Augmentation |
| title_short | Stochastic Power Control Strategy for Hybrid Electric Propulsion Ships Using Markov Chain-Based Operational Data Augmentation |
| title_sort | stochastic power control strategy for hybrid electric propulsion ships using markov chain based operational data augmentation |
| topic | hybrid electric propulsion ships power control strategy operational profile Markov chain stochastic control |
| url | https://www.mdpi.com/2077-1312/13/7/1219 |
| work_keys_str_mv | AT subinchoi stochasticpowercontrolstrategyforhybridelectricpropulsionshipsusingmarkovchainbasedoperationaldataaugmentation AT soonhohong stochasticpowercontrolstrategyforhybridelectricpropulsionshipsusingmarkovchainbasedoperationaldataaugmentation AT sunjekim stochasticpowercontrolstrategyforhybridelectricpropulsionshipsusingmarkovchainbasedoperationaldataaugmentation |