Design optimization of the podded propulsor considering pod housing drag and propulsion motor performance
The podded propulsor (POD) offers advantages such as high efficiency, low noise, and space-saving by integrating the propulsion motor and propeller. This paper presents an optimization methodology that simultaneously improves motor performance and pod housing drag through numerical analysis. The int...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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AIP Publishing LLC
2025-01-01
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| Series: | AIP Advances |
| Online Access: | http://dx.doi.org/10.1063/5.0251019 |
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| author | Yuhang Zhou Chengjiang Liu Yao Yan Quan Chen Wenliang Ke |
| author_facet | Yuhang Zhou Chengjiang Liu Yao Yan Quan Chen Wenliang Ke |
| author_sort | Yuhang Zhou |
| collection | DOAJ |
| description | The podded propulsor (POD) offers advantages such as high efficiency, low noise, and space-saving by integrating the propulsion motor and propeller. This paper presents an optimization methodology that simultaneously improves motor performance and pod housing drag through numerical analysis. The interaction between the motor and pod housing was analyzed, with parametric modeling conducted for both. The Latin hypercube sampling method generated samples of the motor and pod housing for simulation, and radial basis function neural networks were used to create approximate models for the motor performance and pod housing drag. The fitting R2 of motor efficiency, motor power density, propeller hub drag, pod body drag, and pod strut drag of the approximate model reached 0.995, 0.978, 0.920, 0.972, and 0.999, respectively. Sensitivity analysis revealed that the stator outer diameter and fore taper angle are key factors influencing motor performance and drag, respectively. A genetic algorithm was used to optimize the POD with bi-objective and tri-objective focuses on minimizing drag, maximizing motor efficiency and power density. Pareto-optimal designs were validated through simulations. The results show that tri-objective optimization increased the overall efficiency by about 4.2% and enhanced motor power density by around 22%. |
| format | Article |
| id | doaj-art-8f2cbc46a0e946b58025befe4e6781e1 |
| institution | Kabale University |
| issn | 2158-3226 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | AIP Publishing LLC |
| record_format | Article |
| series | AIP Advances |
| spelling | doaj-art-8f2cbc46a0e946b58025befe4e6781e12025-02-03T16:40:43ZengAIP Publishing LLCAIP Advances2158-32262025-01-01151015321015321-1910.1063/5.0251019Design optimization of the podded propulsor considering pod housing drag and propulsion motor performanceYuhang Zhou0Chengjiang Liu1Yao Yan2Quan Chen3Wenliang Ke4College of Electrical Engineering, Zhejiang University, Hangzhou 310027, ChinaNational Key Laboratory of Electromagnetic Energy, Naval University of Engineering, Wuhan 430033, ChinaHubei East Lake Laboratory, Wuhan 430202, ChinaHubei East Lake Laboratory, Wuhan 430202, ChinaSchool of Naval Architecture and Ocean Engineering, Huazhong University of Science and Technology, Wuhan 430074, ChinaThe podded propulsor (POD) offers advantages such as high efficiency, low noise, and space-saving by integrating the propulsion motor and propeller. This paper presents an optimization methodology that simultaneously improves motor performance and pod housing drag through numerical analysis. The interaction between the motor and pod housing was analyzed, with parametric modeling conducted for both. The Latin hypercube sampling method generated samples of the motor and pod housing for simulation, and radial basis function neural networks were used to create approximate models for the motor performance and pod housing drag. The fitting R2 of motor efficiency, motor power density, propeller hub drag, pod body drag, and pod strut drag of the approximate model reached 0.995, 0.978, 0.920, 0.972, and 0.999, respectively. Sensitivity analysis revealed that the stator outer diameter and fore taper angle are key factors influencing motor performance and drag, respectively. A genetic algorithm was used to optimize the POD with bi-objective and tri-objective focuses on minimizing drag, maximizing motor efficiency and power density. Pareto-optimal designs were validated through simulations. The results show that tri-objective optimization increased the overall efficiency by about 4.2% and enhanced motor power density by around 22%.http://dx.doi.org/10.1063/5.0251019 |
| spellingShingle | Yuhang Zhou Chengjiang Liu Yao Yan Quan Chen Wenliang Ke Design optimization of the podded propulsor considering pod housing drag and propulsion motor performance AIP Advances |
| title | Design optimization of the podded propulsor considering pod housing drag and propulsion motor performance |
| title_full | Design optimization of the podded propulsor considering pod housing drag and propulsion motor performance |
| title_fullStr | Design optimization of the podded propulsor considering pod housing drag and propulsion motor performance |
| title_full_unstemmed | Design optimization of the podded propulsor considering pod housing drag and propulsion motor performance |
| title_short | Design optimization of the podded propulsor considering pod housing drag and propulsion motor performance |
| title_sort | design optimization of the podded propulsor considering pod housing drag and propulsion motor performance |
| url | http://dx.doi.org/10.1063/5.0251019 |
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