Energy Management Optimization and Validation of a Hydrogen Fuel Cell-Powered Agricultural Tractor Based on Hierarchical Dynamic Programming
In addressing challenges associated with the constrained enhancement of range performance in pure electric tractors, the difficulty in achieving genuinely eco-friendly agricultural machinery with hybrid powertrains, and the outdated approaches to energy optimization in hydrogen fuel cell tractors, a...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10419358/ |
| _version_ | 1797305323856330752 |
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| author | Yanying Li Mengnan Liu Yiting Wang Liyou Xu Shenghui Lei |
| author_facet | Yanying Li Mengnan Liu Yiting Wang Liyou Xu Shenghui Lei |
| author_sort | Yanying Li |
| collection | DOAJ |
| description | In addressing challenges associated with the constrained enhancement of range performance in pure electric tractors, the difficulty in achieving genuinely eco-friendly agricultural machinery with hybrid powertrains, and the outdated approaches to energy optimization in hydrogen fuel cell tractors, a comprehensive methodology covering the entire spectrum of system design, optimization, and validation is presented. This method constructs an integrated electromechanical and hydraulic power bond graph model for an agricultural tractor, encompassing energy systems, drive systems, and lifting systems. It achieves rapid interaction between 20-sim software and Matlab/Simulink software through a script toolbox. In order to tackle the real-time applicability challenges of dynamic programming, a hierarchical dynamic programming is proposed. The dynamic programming strategy results serve as the upper-level output. At the lower layer, preprocessing of impact value variables is carried out to filter the input variables for the general regression neural network. This enables the real-time application of the dynamic programming algorithm and significantly reduces training time. Finally, validation is conducted through both model-in-the-loop and hardware-in-the-loop. The results demonstrate the correctness and superiority of the designed tractor simulation model and energy management strategy model compared to the power-following strategy. Specifically, in plowing conditions, the dynamic programming and hierarchical dynamic programming strategies exhibited reductions of 10.278% and 6.728%, respectively, in equivalent hydrogen consumption compared to power-following strategy. In transportation conditions, the reductions are 16.02% for dynamic programming strategy and 4.87% for hierarchical dynamic programming strategy, both relative to power-following strategy. This study lays the theoretical groundwork for modeling dynamic systems of tractors and optimizing energy management. |
| first_indexed | 2024-03-08T00:25:15Z |
| format | Article |
| id | doaj.art-d6e55f12821a4ee5a7c51e75dc515abf |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-08T00:25:15Z |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-d6e55f12821a4ee5a7c51e75dc515abf2024-02-16T00:01:33ZengIEEEIEEE Access2169-35362024-01-0112213822140110.1109/ACCESS.2024.336223110419358Energy Management Optimization and Validation of a Hydrogen Fuel Cell-Powered Agricultural Tractor Based on Hierarchical Dynamic ProgrammingYanying Li0https://orcid.org/0009-0008-7214-6961Mengnan Liu1Yiting Wang2Liyou Xu3Shenghui Lei4College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang, ChinaCollege of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang, ChinaCollege of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang, ChinaCollege of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang, ChinaCollege of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang, ChinaIn addressing challenges associated with the constrained enhancement of range performance in pure electric tractors, the difficulty in achieving genuinely eco-friendly agricultural machinery with hybrid powertrains, and the outdated approaches to energy optimization in hydrogen fuel cell tractors, a comprehensive methodology covering the entire spectrum of system design, optimization, and validation is presented. This method constructs an integrated electromechanical and hydraulic power bond graph model for an agricultural tractor, encompassing energy systems, drive systems, and lifting systems. It achieves rapid interaction between 20-sim software and Matlab/Simulink software through a script toolbox. In order to tackle the real-time applicability challenges of dynamic programming, a hierarchical dynamic programming is proposed. The dynamic programming strategy results serve as the upper-level output. At the lower layer, preprocessing of impact value variables is carried out to filter the input variables for the general regression neural network. This enables the real-time application of the dynamic programming algorithm and significantly reduces training time. Finally, validation is conducted through both model-in-the-loop and hardware-in-the-loop. The results demonstrate the correctness and superiority of the designed tractor simulation model and energy management strategy model compared to the power-following strategy. Specifically, in plowing conditions, the dynamic programming and hierarchical dynamic programming strategies exhibited reductions of 10.278% and 6.728%, respectively, in equivalent hydrogen consumption compared to power-following strategy. In transportation conditions, the reductions are 16.02% for dynamic programming strategy and 4.87% for hierarchical dynamic programming strategy, both relative to power-following strategy. This study lays the theoretical groundwork for modeling dynamic systems of tractors and optimizing energy management.https://ieeexplore.ieee.org/document/10419358/Hydrogen fuel cell tractorsbond graphenergy management strategymodel-in-the-loophard-ware-in-the-loop |
| spellingShingle | Yanying Li Mengnan Liu Yiting Wang Liyou Xu Shenghui Lei Energy Management Optimization and Validation of a Hydrogen Fuel Cell-Powered Agricultural Tractor Based on Hierarchical Dynamic Programming IEEE Access Hydrogen fuel cell tractors bond graph energy management strategy model-in-the-loop hard-ware-in-the-loop |
| title | Energy Management Optimization and Validation of a Hydrogen Fuel Cell-Powered Agricultural Tractor Based on Hierarchical Dynamic Programming |
| title_full | Energy Management Optimization and Validation of a Hydrogen Fuel Cell-Powered Agricultural Tractor Based on Hierarchical Dynamic Programming |
| title_fullStr | Energy Management Optimization and Validation of a Hydrogen Fuel Cell-Powered Agricultural Tractor Based on Hierarchical Dynamic Programming |
| title_full_unstemmed | Energy Management Optimization and Validation of a Hydrogen Fuel Cell-Powered Agricultural Tractor Based on Hierarchical Dynamic Programming |
| title_short | Energy Management Optimization and Validation of a Hydrogen Fuel Cell-Powered Agricultural Tractor Based on Hierarchical Dynamic Programming |
| title_sort | energy management optimization and validation of a hydrogen fuel cell powered agricultural tractor based on hierarchical dynamic programming |
| topic | Hydrogen fuel cell tractors bond graph energy management strategy model-in-the-loop hard-ware-in-the-loop |
| url | https://ieeexplore.ieee.org/document/10419358/ |
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