Research on energy optimization control strategy for parallel hybrid tractor based on AIPSO.
In the research on energy optimization control for parallel hybrid tractors, torque has been identified as a crucial factor influencing the tractor's fuel economy, operational efficiency, and agricultural development. This study focuses on the tractor's overall demand torque as the primary...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0315369 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849324146986582016 |
|---|---|
| author | Xiaohui Liu Yiwei Wu Jingyun Zhang Yifan Zhao Yangming Hu Xianghai Yan |
| author_facet | Xiaohui Liu Yiwei Wu Jingyun Zhang Yifan Zhao Yangming Hu Xianghai Yan |
| author_sort | Xiaohui Liu |
| collection | DOAJ |
| description | In the research on energy optimization control for parallel hybrid tractors, torque has been identified as a crucial factor influencing the tractor's fuel economy, operational efficiency, and agricultural development. This study focuses on the tractor's overall demand torque as the primary research parameter and designs a comprehensive scheme for the parallel hybrid tractor. The study includes the design of power system parameters and the construction of a dynamic model for the entire machine. Based on this, an energy optimization control strategy, termed adaptive immune particle swarm optimization fuzzy control strategy (AIPSOFCS), is proposed. Simulation analysis is performed using representative plowing conditions, and AIPSOFCS is compared with the power follow control strategy (PFCS) and fuzzy control strategy (FCS). The results indicate that AIPSOFCS demonstrates higher fuel economy and operational efficiency compared to PFCS and FCS. In the plowing conditions, the fuel economy of AIPSOFCS is reduced by 8.45% and 2.93% compared to PFCS and FCS, respectively. In the rotary tillage conditions, the fuel economy of AIPSOFCS is reduced by 2.40% and 4.07% compared to PFCS and FCS, respectively. Finally, hardware-in-the-loop (HIL) testing of the controller confirms the effectiveness of AIPSOFCS. This research is of significant importance for enhancing the fuel economy and operational efficiency of parallel hybrid tractors and provides theoretical support and reference for the future. |
| format | Article |
| id | doaj-art-70722e5f70934aeea84b7f1526fdb36e |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-70722e5f70934aeea84b7f1526fdb36e2025-08-20T03:48:47ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01202e031536910.1371/journal.pone.0315369Research on energy optimization control strategy for parallel hybrid tractor based on AIPSO.Xiaohui LiuYiwei WuJingyun ZhangYifan ZhaoYangming HuXianghai YanIn the research on energy optimization control for parallel hybrid tractors, torque has been identified as a crucial factor influencing the tractor's fuel economy, operational efficiency, and agricultural development. This study focuses on the tractor's overall demand torque as the primary research parameter and designs a comprehensive scheme for the parallel hybrid tractor. The study includes the design of power system parameters and the construction of a dynamic model for the entire machine. Based on this, an energy optimization control strategy, termed adaptive immune particle swarm optimization fuzzy control strategy (AIPSOFCS), is proposed. Simulation analysis is performed using representative plowing conditions, and AIPSOFCS is compared with the power follow control strategy (PFCS) and fuzzy control strategy (FCS). The results indicate that AIPSOFCS demonstrates higher fuel economy and operational efficiency compared to PFCS and FCS. In the plowing conditions, the fuel economy of AIPSOFCS is reduced by 8.45% and 2.93% compared to PFCS and FCS, respectively. In the rotary tillage conditions, the fuel economy of AIPSOFCS is reduced by 2.40% and 4.07% compared to PFCS and FCS, respectively. Finally, hardware-in-the-loop (HIL) testing of the controller confirms the effectiveness of AIPSOFCS. This research is of significant importance for enhancing the fuel economy and operational efficiency of parallel hybrid tractors and provides theoretical support and reference for the future.https://doi.org/10.1371/journal.pone.0315369 |
| spellingShingle | Xiaohui Liu Yiwei Wu Jingyun Zhang Yifan Zhao Yangming Hu Xianghai Yan Research on energy optimization control strategy for parallel hybrid tractor based on AIPSO. PLoS ONE |
| title | Research on energy optimization control strategy for parallel hybrid tractor based on AIPSO. |
| title_full | Research on energy optimization control strategy for parallel hybrid tractor based on AIPSO. |
| title_fullStr | Research on energy optimization control strategy for parallel hybrid tractor based on AIPSO. |
| title_full_unstemmed | Research on energy optimization control strategy for parallel hybrid tractor based on AIPSO. |
| title_short | Research on energy optimization control strategy for parallel hybrid tractor based on AIPSO. |
| title_sort | research on energy optimization control strategy for parallel hybrid tractor based on aipso |
| url | https://doi.org/10.1371/journal.pone.0315369 |
| work_keys_str_mv | AT xiaohuiliu researchonenergyoptimizationcontrolstrategyforparallelhybridtractorbasedonaipso AT yiweiwu researchonenergyoptimizationcontrolstrategyforparallelhybridtractorbasedonaipso AT jingyunzhang researchonenergyoptimizationcontrolstrategyforparallelhybridtractorbasedonaipso AT yifanzhao researchonenergyoptimizationcontrolstrategyforparallelhybridtractorbasedonaipso AT yangminghu researchonenergyoptimizationcontrolstrategyforparallelhybridtractorbasedonaipso AT xianghaiyan researchonenergyoptimizationcontrolstrategyforparallelhybridtractorbasedonaipso |