Study and Verification of a Fuzzy-Following Energy Management Strategy for Hybrid Tractors
Tractors operate under varying and unpredictable conditions, making energy management strategies insufficient for maintaining system power dynamics, which often leads to reduced traction power and overall efficiency. To overcome this challenge, a fuzzy-following energy management strategy was develo...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | World Electric Vehicle Journal |
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| Online Access: | https://www.mdpi.com/2032-6653/16/1/18 |
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| author | Xin Zhao Guangpeng Zhang Jianhua Wang Zhanpo Xue Mengnan Liu Yibin Liu |
| author_facet | Xin Zhao Guangpeng Zhang Jianhua Wang Zhanpo Xue Mengnan Liu Yibin Liu |
| author_sort | Xin Zhao |
| collection | DOAJ |
| description | Tractors operate under varying and unpredictable conditions, making energy management strategies insufficient for maintaining system power dynamics, which often leads to reduced traction power and overall efficiency. To overcome this challenge, a fuzzy-following energy management strategy was developed. This approach utilizes fuzzy control based on energy following to optimize the tractor’s energy output, ensuring more stable power delivery. A target tractor model was constructed using CRUISE, and joint simulations were carried out via the CRUISE-Simulink interface. The results demonstrated that the fuzzy-following strategy stabilized the battery’s state of charge (SoC) and improved fuel economy. The strategy was implemented for controlling a hybrid tractor, and its effectiveness and stability were validated through drivetrain system tests and real vehicle trials under light load, plowing, and power harrowing conditions, successfully achieving power balance under these diverse operating scenarios. Comparative tests between the hybrid tractor using the fuzzy-following strategy and a powershift tractor revealed that the hybrid tractor exhibited superior plowing efficiency and fuel economy under plowing and power-harrowing conditions. |
| format | Article |
| id | doaj-art-e6d0fffb4c8544deb40d850664522733 |
| institution | Kabale University |
| issn | 2032-6653 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj-art-e6d0fffb4c8544deb40d8506645227332025-01-24T13:52:46ZengMDPI AGWorld Electric Vehicle Journal2032-66532024-12-011611810.3390/wevj16010018Study and Verification of a Fuzzy-Following Energy Management Strategy for Hybrid TractorsXin Zhao0Guangpeng Zhang1Jianhua Wang2Zhanpo Xue3Mengnan Liu4Yibin Liu5School of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an 710048, ChinaSchool of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an 710048, ChinaState Key Laboratory of Intelligent Agricultural Power Equipment, Luoyang 471039, ChinaState Key Laboratory of Intelligent Agricultural Power Equipment, Luoyang 471039, ChinaState Key Laboratory of Intelligent Agricultural Power Equipment, Luoyang 471039, ChinaState Key Laboratory of Intelligent Agricultural Power Equipment, Luoyang 471039, ChinaTractors operate under varying and unpredictable conditions, making energy management strategies insufficient for maintaining system power dynamics, which often leads to reduced traction power and overall efficiency. To overcome this challenge, a fuzzy-following energy management strategy was developed. This approach utilizes fuzzy control based on energy following to optimize the tractor’s energy output, ensuring more stable power delivery. A target tractor model was constructed using CRUISE, and joint simulations were carried out via the CRUISE-Simulink interface. The results demonstrated that the fuzzy-following strategy stabilized the battery’s state of charge (SoC) and improved fuel economy. The strategy was implemented for controlling a hybrid tractor, and its effectiveness and stability were validated through drivetrain system tests and real vehicle trials under light load, plowing, and power harrowing conditions, successfully achieving power balance under these diverse operating scenarios. Comparative tests between the hybrid tractor using the fuzzy-following strategy and a powershift tractor revealed that the hybrid tractor exhibited superior plowing efficiency and fuel economy under plowing and power-harrowing conditions.https://www.mdpi.com/2032-6653/16/1/18fuzzy-following strategyexperimental verificationhybrid tractor |
| spellingShingle | Xin Zhao Guangpeng Zhang Jianhua Wang Zhanpo Xue Mengnan Liu Yibin Liu Study and Verification of a Fuzzy-Following Energy Management Strategy for Hybrid Tractors World Electric Vehicle Journal fuzzy-following strategy experimental verification hybrid tractor |
| title | Study and Verification of a Fuzzy-Following Energy Management Strategy for Hybrid Tractors |
| title_full | Study and Verification of a Fuzzy-Following Energy Management Strategy for Hybrid Tractors |
| title_fullStr | Study and Verification of a Fuzzy-Following Energy Management Strategy for Hybrid Tractors |
| title_full_unstemmed | Study and Verification of a Fuzzy-Following Energy Management Strategy for Hybrid Tractors |
| title_short | Study and Verification of a Fuzzy-Following Energy Management Strategy for Hybrid Tractors |
| title_sort | study and verification of a fuzzy following energy management strategy for hybrid tractors |
| topic | fuzzy-following strategy experimental verification hybrid tractor |
| url | https://www.mdpi.com/2032-6653/16/1/18 |
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