农业负载周期:从记录的GNSS和CAN总线数据中获取拖拉机任务概况
Korbinian Götz1, Andrew Kusuma1, Adrian Dörfler1
1TUM School of Engineering and Design, Chair of Automotive Technology, Technical University of Munich, Boltzmannstr. 15, Garching, 85748, Germany.
Data in brief
|April 14, 2025
概括
电气化农用拖拉机可以减少排放. 这项研究收集了一年的真实世界拖拉机数据,以确定电气化要求,为开发电动拖拉机创建了一个全面的数据集.
科学领域:
- 农业工程 农业工程
- 可再生能源系统可再生能源系统
- 可持续农业 可持续农业
背景情况:
- 由于化石燃料的燃烧,农业机械是温室气体排放的重要来源.
- 电气化拖拉机是一个有希望的解决方案,通过利用可再生能源来减少排放.
- 农业拖拉机缺乏标准化的负载周期,阻碍了电动拖拉机要求的发展.
研究的目的:
- 收集农用拖拉机的高分辨率操作数据,以确定电气化要求.
- 为开发和模拟电动拖拉机创建一个全面的,开放的数据集.
- 与汽车应用相比,解决农业拖拉机使用模式的变化.
主要方法:
- 五台拖拉机 (77-240千瓦) 配备了高分辨率的GNSS记录器,并在一年内收集了CAN总线数据 (J1939发动机总线和ISOBUS).
- 记录了862小时的拖拉机运行数据,包括发动机和负载参数,辅助功率和GNSS信息.
- 用拖拉机模型丰富了数据集,并实施了用于详细分析现实实地作业的信息.
主要成果:
- 创建了最全面的开放数据集之一,用于高分辨率的农业拖拉机运行数据.
- 该数据集在各种农业田地条件下捕获了各种负载和使用信息.
- 为开发电动拖拉机和农业负载周期提供了必要的输入数据.
结论:
- 收集的数据集对于模拟拖拉机电气化和构建标准化农业负载周期至关重要.
- 这项研究支持电动拖拉机技术和可持续农业实践的进步.
- 该数据集可以在农业过程建模,生产指标分析和自主路径规划方面进一步应用.
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