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Real-world CAN bus dataset for agricultural tractor block load cycle characterization
Aykut Dana1, Orkun Özener2, Ali Can Tellioğlu1
1Test and Validation Department, Tümosan Teknoloji Mühendislik Sanayi Ticaret Anonim Şirketi, Istanbul, Türkiye.
Abstract:
Agricultural tractors operate under highly variable load conditions that depend on the field operation, the attached implement, soil characteristics, and operator behavior. Because no standardized, publicly available load cycles exist that reflect this variability, the thermal and durability validation of tractors is commonly performed with boundary-condition scenarios (e.g., continuous maximum torque) that do not represent real field usage. This article presents a dataset of raw, high-resolution Controller Area Network (CAN) bus recordings acquired from an agricultural tractor (Tümosan 81.110 Powershuttle) during real-world operation on fields in the Konya Plain, Türkiye. The tractor was instrumented with a custom-developed CAN-based telemetry system with integrated Global Navigation Satellite System (GNSS) positioning, which continuously streamed the data in real time over a GSM/WebSocket link to a remote server, where the raw frames were decoded into physical values using J1939 signal databases and stored in a time-series database. Approximately one year of operation was recorded at a nominal sampling rate of 10 Hz, covering all activities of the tractor (field work, road transport and idling). From this campaign, the authors filtered the recordings down to the in-field soil tillage segments, which impose the highest engine torque demand, and only these high-load segments are published. The resulting dataset comprises 10 session files, one per worked field, totaling approximately 24.7 h (889,255 samples), so that researchers can focus directly on the most demanding operating condition of the tractor. Each tab-separated value file contains the decoded raw CAN signals. The cyclic alternation between soil-engagement passes under sustained high torque and headland turning events is directly observable in the signals, so that the average duration of working passes under load and of headland turns can be determined. The data can be reused for block load cycle construction, thermal validation on PTO dynamometers, tractor powertrain electrification studies, fuel consumption and productivity analyses and the development of machine state detection and data mining methods for agricultural machinery.
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