The ability to define in-field tractor load states offers the potential to better specify and characterize fuel consumption rate for various field operations. For the same field operation, the tractor experiences diverse load demands and corresponding fuel use rates as it maneuvers through straight passes, turns, suspended operation for adjustments, repair and maintenance, and biomass or other material transfer operations. It is challenging to determine the actual fuel rate and load states of agricultural machinery using force prediction models, and hence, some form of in-field data acquisition capability is required. Controller Area Networks (CAN) available on the current model tractors provide engine performance data which can be used to determine tractor load states in field conditions. In this study, CAN message data containing fuel rate, engine speed and percent torque were logged from the tractor's diagnostic port during anhydrous NH3 application, field cultivation and planting operations. Time series and frequency plots of fuel rate and percent torque were generated to evaluate tractor load states. Based on the percent torque, engine speed and rated engine power, actual load on the tractor was calculated in each tractor load state. Anhydrous NH3 application and field cultivation were characterized by three distinct tractor load states (TS-I, TS-II and TS-III) corresponding to idle states, parallel and headland passes, and turns, whereas corn planting was characterized by two load states (TS-I and TS-II): idle, and a combined state with parallel, headland passes and turns. For anhydrous NH3 application and field cultivation at ground speeds of 7.64 km h-1 and 8.68 km h-1, average tractor load per tool and fuel use rate per tool of the implement were found to be 7.21 kW tool-1, 3.28 L h-1tool-1, and 1.31 kW tool-1, 0.64 Lh-1tool-1, respectively. For planting, average tractor load per row and fuel use rate per row were found to be 4.65 kW row-1 and 1.70 L h-1row-1 at a ground speed of 7.04 km h-1..
ASJC Scopus subject areas
- Agronomy and Crop Science
- Computer Science Applications