Dr. Joe D. Luck
Dr. Santosh K. Pitla
Date of this Version
Stoll, G.P. (2019). Predicting Agricultural Implement Hydraulic Power Demand Using Synchronized Controller Area Network and Ancillary Sensor Data (Master's thesis). University of Nebraska-Lincoln, Lincoln, NE
As agricultural implement designs have progressed in recent years, there has been an increase in hydraulic power demand from the tractor. Current power estimation standards do not accurately estimate hydraulic power demand for implements designed with higher hydraulic power requirements. Several stakeholders, including agricultural producers, tractor and implement manufacturers, and government agencies would benefit from accurate published data on these power requirements.
While an increasing amount of operational data available on the Controller Area Network (CAN) of tractors has assisted researchers in more easily obtaining machinery performance data, hydraulic control valve flow rate and pressure measurements are not currently publically available on modern tractor CAN systems. Thus, this study attempted to determine the minimal amount of additional instrumentation needed to measure these parameters.
Results validated that CAN-reported valve spool position could successfully predict flow rate when the tractor’s pump was capable of producing a sufficient flow rate to satisfy the overall tractor and implement flow demand. However, this message failed to predict flow rate in all valves whenever the pump became flow-limited due to circumstances including multiple valves actuated simultaneously, low engine speeds, or high circuit pressure requirements. A customized orifice flowmeter was found to be a compact, cost-effective solution to estimate flow rate under such flow-limited pump conditions. A flow rate prediction method was tested incorporating temperature compensation using CAN-reported valve spool position in flow-sufficient conditions and the orifice flowmeter in flow-limited conditions. Mean absolute errors below 3 Lpm (5.5% MAPE) were observed between the predicted flow rate and measurements from a laboratory-based turbine flowmeter for various simulated tests.
Once determining the flow rate prediction methodology was acceptable, hydraulic power requirements were analyzed between two no-till air drills utilized for small grain planting operations in Eastern Nebraska. To allow a CAN data logger to serve as the sole data acquisition system, a customized instrumentation integration device, the Sensor CAN Gateway (SCANGate), was developed and used to publish all added pressure sensor data onto the CAN bus. In addition to quantifying both planters’ hydraulic power requirements, comparisons were made between the time and fuel requirements per area for both operations.
Advisors: Joe D. Luck & Santosh K. Pitla