This study was conducted to develop a load-sensitive engine speed control system to maximize the fuel efficiency of an agricultural tractor. The engine speed controller was developed through a model-based design approach using a tractor simulation model. The simulated engine speed and torque values were measured with an average error range of 1.4–4.9% compared to results obtained from field experiments. Using the tractor model, the gain parameters of the proportional–integral (PI) controller were optimized under the step, ramp, and actual load conditions. The simulation results using the actual load showed that the engine speed could be adjusted to within 2–3% of the desired value using the proposed engine speed controller. The throttle control system was constructed using four parts of a tractor engine, a microprocessor with an engine speed control algorithm, a throttle actuator, and a data acquisition system. Using the developed system, the operating engine speed values showed an average 1.17 % error compared to the desired engine speed. Three fuel efficiency parameters were used for evaluating the fuel-saving performance of the control system: specific volumetric fuel consumption (SVFC), fuel consumption per tilled area (FCA), and fuel consumption per work hour (FC). The values for SVFC, FCA, and FC obtained from the engine speed control system during plowing operations were 23.03–57.87%, 4.11–42.06%, and −7.24–38.48%, respectively, showing an improvement over the same operations without the control system.

Measurement of stiffness and damping coefficient of rubber tractor tires using dynamic cleat test based on point contact model

Composite work tools have many components, and complex shapes when compared to standard tools such as rotaries and plows. In addition, the component durability for the tools is critical because the load varies severely according to the soil conditions. This study predicts the fatigue life of the hub bearing in composite work tooling. The loads acting on the tools were measured based on field tests, and the loads acting on the hub bearing were derived using the load reconstruction method. The static safety factor and fatigue life of the hub bearing, loads, and contact stress acting on the inner and outer raceways and presence of truncation were analytically predicted based on the derived loads. The fatigue life of the bearing changed depending on the preload amount of the hub bearing. The bearing life was more than 3000 h for preloads of less than 40 μm, which satisfied the target life of 1200 h. The load acting on the inner and outer raceways of the bearing decreased and then increased as the preload amount of the bearing rose. The bearing contact area, maximum contact stress, and number of balls increased as the load applied to the hub bearing rose. The fatigue life, load, contact stress, and static safety factor of the hub bearing met all requirements, and no truncation occurred on the inner and outer raceways of the bearing. The test verified the achievement of the target life of 1200 h and confirmed that there was no breakage, cracking, or deformation of the bearing.