In this study, a semi-active suspension based on a hydro-pneumatic mechanism was designed to minimize the ride vibration using a suspension control algorithm. The performance of the algorithm was critical for controlling the characteristics of the target tractor. A linear-quadratic-Gaussian (LQG) optimal control algorithm was designed as a semi-active suspension control algorithm. The plant model for developing this algorithm was based on the parameters of an actual tractor. The rear suspension deflection was represented by a Kalman-filter-based state observer feedback to estimate the state variables that were difficult to measure. The designed state observer of the LQG controller was validated in terms of an accuracy index. The estimated vertical velocity and acceleration accuracies of the cabin were 83% and 79%, respectively. The performance of the designed controller was validated in terms of a performance index by comparing the performance of a tractor equipped with a rear rubber mount with that of one equipped with a semi-active suspension. The peak and root-mean-square values of the vertical acceleration of the cabin were reduced by up to 48.97% and 47.06%, respectively. This study could serve as a basis for the application of the control algorithm to systems with similar characteristics, thereby reducing system costs.

A series of ethylene vinyl acetate (EVA) copolymers were blended with aromatic hydrocarbon resins in the molten state in various ratios and possible relations between viscoelastic and adhesion prop...

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.

In gear design, gear performance metrics such as safety factors for tooth root stress and surface durability, peak-to-peak static transmission error (PPSTE), efficiency, mass, and volume are considered. They are calculated by the geometric parameters of gear macro- and micro-geometry, and manufacturing errors related to gear geometry significantly affect gear performance. However, previous studies have only focused on the micro-geometry errors. In this study, Monte Carlo-type robustness analysis was performed considering the manufacturing errors for tooth thickness, tip diameter, and center distance. Gear performance metrics except PPSTE were calculated based on the international standards and geometric characteristics. PPSTE was evaluated analytically due to lack of standards. When the errors were considered, two gear pairs with the safety factors satisfying the design requirements and similar performance for PPSTE, efficiency, mass, and volume showed different gear performances. There were many samples in gear pair 1 that could not satisfy the design requirements of safety factors, and gear pair 2 had the robustness of PPSTE not only at the specific torque but also with wide torque range when compared to gear pair 1. These results imply that considering the gear macro-geometry errors and robustness of PPSTE is significantly important when designing gears.

As the demand for agricultural electric vehicles increases, it is becoming important to conduct noise reduction in consideration of the characteristics of an electric powertrain. This study was conducted to optimize the shape design of gearbox housing for radiated noise reduction of an agricultural electric vehicle gearbox. The noise and vibration of the gearbox were measured considering the noise characteristics of the electric vehicle gearbox, which radiates high-frequency pure tone noise. The main noise source radiated by the structural vibration of the gearbox housing was identified and considered when modeling the loading conditions in the numerical analysis. To improve the reliability, the finite element (FE) model was updated and validated. Internal machine elements were modeled as a substructure through a reduced-order modeling method to reduce the computing time and apply a constant gear excitation force. The weak areas of structure were determined and it was used as the design area for optimization. The topology optimization technique was used to reduce the equivalent radiated power (ERP) which was used as an indicator of radiated noise level. The maximum value of the ERP decreased under all operating conditions at the rated speed.