Abstract
Considering the fuel consumption and soil compaction, optimization of the performance of tractors is crucial for modern agricultural practices. The tractive performance is influenced by many factors, making it difficult to be modeled. In this work, the traction force and tractive efficiency of a low-power tractor, as affected by soil coefficient, vertical load, horizontal deformation, soil compaction, and soil moisture, were studied. The optimal work of a tractor is a compromise between the maximum traction force and the maximum tractive efficiency. Optimizing these factors is complex and requires accurate models. To this end, the performances of soft computing approaches, including neural networks, genetic algorithms, and adaptive network fuzzy inference system, were evaluated. The optimal performance was realized by neural networks trained by backpropagation as well as backpropagation combined with a genetic algorithm, with a coefficient of determination of 0.955 for the traction force and 0.954 for the tractive efficiency. Based on models with the best accuracy, a sensitivity analysis was performed. The results showed that the traction performance is mainly influenced by the soil type; nevertheless, the vertical load and soil moisture also exhibited a relatively strong influence.
Highlights
A mathematical modeling of the soil-tire interaction process can help improve the tractor design and minimize fuel consumption
An Artificial neural networks (ANNs)-genetic algorithm (GA) has been used to model the power of agricultural tractors as a function of the wheel load, slip, and speed [14] and to model the dynamic characteristics of a tractor on sloping terrain [15]. Another hybrid method used for modeling complex relationships in the agricultural field is the adaptive network fuzzy inference system (ANFIS), which combines the advantages of neural networks and fuzzy logic [16, 17]
E objective of this study was to develop ANN, ANN trained by GA, ANN trained by backpropagation (BP) and GA, and ANFIS models to estimate the traction force or tractive efficiency of a low-power tractor as a function of the soil coefficient (which is indicative of soil texture as defined in equation (1)), vertical load, horizontal deformation, soil compaction, and soil moisture
Summary
E tests were conducted on the following types of soil: sand, fine sandy loam, sandy loam, and silty clay loam. Low-power tractors are usually equipped with wheels having a rim diameter of 10 inches On this type of rim, tires with different overall widths can be mounted, e.g., 4.00–10, 4.50–10, and 5.00–10. In the case of highly compact soils, a 4.00–10 tire would be most beneficial, as the narrow tread blocks will be able to extend deeper into the soil ensuring an optimum traction force. E average vertical load recommended for low-power tractors is in the range of 800–900 N. e aim of this research was to develop mathematical models of the relationships under study, which can subsequently be used for optimizing the selected operating parameters in order to minimize soil compaction. 1.25 field water capacity Field water capacity Beginning of plant growth inhibition Strong inhibition of plant growth
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