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Modeling of Tractor Fuel Consumption

Author

Listed:
  • Bronisław Andrzej Kolator

    (Faculty of Technical Sciences, University of Warmia and Mazury in Olsztyn, Oczapowskiego 11 Street, 10-719 Olsztyn, Poland)

Abstract

In this paper, the energy diagnostic of tractor performance consists in evaluating the energy (fuel consumption per hectare—dm 3 ha −1 ) for a given agricultural operation and in combining it with working capacity, also called productivity (area productivity—ha h −1 ). One of the methods of solving this problem is the identification of the functioning process of the machine unit. A model of the process of the machine unit performance was developed, considering the operation of the rear linkage system of the implement with the force control adjustment system. In order to analyze the system, a mathematical model of the system function was built: tractor-implement-soil, defining the physical connections and interdependencies between the individual subsystems of the system. Based on this model, a simulation model was developed and implemented in the Matlab/Simulink environment. The Simulink package was used to test the performance of the machine set. The efficiency indicators according to the adopted criteria were calculated in the evaluation block. To evaluate the process, the technical and operational parameters of the tractor, the type and parameters of the tool, and soil properties were taken into account. The results of simulation studies obtained on a validated model are consistent with experimental data from appropriate soil conditions.

Suggested Citation

  • Bronisław Andrzej Kolator, 2021. "Modeling of Tractor Fuel Consumption," Energies, MDPI, vol. 14(8), pages 1-15, April.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:8:p:2300-:d:539158
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    References listed on IDEAS

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    1. Baogang Li & Dongye Sun & Minghui Hu & Junlong Liu, 2018. "Research on Economic Comprehensive Control Strategies of Tractor-Planter Combinations in Planting, Including Gear-Shift and Cruise Control," Energies, MDPI, vol. 11(3), pages 1-21, March.
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    Cited by:

    1. Hamid Jalilnezhad & Yousef Abbaspour-Gilandeh & Vali Rasooli-Sharabiani & Aref Mardani & José Luis Hernández-Hernández & José Antonio Montero-Valverde & Mario Hernández-Hernández, 2023. "Use of a Convolutional Neural Network for Predicting Fuel Consumption of an Agricultural Tractor," Resources, MDPI, vol. 12(4), pages 1-14, March.

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