Full text
|
PDF (Artículo Tractor PT en Computers and Electronics)
- Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (1MB) | Preview |
Linares Anegón, Pilar and Catalán Mogorrón, Heliodoro Fco. and Mendez Fuentes, Valeriano (2007). Tractor PT: A traction prediction software for agricultural tractor. "Computers and Electronics in Agriculture", v. 60 (n. 2); pp. 289-295. ISSN 0168-1699.
Title: | Tractor PT: A traction prediction software for agricultural tractor |
---|---|
Author/s: |
|
Item Type: | Article |
Título de Revista/Publicación: | Computers and Electronics in Agriculture |
Date: | July 2007 |
ISSN: | 0168-1699 |
Volume: | 60 |
Subjects: | |
Freetext Keywords: | Traction prediction; Tractor performance; Simulation; Visual programming |
Faculty: | E.T.S.I. Agrónomos (UPM) [antigua denominación] |
Department: | Ingeniería Rural [hasta 2014] |
Creative Commons Licenses: | Recognition - Non commercial |
|
PDF (Artículo Tractor PT en Computers and Electronics)
- Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (1MB) | Preview |
Traction prediction modelling, a key factor in farm tractor design, has been driven by the need to find the answer to this question without having to build physical prototypes. A wide range of theories and their respective algorithms can be used in such predictions. The “Tractors and Tillage” research team at the Polytechnic University of Madrid, which engages, among others, in traction prediction for farm tractors, has developed a series of programs based on the cone index as the parameter representative of the terrain. With the software introduced in the present paper, written in Visual Basic, slip can be predicted in two- and four-wheel drive tractors using any one of four models. It includes databases for tractors, front tyres, rear tyres and working conditions (soil cone index and drawbar pull exerted). The results can be exported in spreadsheet format.
Item ID: | 14786 |
---|---|
DC Identifier: | https://oa.upm.es/14786/ |
OAI Identifier: | oai:oa.upm.es:14786 |
Official URL: | http://www.sciencedirect.com/science/article/pii/S0168169907001743 |
Deposited by: | Profesor Asociado Heliodoro Catalán Mogorrón |
Deposited on: | 08 Apr 2013 10:43 |
Last Modified: | 21 Apr 2016 14:36 |