Energy Savings from Optimised In-Field Route Planning for Agricultural Machinery

Efthymios Rodias, Remigio Berruto, Patrizia Busato, Dionysis Bochtis, Claus Grøn Sørensen and Kun Zhou
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Efthymios Rodias: Department of Agriculture, Forestry and Food Science (DISAFA), Faculty of Agriculture, University of Turin, Largo Braccini 2, 10095 Grugliasco, Italy
Remigio Berruto: Department of Agriculture, Forestry and Food Science (DISAFA), Faculty of Agriculture, University of Turin, Largo Braccini 2, 10095 Grugliasco, Italy
Patrizia Busato: Department of Agriculture, Forestry and Food Science (DISAFA), Faculty of Agriculture, University of Turin, Largo Braccini 2, 10095 Grugliasco, Italy
Dionysis Bochtis: Institute for Bio-economy and Agri-Technology (IBO), Centre for Research & Technology—Hellas (CERTH), 57001 Thessaloniki, Greece
Claus Grøn Sørensen: Department of Engineering, Faculty Science and Technology, Aarhus University, 8000 Aarhus, Denmark
Kun Zhou: Department of Engineering, Faculty Science and Technology, Aarhus University, 8000 Aarhus, Denmark

Sustainability, 2017, vol. 9, issue 11, 1-13

Abstract: Various types of sensors technologies, such as machine vision and global positioning system (GPS) have been implemented in navigation of agricultural vehicles. Automated navigation systems have proved the potential for the execution of optimised route plans for field area coverage. This paper presents an assessment of the reduction of the energy requirements derived from the implementation of optimised field area coverage planning. The assessment regards the analysis of the energy requirements and the comparison between the non-optimised and optimised plans for field area coverage in the whole sequence of operations required in two different cropping systems: Miscanthus and Switchgrass production. An algorithmic approach for the simulation of the executed field operations by following both non-optimised and optimised field-work patterns was developed. As a result, the corresponding time requirements were estimated as the basis of the subsequent energy cost analysis. Based on the results, the optimised routes reduce the fuel energy consumption up to 8%, the embodied energy consumption up to 7%, and the total energy consumption from 3% up to 8%.

Keywords: auto-steering systems; area coverage; operations planning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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