TY - JOUR
T1 - Assessment of power consumption of electric machinery in agricultural tasks for enhancing the route planning problem
AU - Romero Schmidt, Javier
AU - Auat Cheein, Fernando
N1 - Funding Information:
This research was founded by CONICYT Fondecyt grant 1171431 , CONICYT FB0008 and CONICYT-PFCHA/MagísterNacional/2018-22170689.
Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2019/8
Y1 - 2019/8
N2 - In field operations, machinery is subject to resource restrictions that lead to a significant number of approaches to make it more efficient. Operational times, costs and manoeuvres, machinery effort, among others, are often considered for route planning strategies. In particular, the route planning problem (RPP) has been widely studied for both single and fleet of agricultural machinery performing a previously assigned task, considering the above constraints. However, such a study is limited to engine combustion of agricultural machinery. With electrically powered vehicles, it is yet to be determined how to estimate the power consumption and the power requirements for the route planning problem, to ensure that the vehicle will be able to complete the task. In electric machinery, the power is associated with the rolling resistance, the aerodynamic resistance of the vehicle, its mass, the terramechanic relationship between the wheel and the terrain, among other factors. In this work, it is analytically presented the estimation of the instantaneous power consumption (IPC) of an electric machinery in agricultural tasks, given a previously defined route, according to the nature of the terrain that it is traversing; and it is latter empirically validated in the field. The experiments performed in an avocado grove show a root mean square error of 60 kW in the estimation of the IPC, against 900 kW when using manufacturer information. The results shown herein can be used for further enhancing the route planning problem and the decision making process of the farmer, by adding power restriction (and thus, energy usage) of electric vehicles to the RPP.
AB - In field operations, machinery is subject to resource restrictions that lead to a significant number of approaches to make it more efficient. Operational times, costs and manoeuvres, machinery effort, among others, are often considered for route planning strategies. In particular, the route planning problem (RPP) has been widely studied for both single and fleet of agricultural machinery performing a previously assigned task, considering the above constraints. However, such a study is limited to engine combustion of agricultural machinery. With electrically powered vehicles, it is yet to be determined how to estimate the power consumption and the power requirements for the route planning problem, to ensure that the vehicle will be able to complete the task. In electric machinery, the power is associated with the rolling resistance, the aerodynamic resistance of the vehicle, its mass, the terramechanic relationship between the wheel and the terrain, among other factors. In this work, it is analytically presented the estimation of the instantaneous power consumption (IPC) of an electric machinery in agricultural tasks, given a previously defined route, according to the nature of the terrain that it is traversing; and it is latter empirically validated in the field. The experiments performed in an avocado grove show a root mean square error of 60 kW in the estimation of the IPC, against 900 kW when using manufacturer information. The results shown herein can be used for further enhancing the route planning problem and the decision making process of the farmer, by adding power restriction (and thus, energy usage) of electric vehicles to the RPP.
KW - Electric agricultural machinery
KW - Energy management
KW - Power assessment
UR - http://www.scopus.com/inward/record.url?scp=85068369426&partnerID=8YFLogxK
U2 - 10.1016/j.compag.2019.104868
DO - 10.1016/j.compag.2019.104868
M3 - Article
AN - SCOPUS:85068369426
SN - 0168-1699
VL - 163
JO - Computers and Electronics in Agriculture
JF - Computers and Electronics in Agriculture
M1 - 104868
ER -