TY - JOUR
T1 - Prognosis of the energy and instantaneous power consumption in electric vehicles enhanced by visual terrain classification
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/Magister Nacional/2018 - 22170689.
Funding Information:
This research was founded by CONICYT Fondecyt grant 1171431 , CONICYT FB0008 and CONICYT-PFCHA/Magister Nacional/2018 - 22170689.
Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2019/9
Y1 - 2019/9
N2 - The use of electric vehicles (EVs) has been viewed as a potential solution to reduce the oil dependence in transportation. Nevertheless, the performance of the EV changes according to the nature and characteristics of the terrain. This work focuses in modelling the instantaneous power consumption (IPC) of an EV as it traverses through different types of terrains, classified using an artificial vision system. The EV is sensorized with voltage and current sensors, accurate real time kinematics device, an artificial vision system and a real time processing unit, to perform field tests. To see the advantages of using terrain information for energy prognosis in EVs, we compared our proposal with the information provided by the manufacturer and previously published approaches. Our system showed to be up to 95% more accurate when tested over clay, gravel, pavement and grass in both short term and long term trials, and it does not need of a complete knowledge of the system's model.
AB - The use of electric vehicles (EVs) has been viewed as a potential solution to reduce the oil dependence in transportation. Nevertheless, the performance of the EV changes according to the nature and characteristics of the terrain. This work focuses in modelling the instantaneous power consumption (IPC) of an EV as it traverses through different types of terrains, classified using an artificial vision system. The EV is sensorized with voltage and current sensors, accurate real time kinematics device, an artificial vision system and a real time processing unit, to perform field tests. To see the advantages of using terrain information for energy prognosis in EVs, we compared our proposal with the information provided by the manufacturer and previously published approaches. Our system showed to be up to 95% more accurate when tested over clay, gravel, pavement and grass in both short term and long term trials, and it does not need of a complete knowledge of the system's model.
KW - Electric vehicles
KW - Instantaneous power consumption
KW - Real time processing
KW - Terrain modelling
UR - http://www.scopus.com/inward/record.url?scp=85068848121&partnerID=8YFLogxK
U2 - 10.1016/j.compeleceng.2019.07.003
DO - 10.1016/j.compeleceng.2019.07.003
M3 - Article
AN - SCOPUS:85068848121
SN - 0045-7906
VL - 78
SP - 120
EP - 131
JO - Computers and Electrical Engineering
JF - Computers and Electrical Engineering
ER -