Prognosis of the energy and instantaneous power consumption in electric vehicles enhanced by visual terrain classification. (September 2019)

• Record Type: Journal Article
• Authors: Romero Schmidt, Javier; Auat Cheein, Fernando
• Is Part Of: Computers & electrical engineering. Volume 78(2019)
• Page Start: 120
• Page End: 131
• Publication Date: 2019-09
• Subjects: Electric vehicles -- Terrain modelling -- Instantaneous power consumption -- Real time processing; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2019.07.003
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: 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.