A Model-Driven Approach for Estimating the Energy Performance of an Electric Vehicle Used as a Taxi in an Intermediate Andean City

Jairo Castillo-Calderón, Daniel Cordero-Moreno and Emilio Larrodé Pellicer ()
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Jairo Castillo-Calderón: PhD Program in Mechanical Engineering, University of Zaragoza, C. de Pedro Cerbuna, 12, 50009 Zaragoza, Spain
Daniel Cordero-Moreno: Faculty of Science and Technology, Universidad del Azuay, Av. 24 de Mayo 7-77, Cuenca 010204, Ecuador
Emilio Larrodé Pellicer: Department of Mechanical Engineering, University of Zaragoza, C. de Pedro Cerbuna, 12, 50009 Zaragoza, Spain

Energies, 2024, vol. 17, issue 23, 1-23

Abstract: Regarding the decision to opt for vehicles with electric propulsion systems to achieve a sustainable future, much research has focused on the electrification of passenger cars, since this class of vehicles is the largest contributor of greenhouse gas emissions in the transportation sector. The purpose of this paper is to assess the energy performance of an electric vehicle used as a taxi in Loja, Ecuador, an intermediate Andean city, using a model-driven approach. Data acquisition was performed through the OBDII port of the KIA SOUL EV for 24 days and the variable mass of the vehicle was recorded as a function of the number of passengers; the effects of road gradient were also considered. The energy performance of the vehicle was simulated by developing an analytical model in MATLAB/Simulink. An average measured battery performance of 8.49 ± 1.4 km/kWh per day was obtained, where the actual energy regenerated was 31.2 ± 1.5%. To validate the proposed model, the results of the daily energy performance estimated with the simulation were compared with those measured in real driving conditions. The results demonstrated a Pearson correlation coefficient of 0.93, indicating a strong positive linear dependence between the variables. In addition, a coefficient of determination of 0.86 and a mean absolute percentage error of 3.35% were obtained, suggesting that the model has a satisfactory predictive capacity for energy performance.

Keywords: electric taxi; energy performance; model-driven approach; real driving conditions (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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