Parameter Estimation of Electric Vehicles for Improved Range Prediction

Autor: Saglam, Berkay, Bostanci, Emine, Gol, Murat
Rok vydání: 2021
Zdroj: 2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe).
DOI: 10.1109/isgteurope52324.2021.9640048
Popis: In order to improve performance of range estimation of electric vehicles, parameters that affect energy consumption should be determined accurately. This paper presents a parameter estimation methodology for electric vehicles based on least squares method. In this study, the power and angular velocity of wheels are measured from the vehicle directly. In addition to those, the directional velocity data is extracted from the GPS signal, in order to avoid the parameter dependency between the angular velocity and directional velocity. The proposed estimation process is validated by means of a drivetrain simulator, which calculates the power consumption of different types of vehicles.
Databáze: OpenAIRE