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Parameter Estimation of Electric Vehicles for Improved Range Prediction
Date
2021-01-01
Author
Saglam, Berkay
Bostancı, Emine
Göl, Murat
Metadata
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This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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© 2021 IEEE.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.
Subject Keywords
parameter estimation
,
electric vehicle
,
power consumption
,
state estimation
,
powertrain model
,
electric vehicle
,
parameter estimation
,
power consumption
,
powertrain model
,
state estimation
URI
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85123938483&origin=inward
https://hdl.handle.net/11511/98854
DOI
https://doi.org/10.1109/isgteurope52324.2021.9640048
Conference Name
11th IEEE PES Innovative Smart Grid Technologies Europe, ISGT Europe 2021
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
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B. Saglam, E. Bostancı, and M. Göl, “Parameter Estimation of Electric Vehicles for Improved Range Prediction,” presented at the 11th IEEE PES Innovative Smart Grid Technologies Europe, ISGT Europe 2021, Espoo, Finlandiya, 2021, Accessed: 00, 2022. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85123938483&origin=inward.
