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World Electric Vehicle Journal is published by MDPI from Volume 9 issue 1 (2018). Articles in this Issue were published by The World Electric Vehicle Association (WEVA) and its member the European Association for e-Mobility (AVERE), the Electric Drive Transportation Association (EDTA), and the Electric Vehicle Association of Asia Pacific (EVAAP). They are hosted by MDPI on mdpi.com as a courtesy and upon agreement with AVERE.
Open AccessArticle

Electric Vehicle Parameter Identification

1
Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
2
ETH-Zürich, Rämistr. 101, Zürich, CH-8092, Switzerland
3
EMPA, Lerchenfeldstr. 5, St.Gallen, CH-9014, Switzerland
4
Singapore University of Technology and Design, 20 Dover Drive, Singapore,138682
*
Author to whom correspondence should be addressed.
World Electr. Veh. J. 2012, 5(4), 1090-1099; https://doi.org/10.3390/wevj5041090
Published: 28 December 2012
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Abstract

This work describes a method developed to simplify and reduce the cost of the standardized testing required to measure the energy consumption of electric motorcycles before they are sold on the Swiss market. The robust algorithms for estimating four characteristic parameters of electric two-wheelers are based on a linear dynamics model that is considered to be as simple as possible yet as complex as necessary to characterize the vehicles. The model equations are investigated analytically for their ability to find unique solutions, and it is shown that multiple solutions may exist. The algorithms are tested for their ability to handle various data frequencies, levels of noise, and initial guesses. Ultimately it is found that these methods effectively enable the use of simulation models trained on real-world driving to run mandated standard test cycles in place of expensive dynamometer testing to estimate on-road energy use.
Keywords: modelling; simulation; optimization; scooter; standardization modelling; simulation; optimization; scooter; standardization
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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MDPI and ACS Style

Wilhelm, E.; Bornatico, R.; Widmer, R.; Rodgers, L.; Soh, G.S. Electric Vehicle Parameter Identification. World Electr. Veh. J. 2012, 5, 1090-1099.

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