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Model-based Range Prediction for Electric Cars and Trucks under Real-World Conditions

DOI zum Zitieren der Version auf EPub Bayreuth:
URN to cite this document: urn:nbn:de:bvb:703-epub-6541-7

Title data

Dollinger, Manfred ; Fischerauer, Gerhard:
Model-based Range Prediction for Electric Cars and Trucks under Real-World Conditions.
In: Energies. Vol. 14 (September 2021) Issue 18 . - No. 5804.
ISSN 1996-1073
DOI der Verlagsversion:

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The further development of electric mobility requires major scientific efforts to obtain reliable data for vehicle and drive development. Practical experience has repeatedly shown that vehicle data sheets do not contain realistic consumption and range figures. Since the fear of low range is a significant obstacle to the acceptance of electric mobility, a reliable database can provide developers with additional insights and create confidence among vehicle users. This study presents a detailed, yet easy-to-implement and modular physical model for both passenger and commercial battery electric vehicles. The model takes consumption-relevant parameters, such as seasonal influences, terrain character, and driving behavior, into account. Without any a posteriori parameter adjustments, an excellent agreement with known field data and other experimental observations is achieved. This validation conveys much credibility to model predictions regarding the real-world impact on energy consumption and cruising range in standardized driving cycles. Some of the conclusions, almost impossible to obtain experimentally, are that winter conditions and a hilly terrain each reduce the range by 7–9%, and aggressive driving reduces the range by up to 20%. The quantitative results also reveal the important contributions of recuperation and rolling resistance towards the overall energy budget.

Further data

Item Type: Article in a journal
Keywords: Battery electric vehicle; BEV; electric truck; cruising range; real-world conditions; physical model; range prediction; consumption shares; recuperation; rolling resistance
DDC Subjects: 600 Technology, medicine, applied sciences > 620 Engineering
Institutions of the University: Faculties > Faculty of Engineering Science > Chair Measurement and Control Technology
Profile Fields > Emerging Fields > Energy Research and Energy Technology
Research Institutions > Research Units > Zentrum für Energietechnik - ZET
Faculties > Faculty of Engineering Science
Profile Fields
Profile Fields > Emerging Fields
Research Institutions
Research Institutions > Research Units
Language: English
Originates at UBT: Yes
URN: urn:nbn:de:bvb:703-epub-6541-7
Date Deposited: 25 Jul 2022 09:00
Last Modified: 25 Jul 2022 09:00


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