- AutorIn
- Anne Voigt Technische Universität Chemnitz#BMW Group
- Dr. Christina KurpiersBMW Group
- Prof. Dr. Stefan BrandenburgTechnische Universität Chemnitz
- Titel
- Examining Drivers’ Mental Models for Energy Efficient Electric Driving
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:ch1-qucosa2-1013125
- Konferenz
- 9th Humanist Virtual Centre of Excellence Conference 2025. Chemnitz, 27.-29. August 2025
- Quellenangabe
- The 9th HUMANIST Conference - Virtual Centre of Excellence - Chemnitz, Germany 27–29 August 2025
- DOI
- https://doi.org/10.60687/2026-0006
- Abstract (EN)
- When switching from vehicles with combustion engine (ICEV) to battery powered vehicles (BEV) driving behaviour has a big impact on the available driving range. Currently, there is a lack of insight regarding the knowledge drivers should have to extend range by applying eco-driving strategies. Semi-structured interviews with N = 52 ICEV drivers were conducted on known eco-driving strategies as well as measures to reduce energy consumption and their application. The results revealed that most drivers do have knowledge of eco-driving strategies and measures to some extent. However, this knowledge is not extensive and some of it is not correct. While the effect of reduced vehicle speed on energy efficiency is underestimated, the effect of assistance systems like ACC is overestimated. In addition, participants reported applying fewer strategies than they actually know. We conclude that drivers should be provided with specific knowledge on eco-driving in electric vehicles as well as instant feedback showing benefits of eco-driving to promote actual application of the correct behaviors.
- Freie Schlagwörter (EN)
- Electric Driving, Eco-driving, Energy Efficiency, Mental Models
- Klassifikation (DDC)
- 158
- Normschlagwörter (GND)
- Batteriefahrzeug, Elektrofahrzeug, Energieeffizienz
- Herausgeber (Institution)
- Technische Universität Chemnitz, Chemnitz
- Version / Begutachtungsstatus
- publizierte Version / Verlagsversion
- URN Qucosa
- urn:nbn:de:bsz:ch1-qucosa2-1013125
- Veröffentlichungsdatum Qucosa
- 07.01.2026
- Dokumenttyp
- Konferenzbeitrag
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis
CC BY-SA 4.0