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Who Adopts Where and When? Electric Vehicle Diffusion with Building-Level Localization in Germany

Raab, Moritz ORCID iD icon 1; Kleinebrahm, Max ORCID iD icon 1; Vogl, Jonathan ORCID iD icon 1; Signer, Tim 1; Braun, Jannik; Fichtner, Wolf ORCID iD icon 1
1 Institut für Industriebetriebslehre und Industrielle Produktion (IIP), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

The electrification of private vehicles is a central element of decarbonizing transport and energy systems. Accurately anticipating when and where electric vehicles will be adopted is critical for charging infrastructure planning, distribution grid planning, and energy system operation, yet most diffusion models represent adoption at aggregated spatial scales. Here we introduce an open, high-resolution technology diffusion framework that links household-level electric vehicle adoption with GPS-exact residential locations. The framework combines a synthetic population, household-to-building matching, car ownership modeling, and a national Bass diffusion trajectory to translate aggregate electric vehicle growth into localized adoption pathways. We apply the framework to Germany from 2025 to 2050 and validate its main components against Census marginals, building assignments, and registered vehicle counts, demonstrating its suitability for spatially explicit EV diffusion analysis. The results reveal substantial spatial heterogeneity in electric vehicle diffusion across regions, municipalities, grid cells, and buildings. Differences in household income and the share of single-family houses shape local adoption trajectories, leading to higher adoption in West Germany than in East Germany and slightly higher adoption in rural than urban municipalities in aggregate. ... mehr


Volltext §
DOI: 10.5445/IR/1000196458
Veröffentlicht am 25.08.2026
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Industriebetriebslehre und Industrielle Produktion (IIP)
Publikationstyp Forschungsbericht/Preprint
Publikationsmonat/-jahr 08.2026
Sprache Englisch
Identifikator ISSN: 2196-7296
KITopen-ID: 1000196458
Verlag Karlsruher Institut für Technologie (KIT)
Umfang 28 S.
Serie Working Paper Series in Production and Energy ; 82
Schlagwörter Technology diffusion, Electric vehicle adoption, Synthetic population, Spatially explicit modeling, Household-level adoption, Building-level modeling
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