Data-driven modelling of passenger-car stock electrification: validation and cross-country scenarios

Electrification policy targets new registrations, but the transition of the national passenger-car stock depends jointly on BEV adoption and vehicle retirement. This study models both, using the Czech Republic as an ageing-market case. A power-law registration function is calibrated on Czech data for 2016–2024 and benchmarked against five reference countries; a fixed-lifetime stock-turnover model, with an age-structured extension, then gives post-2035 trajectories. The adoption parameter α is a reduced-form capacity measure reflecting affordability, policy continuity and charging access. Adjusted MAPE is 6.1–17.2 % with R 2 above 0.92; the Czech in-sample fit gives MAPE 5.8 %, R 2 0.974, α cal 0.034 and n cal 2.81. Vehicle lifetime alone sets the nominal replacement horizon r d = r 0 + L: 2047 for L = 12 years, 2055 for L = 20, while α scn = 0.10–0.40 governs the stock trajectory, not the terminal year. Results are scenario comparisons, not forecasts.

Authors

Institutions

Publication Details

Journal
Transportation Research Part D Transport and Environment
Published
2026-09-19
DOI
https://doi.org/10.1016/j.trd.2026.105639
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Data-driven modelling of passenger-car stock electrification: validation and cross-country scenarios

Vladislav Kemka, Jan Kovanda, Dominik Fink, Pavel Žlábek et al.
Transportation Research Part D Transport and Environment
Electric Vehicles and Infrastructure
article

Data-driven modelling of passenger-car stock electrification: validation and cross-country scenarios

Vladislav Kemka, Jan Kovanda, Dominik Fink, Pavel Žlábek, Harald Lerch
article en

Abstract

Electrification policy targets new registrations, but the transition of the national passenger-car stock depends jointly on BEV adoption and vehicle retirement. This study models both, using the Czech Republic as an ageing-market case. A power-law registration function is calibrated on Czech data for 2016–2024 and benchmarked against five reference countries; a fixed-lifetime stock-turnover model, with an age-structured extension, then gives post-2035 trajectories. The adoption parameter α is a reduced-form capacity measure reflecting affordability, policy continuity and charging access. Adjusted MAPE is 6.1–17.2 % with R 2 above 0.92; the Czech in-sample fit gives MAPE 5.8 %, R 2 0.974, α cal 0.034 and n cal 2.81. Vehicle lifetime alone sets the nominal replacement horizon r d = r 0 + L: 2047 for L = 12 years, 2055 for L = 20, while α scn = 0.10–0.40 governs the stock trajectory, not the terminal year. Results are scenario comparisons, not forecasts.

Transportation Research Part D Transport and EnvironmentVol. 161
University of West Bohemia in Pilsen (CZ)
Openalex Percentile: Top 20%
Electric Vehicles and Infrastructure
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.