Fleet Model

We developed a System Dynamics-based analytical tool that is capable of estimating future vehicle fleet composition by age, technology, fuel type, and size, building on extensive and up-to-date data sets of the current vehicle stock and assumptions about expected market share of different vehicle types (e.g., diesel, gasoline, electric, hydrogen, …).
The model consists of 57 regions, many of them representing single countries, i.e. all the European countries and other world major economies.
The tool can be linked to a technology choice model, or can use exogenous assumptions on technology market shares to estimate future fleet composition and associated emissions.
Vehicle-kilometres (vkm) and passenger-kilometres (pkm) distinguished by zone, purpose, region, distance, urban level, time period, mode, and network, tonne-kilometres (tkm) distinguished by zone, car type, region, distance, urban level, time period, mode, and network, and average load factor by demand segment.
The main goal of the fleet module is to convert aggregate estimations of transport demand, in terms of pkm, tkm and/or vkm, into a more detailed vehicle classification and generation (cohort) which directly relates to technology in terms of vehicle performance and characteristics, fuel use, and emissions.
The tool has been used to estimate total emission savings under various electric-vehicle uptake scenarios, fully reflecting the inertia of the fleet (i.e. gradual fleet turn-over) as well as characteristics of the second hand market.
The tool is coded in Excel, Python, and Vensim, and highly flexible for any assessment involving impact on passenger car fleet.
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