Dataset to „Battery Electric Vehicles in Commercial Fleets: Use profiles, battery aging, and open-access data“

Rücker, Fabian; Schoeneberger, Ilka; Figgener, Jan; Sauer, Dirk Uwe

doi:10.18154/RWTH-2024-01907

Dataset to „Battery Electric Vehicles in Commercial Fleets: Use profiles, battery aging, and open-access data“

Rücker, Fabian (Corresponding author)^RWTH* ; Figgener, Jan^RWTH* ; Schoeneberger, Ilka^RWTH* ; Sauer, Dirk Uwe^RWTH*

2024

Online
DOI: 10.18154/RWTH-2024-01907
URL: https://publications.rwth-aachen.de/record/979878/files/Electric_Vehicle_and_Battery_Data.zip

Einrichtungen

Lehrstuhl für Elektrochemische Energiewandlung und Speichersystemtechnik (618310)
Center for Ageing, Reliability and Lifetime Prediction of Electrochemical and Power Electronic Systems (080070)
Profilbereich Energy, Chemical & Process Engineering (ECPE) (080016)

Projekte

16SBS001C - Gewerblich operierende Elektro-Kleinflotten GO ELK! (16SBS001C) (16SBS001C)

Inhaltliche Beschreibung (Schlagwörter)
electric vehicle (frei) ; open-access data (frei) ; charging curve (frei) ; field test (frei) ; battery aging (frei) ; fleet (frei)

Kurzfassung
Electric vehicles are key to reducing emissions in the transportation sector, and the electric vehicle market is growing strongly worldwide. In research and development in the electric vehicle sector, it is important to understand electric vehicle use profiles and their impact on battery aging. The battery is the central element of a vehicle as it determines the range as well as the price. For techno-economic analysis, battery aging is of special interest as it is a major factor in the vehicle’s lifetime. Battery aging depends on the battery use profile, but up to now, operational data is scarce, and many publications are based on simulations and assumptions. To contribute, we analyze multi-year commercial vehicle and battery data collected from onboard data loggers in a field test conducted from 2014 to 2016. We also develop and evaluate periodic non-intrusive capacity tests carried out with a chassis dynamometer to assess battery aging in terms of capacity fade. Electric vehicles in a geriatric care fleet experienced high usage and regular driving patterns with annual driving distances of 9062 km to 15308 km and a mean state-of-charge between 70% and 80% while driving. Use profile regularity and state-of-charge values at the time of plug-in are major factors in the evaluation of vehicle-to-X application viability. Regarding aging, the batteries suffered a capacity fade from 3.1% to up to 13% during fleet operation of three years. We publish time series data of the vehicle and the battery in addition to mobility data for nine vehicles to fill the data gap for available electric vehicle data and allow for further analysis.

OpenAccess:
ZIP
(additional files)