Experimental Study of Energy Consumption Variation in Recurring Driving Trips
Open accessAbstract
With a growing consumer market of battery electric vehicles, customers' demand for technology and features is on the rise.The range and, to a certain extent, the range estimation will play a key factor in customers' purchase decisions.In order to guarantee a precise range estimation over the usage life of battery electric vehicles, a method is presented that combines adaptive filter algorithms with statistical approaches.The statistical approach uses recurring driving cycles over the lifetime in order to derive the aging status of the traction battery.It is implied that the variance of the energy usage of these driving cycles is within certain bounds.This fact should be proven by an experimental case study.The dataset used in this paper is open to the public.
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Energy restored through regenerative braking under warm conditions without limitation can contribute 18% of the total energy required for a trip.
“since the energy restored through regenerative braking under warm conditions (without limitation) can contribute 18% of the total energy required for a trip [29].”
From Effect of Low Temperature on Electric Vehicle Range (2021) · cites this paper as [29]
The Results report that recuperation averaged 0.625 kWh, or 17.9% of driving energy, on reference runs that did not start with a fully charged battery. This supports an approximately 18% figure, but not the claim that it is a share of total trip energy or that it was measured under warm, unlimited conditions: the Results say the maximum recuperation-power limit was reached on 37 of 40 comparable reference trips. (LLM, conf=0.88)
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Cites
Critical review of state of health estimation methods of Li-ion batteries for real applications
Berecibar, M., Gandiaga, I., Villarreal, I., Omar, N., Van Mierlo, J., & Van den Bossche, P. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2015.11.042 · Cited by 1,126 · cited 1× · see citing works
“Furthermore, the accuracy of experimental techniques is rather low [10].”
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Research works printed but not linked: 11
- Hong, J., Park, S., and Chang, N. 2016. "Accurate Remaining Range Estimation for Electric Vehicles." In Proceedings of the Asia and South Pacific Design Automation Conference, 781-6.
- Adermann, J., Brecheisen, D., Wacker, P., and Lienkamp, M. 2017. "Parameter Estimation of Traction Batteries by Energy and Charge Counting during Reference Cycles." In 2017 IEEE 86th Vehicular Technology Conference 7.
- Adermann, J., Wacker, P., Horlbeck, L., Baumann, M., and Lienkamp, M. 2016. "Alternative Methods for Detecting the Degeneration of Electric Drive Train Components." In Conference on Future Automotive Technology, 1-9.
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Cited by
Sorted by citations
Effect of Low Temperature on Electric Vehicle Range
Steinstraeter, M., Heinrich, T., & Lienkamp, M. (2021) · World Electric Vehicle Journal · doi:10.3390/wevj12030115 · Cited by 122 · see citing works
Self-citation
- Authors
- Adermann, J., Kreibich, J., & Lienkamp, M.
- Affiliations
- Technical University of Munich (DE)
- ORCID
- Markus Lienkamp
- Venue
- J. of Electrical Engineering
- Publisher
- David Publishing Company
- Published
- 2017-09-28
- Volume
- 5
- Issue
- 5
- ISSN
- 2328-2223 (ISSN-L)
- OpenAlex
- W2758767948
- Cited by
- 10
- References
- 1
- Citations by year
- 2023: 1 · 2022: 1 · 2021: 2 · 2020: 1 · 2019: 4 · 2018: 1
- FWCI
- 0.68
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc
- Locations
- J of Electrical Engineering (publishedVersion, cc-by-nc)
- Funders
- Bayerische Forschungsstiftung
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
- Physical Sciences › Engineering › Automotive Engineering › Electric and Hybrid Vehicle Technologies
- Physical Sciences › Engineering › Automotive Engineering › Advanced Battery Technologies Research
- Keywords
- battery electric vehicles, energy consumption, battery degradation, range estimation, electric vehicle batteries, adaptive filtering, driving cycles
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