Cited by 122Electric and Hybrid Vehicle TechnologiesBattery Modeling and ManagementElectric Vehicles and Infrastructure

The DOI matches its Crossref record; 35 of the 36 references it cites were found in a registry or an index; 21 of the 47 sources its claims cite were checked for support.

Effect of Low Temperature on Electric Vehicle Range

Open access
Steinstraeter, Matthias, Heinrich, Tobias, Lienkamp, Markus·2021·World Electric Vehicle Journal

Abstract

A significant disadvantage of battery electric vehicles compared to vehicles with internal combustion engines is their sharply decreased driving range at low temperatures. Two factors are primarily responsible for this decreased range. On the one hand, the energy demand of cabin heating needs to be supplied by the vehicle’s battery since less waste heat is available from the powertrain, which could be used to cover heating demands. On the other hand, a limited capability to recuperate at low temperatures serves to protect the battery from accelerated aging, which ultimately leads to less energy regeneration. This paper analyzes the impact of both factors separately on a battery electric vehicle’s driving range. Additionally, this paper provides technical requirements for the implementation of an electrothermal recuperation system. Such a system has the potential to reduce the impact of both abovementioned factors on driving range by enabling the direct usage of regeneratable energy for heating when battery charging is limited under cold conditions. The presented analysis is based on BMW i3 and Tesla Model 3 datasets, which combined cover more than 125 trips in and around Munich at different ambient conditions. The results show that the range can decrease by up to 31.9% due to heating and by up to 21.7% due to limited recuperation, which gives a combined maximum range decrease of approximately 50% under cold conditions. Additionally, it was found that a heater with a short reaction time in the lower millisecond range and a power capability of 20 kW would be sufficient for an electrothermal recuperation system to enable the utilization of unused regenerative braking potentials directly for heating.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This paper separates the effects of cabin heating and limited regenerative braking on battery electric vehicle range under cold conditions using real-world BMW i3 and Tesla Model 3 driving data. It finds heating can reduce range by up to 31.9% and limited recuperation by up to 21.7%, giving a combined maximum reduction of approximately 50%, and derives requirements for an electrothermal recuperation system.

Key findings

  • Heating energy demand can cut a BEV’s range by up to 31.9% (Tesla Model 3) and 30.0% (BMW i3) of total trip energy, i.e., almost one third.
  • Recuperated energy can cover up to 42.2% (Tesla) and 38.6% (BMW) of traction-system energy demand; if recuperation were disabled for a whole trip, theoretical range loss could reach about 42%, but practical measured range reductions due to limited recuperation were up to 21.7% (Tesla rural trip) and 8.33% (BMW FTM trip comparison).
  • Regenerative braking power is limited below 10 °C, with an approximately linear dependence on battery temperature; above 10 °C no significant limitation was detected. Tesla enabled regenerative braking at −4 °C, while the lowest measured BMW battery temperature with recuperation was −1.5 °C.
  • Combined heating and limited-recuperation effects can reduce range by approximately 50% under cold conditions. An electrothermal recuperation system would need response times in the lower millisecond range and power capability of 20 kW.

Methods

  • Real-world driving logs from a 2014 BMW i3 and a 2020 Tesla Model 3 in and around Munich, covering more than 125 trips; all trips used the same driver, with cabin temperature set to 22 °C and automatic mode. Random trips included 68 BMW and 44 Tesla trips; designed routes included 9 BMW FTM-route trips and Tesla city/rural/highway routes (3, 5, and 5 trips).
  • Two-stage analysis: a general analysis of all trips and a detailed same-route comparison. Heating energy share (HS) was computed from heater current/voltage divided by battery discharge energy; recuperation energy share (RS) was computed from battery charge energy divided by traction-system energy demand.
  • Recuperation analysis used a clustering algorithm to identify maximum regenerative braking power versus battery temperature (1 °C step), and a longitudinal dynamics simulation to predict regenerative braking potential. The simulation used speed and altitude signals, Gaussian smoothing with bandwidth b = 16, and a reverse-engineered CAD drivetrain moment of inertia of 10.42 kg·m². Trip parameters included regenerative braking performance (RP), potential regenerative braking share (PRS), measured range reduction (MRR), and unused range potential (URP).

Limitations

  • Stated: the available dataset does not allow detailed analysis of how weather conditions affect heating requirements; this remains open for further research.
  • Stated: MRR has uncertainty because trip characteristics (velocity and acceleration) and powertrain efficiency can vary between trips on the same route, so the absolute traction energy demand may not be identical.
  • Stated: URP is theoretical because it assumes 100% powertrain efficiency.
  • Stated: no exact minimum battery temperature for allowing recuperation could be determined for the BMW i3 due to lack of operating data at lower temperatures.
  • Stated: ETR range regain is restricted by the limited energy storage capability of the heating circuit and the heater’s inability to utilize peak recuperation powers above 20 kW.
  • Stated: extreme cold conditions such as −26 °C were not investigated, though trends suggest heating energy share would be higher at such temperatures.
  • Evident from the text: the study is based on only two vehicle models, one driver, and routes in and around Munich, which limits generalizability; the BMW cold-condition recuperation duration analysis also relies on a small database in that range.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.3390/wevj12030115

Cites

35 of 36 references verified0 citation errors · 1 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

21 of 47 cited sources checked · 14 supported · 1 flagged · accuracy not yet measured

Show all 75 claims

  • It may state two separate claims as one. 33
  • Probably not a substantial claim. 24
52 of 52
  • The paper relies on this without support.

    This is the first paper to analyze the two main factors causing limited range of BEVs at low temperatures separately.

    “To the best of our knowledge, this is the first paper to analyze the two main factors causing a limited range of BEVs at low temperatures separately.”
  • The paper relies on this without support.

    Heat pump performance at low temperatures is restricted by decreasing coefficient of performance and risk of freezing below the coolant's freezing point.

    “Firstly, the coefficient of performance (COP) decreases at lower temperatures, and secondly, heat pumps show a risk of freezing when the temperature drops below the coolant's freezing point.”
  • The paper relies on this without support.

    The battery can still be charged at cold temperatures even though charging is limited.

    “However, they set the battery's charging capability to zero and did not consider that the battery can still be charged at cold temperatures even though charging is limited.”
  • The paper relies on this without support.

    There is a lack of available information in scientific publications on BEV drivetrain moments of inertia.

    “Due to the lack of available information in scientific publications on BEV drivetrain moments of inertia, we reverse-engineered a CAD model of a BEV drivetrain (Figure 3) on the basis of publicly available information.”
  • The authors state this as an assumption.

    All drivetrain components are made from homogeneous materials with a material density of ρ_Comp.

    “All drivetrain components were assumed to be made from homogeneous materials with a material density of ρ Comp .”
  • The paper relies on this without support.

    Steep slopes are not present on the roads driven on by the vehicles in the datasets.

    “Since steep slopes are not present on the roads driven on by the vehicles in the datasets, a positive total driving resistance means the vehicle must supply power for propulsion, whereas a negative driving resistance means the vehicle has to supply braking power to explain the observed change in velocity.”
  • The authors state this as an assumption.

    Potential recuperation phases are present whenever the computed total driving resistance power P_DR is smaller than zero and the traction system current I_TS is smaller than or equal to zero.

    “Potential recuperation phases are assumed to be present whenever the computed total driving resistance power P DR (Equation ( 5)) is smaller than zero and when the traction system current I TS (Equation (11)) is smaller than or equal to zero.”
  • The authors state this as an assumption.

    The powertrain efficiency is at 100% for the potential regenerative braking share (PRS).

    “This value assumes that the powertrain efficiency is at 100%, which makes it a theoretical number.”
  • The authors state this as an assumption.

    The same assumption and uncertainty applies for the URP as for the MRR to allow the deduction of range implications based on energy share values.

    “For the URP, the same assumption and therefore also the same uncertainty applies as for the MRR to allow the deduction of range implications based on energy share values.”
  • The authors state this as an assumption.

    The efficiency assumption for the PRS applies as well for the URP.

    “Additionally, the efficiency assumption for the PRS applies as well for the URP, which makes the URP also a theoretical value.”
  • The authors state this as an assumption.

    The driver was the same for all trips, so passenger comfort can be neglected for explaining the phenomenon of warmer trips requiring more heating energy.

    “Since the driver was the same for all trips, it is assumed that the former factor can be neglected for explaining the phenomenon.”
  • The authors state this as an assumption.

    The powertrain efficiency is 100% for the URP additional range advantage calculations.

    “The URP shows that the vehicle could have gained an additional range advantage of 11.74% for the FTM Trip 06 and 15.11% for FTM Trip 07 when it would have used the respective predicted regenerative braking potential to the fullest (assumption: powertrain efficiency of 100%).”
  • The paper relies on this without support.

    The range reductions from heating energy demands and limited recuperation are additive.

    “In total, range reductions of approximately.50% are possible at low temperatures due to the combination of both heating energy demands and limited recuperation.”
  • The paper relies on this without support.

    The two test vehicles (BMW i3 and Tesla Model 3) are representative of BEVs in general for the purpose of generalizing the findings.

    “A BEV's maximum regenerative braking power capability depends on the battery temperature.”
  • The paper relies on this without support.

    The longitudinal dynamics simulation accurately predicts the theoretically possible recuperation potential.

    “The predicted potential was determined by a longitudinal dynamics simulation for both vehicles.”
15 of 15

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Sakhdari and Azad citation points to a different author

    Minor

    The text identifies reference [46] as work by Sakhdari and Azad, but entry 46 is by Kuptsov. Sakhdari and Azad appear at entry 45.

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Metadata

Authors
Steinstraeter, M., Heinrich, T., & Lienkamp, M.
Affiliations
Technical University of Munich (DE)
Corresponding author
Steinstraeter, Matthias
Venue
World Electric Vehicle Journal
Publisher
MDPI AG
Published
2021-08-10
Volume
12
Issue
3
Pages
115
ISSN
2032-6653 (ISSN-L)
OpenAlex
W3189275896
Cited by
122
References
32
Citations by year
2026: 32 · 2025: 41 · 2024: 25 · 2023: 13 · 2022: 10 · 2021: 1
FWCI
3.93
Type
journal article
Language
en
Open access
Locations
  • World Electric Vehicle Journal (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion)
  • mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion, other-oa)
Funders
Webasto Thermo&Comfort (-)
Topics
  • Physical Sciences › Engineering › Automotive Engineering › Electric and Hybrid Vehicle Technologies
  • Physical Sciences › Engineering › Automotive Engineering › Battery Modeling and Management
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
Keywords
battery electric vehicles, driving range, low temperature, cabin heating, regenerative braking, battery degradation, range loss, BMW i3, Tesla Model 3

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