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Cited by 23Electric Vehicles and InfrastructureSmart Grid Energy ManagementElectric and Hybrid Vehicle Technologies

Grid-connected cabin preheating of Electric Vehicles in cold climates – A non-flexible share of the EV energy use

Open access
Sørensen, Åse Lekang, Ludvigsen, Bjørn, Andresen, Inger·2023·Applied Energy
DOI 10.1016/j.apenergy.2023.121054
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Abstract

The number of EVs is increasing globally. In cold climates, it is generally recommended to use electricity from the grid to preheat the EV cabin before using the car, to extend driving ranges, to ensure comfort, and for safety. A majority of such preheating sessions are happening in the morning hours during the winter, when there is also a high demand for other energy use. It is thus important to understand the power loads for grid-connected preheating of EV cabins. This work presents an experimental study, with 51 preheating sessions of five typical EV models during different outdoor temperatures. The results of the study showed that during the preheating sessions, most of the EVs had a power use of between 3 and 8 kW initially, which was reduced to about 2 to 4 kW after a 10 to 20 min initial period. For most of the sessions, the preheating lasted between 15 and 45 min. The preheating energy use was found to be up to 2 kWh for most EVs, with a maximum of 5 kWh. Multiple linear regression models were developed, to investigate the relationship between various variables and the energy use for preheating. Finally, hourly energy loads for EV cabin preheating were compared to other energy loads in apartment buildings. The power and energy loads for preheating EV cabins are affected by a number of parameters, such as the specific EV, charge point, preheating duration, temperature levels, and user habits.

AI snapshot

Written from the paper’s full text.

TL;DR

This study experimentally measures grid-connected EV cabin preheating in cold climates using 51 sessions across five EV models in Norway, finding initial loads of 3–8 kW that fall to about 2–4 kW after 10–20 minutes. It develops multiple linear regression models for preheating energy and shows that, while preheating can strongly increase an apartment’s morning peak, its aggregated winter morning load impact is small under the study’s assumptions.

Key findings

  • Across 51 preheating sessions (24 at site 1, 27 at site 2), most EVs used 3–8 kW initially, reduced to about 2–4 kW after 10–20 min; sessions mostly lasted 15–45 min, with outdoor temperatures from −10 °C to +10 °C. Preheating energy was up to about 2 kWh for most EVs, while Tesla Model 3 used up to 5 kWh.
  • Two MLR models were selected: mod_TDSH* had R² 0.848 for training and 0.895 for validation; mod_CSH* had R² 0.860 for training and 0.752 for validation. For the same cabin temperature difference, predicted preheating energy for EVs with PTC was 2 times higher than for EVs with HP, and large EVs used 1.9 times more than small/medium EVs.
  • For an example cold day, EV cabin heating increased the apartment morning hourly energy peak from 4.2 kWh/h to 6.2 kWh (48%) with 2 kWh preheating, or to 8.2 kWh (95%) with 4 kWh preheating.
  • In aggregated scenarios, the workday morning preheating peak varied between 0.15 kW and 0.67 kW per EV user. Assuming 0.7 EVs per apartment and 50% preheating use, cabin preheating increased the average winter workday morning load by 0.5–2% including all apartment energy loads and EV charging, and by about 10% compared with apartment electricity only.

Methods

  • Experimental trials at two Norwegian sites with 7.4 kW level 2 charge points: site 1 in Oslo during winter 2021/2022 logged power every second and cabin temperature every minute for BMW i3, Jaguar I-PACE, Nissan Leaf, Tesla Model 3, and VW eGolf; site 2 in Bærum during 2020–2022 logged power at 15-minute resolution for three Nissan Leaf cars. In total, 51 preheating sessions were analysed, plus 11 battery-preheating sessions for Nissan Leaf MY2018.
  • Multiple linear regression in R used forward selection on the 51 trial sessions, with an independent validation dataset of 17 preheating sessions using Nissan Leaf MY2018, Kia Soul MY2015, and Tesla Model S MY2019 across three 7.4 kW charge points. Variables included outdoor temperature, cabin temperature difference, preheating duration, EV size, and heating system.
  • Preheating loads were compared with apartment energy loads using hourly data from 505 apartments in Trondheim and 24 apartments in Bærum/Oslo. Aggregated grid loads were assessed by combining trial results with an EV charging dataset of 34,499 charging sessions from 261 EV users in 12 Norwegian locations.

Limitations

  • The paper states that a larger dataset would improve the models, with more EV models and more EVs; only one EV was tested for most models, so results may depend on the specific EV and its settings. Cabin temperatures were logged at only one location in the cabin, normally the cup holder, creating uncertainty.
  • The paper states that the aggregated effect seems rather small given the assumptions, and that actual aggregated load depends on EV density, number of preheating sessions per day, preheating power and duration, outdoor temperatures, and user habits.
  • Evident from the text: some preheating sessions were interrupted by plug-out, so energy use could be higher; site 2 had 15-minute power resolution and no cabin temperature logging; and the battery-preheating trial was limited to Nissan Leaf MY2018.

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

Integrity signals

Registry

Crossref · 10.1016/j.apenergy.2023.121054

Cites

42 of 42 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 46 cited sources checked · 0 supported · 0 flagged

  • Findingreasoning

    After a 10 to 20 min initial period, the cabin preheating power was reduced to about 2 to 4 kW.

    “After a 10 to 20 min initial period, the cabin preheating power was reduced to about 2 to 4 kW.”
    • Also stated in: § 4. Conclusion · plain
      “After a 10 to 20 min initial period, the cabin preheating power was reduced to about 2 to 4 kW.”
    Quote in the paperNot a substantial claim
  • Findingreasoning

    The requested cabin temperature (22 °C) was not reached.

    “The temperature difference in the EV cabin was in average about 4 • C, and the requested cabin temperature (22 • C) was not reached.”
    Quote in the paperSubstantial claim
  • Findingown data

    For Tesla Model 3, the cabin temperature increased about 15°C during the coldest session (from -1.5 to 14.5°C).

    “The cabin temperature increased about 15 • C during the preheating session (from -1.5 to 14.5 • C)”
    Quote in the paperNot a substantial claim
  • Findingreasoning

    There is a difference in user habits in scenarios 1 and 3 (with all users) compared with 2 and 4 (with most frequent users).

    “There is a difference in user habits in scenarios 1 and 3 (with all users) compared with 2 and 4 (with most frequent users).”
    Quote in the paperNot a substantial claim
  • Findingown data

    There is a difference between EV models in how fast the cabins are heated.

    “Still, there seems to be a difference between the EV models in how fast the cabins are heated, and if the temperature levels requested for the preheating sessions can be reached.”
    Quote in the paperNot a substantial claim
  • Classified as probably not a substantial claim. 51
  • May combine two claims. 38
  • The quote only partly states this claim. 1

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    For space heating and DHW, the apartments have an average daily heat load between 1.5 and 2.5 kW/apartment during the winter, with a morning and evening peak.

    “For space heating and DHW, the apartments have an average daily heat load between 1.5 and 2.5 kW/apartment during the winter, with a morning and evening peak.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    For BMW i3, cabin preheating power was initially on the same level as the onboard charger capacity, then reduced to between 2 and 5 kW after approx 10 min.

    “The cabin preheating power was initially on the same level as the onboard charger capacity, being reduced to between 2 and 5 kW after approx.10 min.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    For Nissan Leaf MY2013, preheating power was highest, about 4 to 5 kW, and it was the only Nissan Leaf EV in the trial without HP.

    “MY2013 has the highest preheating power, of about 4 to 5 kW, and is also the only Nissan Leaf EV in the trial without HP.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    For Tesla Model 3, cabin preheating power was initially on the same level as the maximum, before being reduced to about 3 kW after approx 20 min.

    “The cabin preheating power was initially on the same level as this maximum, before being reduced to about 3 kW after approx.20 min.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Model TDSH* relates cabin preheating energy use to outdoor temperature and EV size/heating system, with R2 0.848 for training data and 0.895 for validation data.

    “Two models were selected to show the relationship between the cabin preheating energy use, outdoor temperature, and EV size/heating system (model TDSH*, R 2 0.848 for training data and 0.895 for validation data), and between the cabin preheating energy use, cabin temperature difference, preheating duration, and EV size / heating system (model CSH*, R 2 0.860 for training data and 0.752 for vali”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    For VW eGolf, preheating sessions were ended by the EV thermal management system.

    “before being ended by the EV thermal management system.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    For the example day, energy for EV cabin heating increases the hourly energy peak in the morning from 4.2 kWh/h to 6.2 kWh (48 %), or from 4.2 kWh/h to 8.2 kWh (95 %), including all the energy loads.

    “For the example day, energy for EV cabin heating increases the hourly energy peak in the morning from 4.2 kWh/h to 6.2 kWh (48 %), or from 4.2 kWh/h to 8.2 kWh (95 %), including all the energy loads (Fig. 13 d).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    For Jaguar I-PACE, initial cabin preheating power was close to the onboard charger capacity, but reduced after approx 5 min.

    “Also for this EV, the initial cabin preheating power was close to the onboard charger capacity, but the power was reduced after approx.5 min.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based). May combine two claims.

    Findingnone given

    During workdays, a majority of EV cabin preheating sessions happen in the morning hours, when there is also a high demand for other energy use.

    “During workdays, a majority of EV cabin preheating sessions happen in the morning hours, when there is also a high demand for other energy use.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Model CSH* relates cabin preheating energy use to cabin temperature difference, preheating duration, and EV size/heating system, with R2 0.860 for training data and 0.752 for validation data.

    “Two models were selected to show the relationship between the cabin preheating energy use, outdoor temperature, and EV size/heating system (model TDSH*, R 2 0.848 for training data and 0.895 for validation data), and between the cabin preheating energy use, cabin temperature difference, preheating duration, and EV size / heating system (model CSH*, R 2 0.860 for training data and 0.752 for vali”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    At site 1, the two coldest sessions (ID 3 and 7) lasted for 45 min.

    “At site 1, the two coldest sessions (ID 3 and 7, -4.4 • C) used about 1.5-1.8kWh energy and lasted for 45 min.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Some variables are dependent on each other, for example cabin temperature difference and preheating duration, and should not be used in the same model.

    “The table shows that some variables are dependent on each other, for example cabin temperature difference and preheating duration, and should not be used in the same model.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    In the trial, the preheating energy use was found to be up to 2 kWh for most EVs, while the Tesla used up to 5 kWh.

    “In the trial, the preheating energy use was found to be up to 2 kWh for most EVs, while the Tesla used up to 5 kWh.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    For Tesla Model 3, the other two sessions were ended by plug-out of the EV after about 20 min.

    “and both of these sessions were ended by plug-out of the EV after about 20 min.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

    Findingnone given

    The average apartment electricity load during winter is between 0.5 and 0.8 kW/apartment, with the highest energy loads in the afternoons/evenings.

    “The average apartment electricity load during winter is between 0.5 and 0.8 kW/apartment, with the highest energy loads in the afternoons/evenings.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    For Jaguar I-PACE, the coldest session ended when the EV was plugged out from the CP.

    “and the session ended when the EV was plugged out from the CP.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    The outdoor temperatures during the battery trial sessions varied from 2 to -11 °C.

    “The outdoor temperatures during the sessions varied from 2 to -11 • C.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    mod_TDSH* and mod_CSH* predict energy charged from the validation data with R2 0.895 and R2 0.752, respectively.

    “The mod_TDSH* and mod_CSH* predict energy charged from the validation data with R 2 0.895 and R 2 0.752, respectively.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

    Findingnone given

    Maximum duration for preheating is car dependent, and for example Nissan starts the preheating up do 2 h before departure, depending on the outdoor temperature, while Tesla allows up to 4 h preheating after starting time, dependent on user preferences.

    “Maximum duration for preheating is car dependent, and for example Nissan starts the preheating up do 2 h before departure, depending on the outdoor temperature, while Tesla allows up to 4 h preheating after starting time, dependent on user preferences.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    During the rest of the day, and during the weekends, the preheating load is more evenly distributed, and the average daily load varies from 0.04 kW in Scenario 1 to 0.2 kW per user in Scenario 4.

    “During the rest of the day, and during the weekends, the preheating load is more evenly distributed, and the average daily load varies from 0.04 kW in Scenario 1 to 0.2 kW per user in Scenario 4.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    For VW eGolf, charging power was about 4 kW, which is lower than the listed onboard charger capacity of 7.2 kW.

    “For the VW eGolf used in the trial, the charging power was about 4 kW, which is lower than the listed onboard charger capacity of 7.2 kW.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    In total, 51 preheating sessions were analysed: 24 at site 1 (5 EVs: BMW i3, Jaguar I-PACE, Nissan Leaf, Tesla Model 3, VW eGolf) and 27 at site 2 (3 EVs, all Nissan Leaf).

    “In total 51 preheating sessions are analysed, whereof 24 sessions at site 1 (5 EVs, BMW i3, Jaguar I-PACE, Nissan Leaf, Tesla Model 3, and VW eGolf), and 27 sessions at site 2 (3 EVs, all Nissan Leaf).”
    • Also stated in: § 3.1.2. Summary of the cabin preheating trial: Power, cabin temperatures, and duration · plain
      “In this trial, preheating sessions for five EV models were explored, with 24 sessions at site 1 and 27 sessions at site 2.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    For session ID 7, the cabin temperature increased about 16°C during preheating (from -1.5 to 14.5°C).

    “For one of these sessions (ID 7), the cabin temperature increased about 16 • C during the preheating (from -1.5 to 14.5 • C).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    For Tesla Model 3, the coldest trial session (ID 15) was ended by plugging out the EV from the CP.

    “before being ended by plugging out the EV from the CP.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    During the trial, the outdoor temperatures varied between -10 °C and +10 °C.

    “During the trial, the outdoor temperatures varied between -10 • C and + 10 • C.”
    Quote in the paperNot a substantial claim

  • The quote only partly states this claim.

    Findingown data

    Comparing predicted energy use for EVs with different sizes, energy use for large EVs is 1.9 times higher than for small/medium EVs.

    “Comparing predicted E for EVs with different sizes, E for S L is 1.9 times higher than for S SM .”
    • Also stated in: § 4. Conclusion · plain
      “Comparing predicted energy use for EVs with different sizes, preheating energy use for large EVs was 1.9 times higher than for small/medium EVs.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingnone given

    For the grid-connected preheating sessions for the same EV, the preheating durations were longer and the EV cabin temperature differences larger.

    “For the gridconnected preheating sessions for the same EV, the preheating durations were longer and the EV cabin temperature differences larger (ref.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Findingnone given

    Our literature review identified a need for more experimental knowledge within this topic.

    “Our literature review identified a need for more experimental knowledge within this topic.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The EV charging load during winter is in the range of 0.1 kWh per EV user during morning/daytime, and 0.5 kW per EV user during evenings/early night hours.

    “The EV charging load during winter is in the range of 0.1 kWh per EV user during morning/daytime, and 0.5 kW per EV user during evenings/early night hours.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    EV cabin preheating power and energy loads were found to be affected by a number of parameters, such as the specific EV (EV model, HVAC system, fresh air rates), CP (available charging power), user (preheating duration, EV settings), initial cabin and battery temperatures, and weather conditions (ambient temperature, solar radiation).

    “In summary, the EV cabin preheating power and energy loads were found to be affected by a number of parameters, such as the specific EV (EV model, HVAC system, fresh air rates), CP (available charging power), user (preheating duration, EV settings), initial cabin and battery temperatures, and weather conditions (ambient temperature, solar radiation).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingnone given

    The models BMW i3, Jaguar I-PACE, Nissan Leaf, Tesla Model 3, and VW eGolf were tested, representing 38 % of the EVs in the Norwegian EV stock.

    “The models BMW i3, Jaguar I-PACE, Nissan Leaf, Tesla Model 3, and VW eGolf were tested, representing 38 % of the EVs in the Norwegian EV stock.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    For Nissan Leaf, cabin preheating power was lower, between 2 and 3 kW, and fairly stable during the preheating session.

    “The cabin preheating power was lower, between 2 and 3 kW, and was found to be fairly stable during the preheating session.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    In 28 European countries, uncontrolled EV charging would increase peak demand in the range of 35-51%.

    “EV charging loads have an impact on the power grid, and [3] found that in 28 European countries, uncontrolled EV charging would increase peak demand in the range of 35-51 %.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [3]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    The small temperature differences for the tested VW eGolf may indicate that the energy was mainly used for preheating of the battery, and not the EV cabin.

    “The small temperature differences for the tested VW eGolf may indicate that the energy was mainly used for preheating of the battery, and not the EV cabin.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationcitation

    A main reason for higher initial power use is that the PTC power use is higher in the beginning, to quickly achieve a thermal comfort level, and that the PTC provides start-up heat before a HP takes over.

    “A main reason is that the PTC power use is higher in the beginning, to quickly achieve a thermal comfort level [46,47], and that the PTC provides start-up heat before a HP takes over (Customer service Jaguar Land Rover Limited, personal communication May 2022).”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [46]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [47]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Customer service Jaguar Land Rover Limited, personal communication May 2022

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Classified as probably not a substantial claim.

    Study design and conductown data

    Sessions where charging and preheating happened simultaneously were excluded because preheating power and energy could not be separated from charging.

    “Sessions where the charging and the preheating happened simultaneously were not included, since in these sessions the preheating power and energy could not be separated from the charging.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    Preheating the EV using energy from the battery could fulfil comfort and safety goals of the driver, but to a less degree the goal of extending the driving range of the EV, since the battery SoC will be reduced.

    “This could fulfil comfort and safety goals of the driver, but to a less degree the goal of extending the driving range of the EV, since the battery SoC will be reduced.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Several EV models can alternatively preheat the EV using energy from the battery.

  • May combine two claims.

    Interpretationcitation

    The average cabin temperature difference of about 4 °C and failure to reach 22 °C can be explained by the preheating duration.

    “This can be explained by the preheating duration, which is maximum 15 min for Nissan Leaf when using energy from the battery [77].”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    Before preheating, EV batteries were charged to about 100% SoC (Tesla 80-95% SoC) to prevent simultaneous charging and preheating.

    “Before starting the preheating of the EV cabins, the EV batteries were charged to about 100 % SoC (for Tesla 80-95 % SoC).This was done to prevent simultaneous charging and preheating.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    For B, there was a small dataset, with only two EVs, and limited data for drawing general conclusions.

    “For B, there was a small dataset, with only two EVs, and limited data for drawing general conclusions.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Interpretationnone given

    When preheating the EV using energy from the battery, the grid energy use for preheating may become flexible in time, similar to other EV charging loads.

    “When preheating the EV using energy from the battery, the grid energy use for preheating may become flexible in time, similar to other EV charging loads.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Cabin preheating is becoming common practice for BEV and PHEV owners in cold climates.

    “Cabin preheating is becoming common practice for BEV and PHEV owners in cold climate [12].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [12]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    Both the trial dataset and validation dataset have uncertainties related to the measured cabin temperatures.

    “It can be noted that both for the trial dataset (Table 5) and validation dataset (Table 8), there are uncertainties related to the measured cabin temperatures, as described in section 3.1.2.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    The results presented in section 3 are based on the primary power meter (not adjusted), since the building distribution board was considered the most natural boundary for the building and grid analysis.

    “The results presented in section 3 are based on the primary power meter (not adjusted), since the building distribution board was considered to be the most natural boundary for the building and grid analysis.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    At site 1, 46 sessions were metered, and 24 of the sessions were selected for further analysis because their preheating time was clearly separated from their charging time; at site 2, 27 preheating sessions were analysed.

    “At site 1, 46 sessions were metered.24 of the sessions were selected for further analysis, since their preheating time was clearly separated from their charging time.At site 2, 27 preheating sessions were analysed.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    The five EV models tested are typical in the Norwegian market, and cover 38% of the EVs in the national EV stock.

    “The five EV models tested are typical in the Norwegian market, and the models cover 38 % of the EVs in the national EV stock (ref.Table 3 [52]).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [52]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationnone given

    The actual aggregated load will depend on a number of parameters, such as the EV density, the number of preheating sessions per day, the preheating power and duration, outdoor temperatures, and user habits.

    “The actual aggregated load will depend on a number of parameters, such as the EV density, the number of preheating sessions per day, the preheating power and duration, outdoor temperatures, and user habits.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

    Interpretationnone given

    More EV models can have heat pumps installed.

    “even more EV models can have HPs installed”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Tesla owner's manual [74] states that preheating automatically turns off after four hours, or if the charge level drops to 20%, if using the mobile app to turn on the climate control system.

    “Tesla owner's manual [74] states that the preheating automatically turns off after four hours, or if the charge level drops to 20 %, if using the mobile app to turn on the climate control system.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [74]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    When preheating the EV cabin, the energy use may differ when using energy from the battery, compared to using energy from the grid.

    “When preheating the EV cabin, the energy use may differ when using energy from the battery, compared to using energy from the grid.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Several EV models can alternatively preheat the EV using energy from the battery.

  • Classified as probably not a substantial claim.

    Study design and conductown data

    To validate the models, an additional independent dataset of 17 preheating sessions, not earlier included when training the models, was used.

    “To validate the models, an additional independent dataset was used to assess how the models performed.The dataset used for validation consisted of 17 preheating sessions, which were not earlier included when training the models.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    In Norway, the current density of personal cars was 1.4 cars per household in 2020, and apartments typically have lower access to parking spaces than freestanding houses.

    “The current density of personal cars in Norway was 1.4 car per households in 2020 [71] (including cars using fossil fuels), but apartments typically have lower access to parking spaces than freestanding houses.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [71]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Premisecitation

    During cold winter days, the Norwegian electricity grid experiences high peak loads, especially in the morning hours.

    “During such periods, the Norwegian electricity grid is already experiencing high peak loads [34].”
    • Also stated in: § 4. Conclusion · plain
      “Morning hours during cold winter days are the time of the year with the highest peak loads in Norway.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [34]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Parking requirements vary with location/municipality, ranging from 0.4 to 1.2 cars per apartment.

    “Parking requirements vary with the location /municipality, and is e.g.min.0.4 to 1.2 car per apartment [72].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [72]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    The example apartment was randomly selected (apartment ID 10), and its daily electricity use during the example day corresponds to the average electricity use for all the apartments during the same date.

    “The example apartment was randomly selected (apartment ID 10), and its daily electricity use during the example day corresponds to the average electricity use for all the apartments during the same date.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    The reason for the difference in user habits is most likely that the most frequent users have smaller battery capacities than the average users, and that they therefore more frequently charge their EVs during the day, before disconnecting from the CP in the afternoon.

    “The reason for this is most likely that the most frequent users have smaller battery capacities than the average users, and that they therefore more frequently charge their EVs during the day, before disconnecting from the CP in the”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    The additional validation dataset included differences in the EVs and CPs used, to evaluate if the developed models were well generalized or fitted too closely to the trial dataset.

    “Compared to the trial dataset that was originally used for creating the models, the additional dataset used for validation included some differences in the EVs and CPs used.The aim of introducing these differences was to evaluate if the developed models were well generalized, or if they fitted too closely to the trial dataset.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    According to [62], the necessary operation time for preheating is calculated two hours before the set preheating time, dependent on ambient temperature.

    “According to [62], the necessary operation time for preheating is calculated two hours before the set preheating time, dependent on the ambient temperature.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [62]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Interpretationnone given

    The EV battery can provide energy for preheating on days when extended driving ranges are not needed.

    “For example, the EV battery can provide energy for preheating on days where extended driving ranges are not needed.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    After preheating, SoC was controlled to still be 100% to ensure preheating energy was not supplied by the battery.

    “After the preheating session it was controlled that the SoC was still 100%, to make sure that the preheating energy was not supplied by the battery.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Interpretationreasoning

    Technological solutions can reduce the grid burden of EV cabin preheating.

    “Technological solutions can reduce the grid burden of EV cabin preheating.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationcitation

    For VW eGolf, the reason for the higher initial power level is that the battery is preheated in the beginning, and it takes a few (>5) minutes before the cabin temperature starts to increase.

    “The reason for the higher initial power level is that also the battery is preheated in the beginning (Customer service Harald A. Møller AS, personal communication May 2022), and it takes a few (>5) minutes before the cabin temperature starts to increase.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Customer service Harald A. Møller AS, personal communication May 2022

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    Three Nissan Leaf cars were tested with different model years: MY2018 at site 1 and site 2, while MY2013 and MY2015 were tested at site 2 only.

    “For Nissan Leaf, three cars were tested with different model years: MY2018 was tested at site 1 and site 2, while MY2013 and MY2015 were tested at site 2 only.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Interpretationnone given

    Preheating power can be managed according to a local power limit.

    “the preheating power can be managed according to a local power limit”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    The regression models were created with data from the 51 preheating sessions in the trial.

    “The regression models were created with data from the 51 preheating sessions in the trial.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    The average heated apartment area for the case in Bærum/Oslo (86 m2) is similar to the average area in Trondheim (88 m2).

    “The average heated apartment area for the case in Bærum/ Oslo (86 m 2 ) is similar to the average area in Trondheim (88 m 2 ).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Interpretationnone given

    Cabin preheating is probably most relevant for EV owners parking outside or in cold garages.

    “Cabin preheating is probably most relevant for EV owners parking outside or in cold garages.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Interpretationown data

    A larger dataset would improve the models.

    “A larger dataset would improve the models, since there are few sessions especially for S L H HP and S L H PTC .”
    • Also stated in: § 4. Conclusion · hedged
      “A larger dataset would improve the models, with an extended number of EV models, and EVs.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationreasoning

    The two selected models can be used in parallel, since they have different input values, and therefore different advantages when applying them in analysis.

    “The two selected models can be used in parallel, since they have different input values, and therefore different advantages when applying them in analysis.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    The high value for adjusted R2 and the low values for MAE and RMSE are considered favourable, and show that the models can be used for describing the cabin preheating energy use.

    “The high value for the adjusted R 2 and the low values for MAE and RMSE are considered to be favourable, and show that the models can be used for describing the cabin preheating energy use.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    Since only one EV is tested for most of the models, the results may not be general for the EV models but depend on the specific EV and its settings.

    “Since only one EV is tested for most of the models, the results may not be general for the EV models but depend on the specific EV and its settings.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Existing experimental studies with power data for EV heating sessions focused on improving HVAC systems and were not seen in relation with energy loads in buildings or the grid.

    “There exist some experimental studies with power data for EV heating sessions [37,39,40,46,47], but these studies focused on improving the HVAC systems in EVs and were not seen in relation with energy loads in buildings or the grid.”
    Quote in the paperSubstantial claim0 of 5 sources checked
    • cites [37]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [39]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [40]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [46]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [47]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    Since some of the preheating sessions were interrupted by disconnecting the EVs, it is expected that the energy use can be higher.

    “Since some of the preheating sessions were interrupted by disconnecting the EVs, it is expected that the energy use can be higher.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    For EV charging load, a session energy use of 15 kWh is typical for home charging.

    “For the EV charging load, two alternative load profiles are shown (3.6 kW or 7.4 kW charging power), both started charging at midnight, and with a session energy use of 15 kWh, which is typical for home charging [33].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [33]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S4 (based).

    Premisenone given

    The chosen EV density of 0.7 car per apartment corresponds to the available parking spaces for the apartments located at Risvollan.

    “The chosen EV density of 0.7 car per apartment corresponds to the available parking spaces for the apartments located at Risvollan.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Tesla recommends activating preheating at least 30-45 min before departure [28].

    “Tesla recommends activating preheating at least 30-45 min before departure [28].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [28]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    Such energy losses are not necessarily included when analysing SoC reductions related to cabin preheating using energy from the battery.

    “Such energy losses are not necessarily included when analysing SoC reductions related to cabin preheating using energy from the battery.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    When ambient temperature is low, preheating duration is longer, with a maximum of 2 h.

    “When the ambient temperature is low, the preheating duration is longer, with a maximum of 2 h.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [62]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

78 of 78

  • The authors state this as an assumption.

    The preheating happened within one clock hour during the morning, between 07:00 and 08:00.

    “It was assumed that the preheating happened within one clock hour during the morning, between 07:00 to 08:00.”

  • The authors state this as an assumption.

    The EV user habits for preheating the EVs are in line with the user habits for EV charging.

    “It is assumed that the EV user habits for preheating the EVs are in line with the user habits for EV charging, which is normally the main reason for CP connections.”

  • The authors state this as an assumption.

    All the EVs are preheated before plug-out times.

    “In the preheating scenarios it was assumed that all the EVs are preheated before plug-out times.”

  • The authors state this as an assumption.

    Preheating starting close to plug-out time and being interrupted by EV departure is how the preheating function is often used in real life.

    “This was accepted, since it was assumed that this is how the preheating function is often used in real life.”

  • The paper relies on this without support.

    Several EV models can alternatively preheat the EV using energy from the battery.

    “However, it should be noted that several EV models alternatively can preheat the EV using energy from the battery.”

  • The paper relies on this without support.

    Some EV models reduce the maximum preheating duration or the preheating power when the EV is not connected to a CP.

    “The reason for this is that some EV models reduce the maximum preheating duration or the preheating power when the EV is not connected to a CP.”

  • The paper relies on this without support.

    Apartment buildings have an expected high density of EV charging and cabin preheating use.

    “Apartment buildings have been chosen as the focus of this work, since this is a building type with an expected high density of EV charging and cabin preheating use.”

  • The authors state this as an assumption.

    All the preheating happens between 07:00 to 08:00 in the morning.

    “it is assumed that all the preheating happens between 07:00 to 08:00 in the morning.”

  • The paper relies on this without support.

    EV charging is often recognized as flexible, but cabin preheating is normally not flexible.

    “While the EV charging is often recognized as flexible, this is normally not the case for the cabin preheating.”

  • The authors state this as an assumption.

    Preheating habits during cold days are in accordance with the average charging habits of today, without adding any extra CP connections for preheating of the EVs.

    “It is assumed that the preheating habits during cold days are in accordance with the average charging habits of today, without adding any extra CP connections for preheating of the EVs.”

  • The paper relies on this without support.

    Winter loads during workdays are the dimensioning period for the grid.

    “For this study, winter loads during workdays are most relevant, since this is the dimensioning period for the grid.”

  • The authors state this as an assumption.

    In the aggregated comparison, every apartment had 0.7 EVs and 50% of the EVs used cabin preheating.

    “it was assumed that every apartment had 0.7 EVs and that 50 % of the EVs used cabin preheating.”

  • The paper relies on this without support.

    Knowledge on EV cabin preheating power and energy use is lacking in literature.

    “Such knowledge is lacking in literature”
13 of 13

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.

  • Conclusion adds duration to a model that does not use it

    Minor

    The conclusion says model CSH* relates energy use to preheating duration, but its listed formula contains cabin temperature difference, EV size, and heating system-not duration.

  • Tesla Model 3 cabin temperatures disagree with Table 5

    Minor

    The text gives the Tesla session's cabin temperatures as -1.5 to 14.5 °C, whereas Table 5 lists 2.5 to 17.5 °C for the same session (ID 15). The table's values support the stated 15 °C increase; the parenthetical temperatures do not.

  • Battery-trial temperature range excludes reported sessions

    Minor

    The stated outdoor-temperature range ends at 2 °C on its warm side, but the subsequent description reports battery-trial sessions at temperatures up to 9 °C.

  • Not all post-preheating battery charges were 100%

    Minor

    The stated check that battery state of charge remained at 100% does not hold for session ID 3: Table 5 records a fall from 98% to 96%.

4 of 4

Cites

Flagged first, then by citations

Research works printed but not linked: 5

  1. Volkswagen, Heating, air conditioning (Edition 10.2015), Work. Man. E-Golf 2014+; 2015. https://cardiagn.com/e-golf-2014-heating-air-conditioning/ (accessed May 5, 2022).
  2. Barnitt, 2010, Analysis of off-board powered thermal preconditioning in electric drive vehicles, EVS 2010 - Sustain, Mobil Revolut 25th World Batter Hybrid Fuel Cell Electr Veh Symp Exhib
  3. BMW Group University, Product information. I01 Heating and A/C Systems, Tech. Train.; 2014: 70. https://cardiagn.com/bmw-i3-training-heating-and-a-c-systems/ (accessed May 5, 2022).
  4. Statens Vegvesen, Nasjonal reisevaneundersøkelse Nøkkeltallsrapport 2020, RVU; 2021: 64. https://www.vegvesen.no/globalassets/fag/fokusomrader/nasjonal-transportplan-ntp/reisevaner/2020/nokkeltallsrapport-2020-versjon-per-23.12.21.pdf (accessed June 26, 2022).
  5. Krogstad, 2022, Parkering som virkemiddel for å nå nullvekstmålet, NORCE Helse Samf Rapport, 5, 102

Cited by

Sorted by citations

Related

Authors
Sørensen, Å. L., Ludvigsen, B., & Andresen, I.
Affiliations
  • SINTEF (NO)
  • Norwegian University of Science and Technology (NO)
Corresponding author
Sørensen, Åse Lekang
ORCID
Venue
Applied Energy
Publisher
Elsevier BV
Published
2023-07
Volume
341
Pages
121054
ISSN
0306-2619 (ISSN-L)
DOI
10.1016/j.apenergy.2023.121054
OpenAlex
W4366780378
Cited by
23
References
40
Citations by year
2026: 6 · 2025: 9 · 2024: 8
FWCI
1.68
Type
journal article
Language
en
Open access
Licence
Locations
  • Applied Energy (publishedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
  • NORA - Norwegian Open Research Archives (submittedVersion, cc-by)
Funders
Norges forskningsrad (272402, 257660)
Topics
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
  • Physical Sciences › Engineering › Automotive Engineering › Electric and Hybrid Vehicle Technologies
Keywords
grid-connected charging, cold climate, apartment buildings, multiple linear regression, outdoor temperature, user behavior patterns, driving range

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-28.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-28.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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