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Range estimation: what the evidence base looks like

14 publications, 0 of them trials and 0 syntheses. This page describes the shape of that literature rather than summarising its conclusions.

Updated 4 min read 14 citations

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Ajay Kumar Chaurasiya · CC BY-SA 4.0 · Wikimedia Commons
What the evidence on range estimation is made of Of 14 publications on this topic, the breakdown by study type: 14 other. 14other (14)
14 publications, by study type. Volume is not strength — the same count can be a settled question or a pile of commentary, and which one it is depends almost entirely on this breakdown. Harvested from PubMed and Crossref; publication type as recorded by the source.

What this literature is made of

A reasonable volume of literature, but weighted towards reviews and observational work rather than trials. That is enough to describe a phenomenon and rarely enough to establish that an intervention works.

The distinction that matters most is between synthesis and primary research. A meta-analysis pools trials and is the closest thing to a settled answer a field produces. A narrative review is one group's reading of the same material and can be selective without being dishonest. Counting them together, which most citation counts do, obscures exactly the thing you want to know.

When the range estimation literature was published Publication years for the 14 papers on this topic, grouped into bands from before 2015 through to 2023 onwards. 2023 onwards5 papers2015-20194 papers2020-20223 papersBefore 20152 papers
Still active. The most recent paper here is from 2026, so this is a field where an answer written today may not hold for long. Publication years as recorded by PubMed and Crossref.

How this page is built

Everything above is computed from the citations this site harvested from PubMed and Crossref, not written by hand. When the weekly harvest finds a new paper on this topic, these counts change and the characterisation changes with them. That is the point: a hand-written claim about how strong an evidence base is starts decaying the day it is written.

Publication type is taken as the source records it. That is imperfect — journals label inconsistently, and a paper indexed as a "review" may be a systematic one — so treat the bands as approximate. They are accurate enough to distinguish a trial literature from a commentary literature, which is the distinction that matters.

Labelled chemical bottles standing together on a laboratory bench
564dude · CC BY-SA 3.0 · Wikimedia Commons

The strongest work on this topic

Ordered by study design first, then recency. The full set is listed in the references below.

  1. Effect of Ambient Temperature on Electric Vehicles’ Energy Consumption and Range: Model Definition and Sensitivity Analysis Based on Nissan Leaf Data — Iora P, Tribioli L, 2019, journal article
  2. Electric Vehicle Energy Consumption Modelling and Prediction Based on Road Information — Wang J, Besselink I, Nijmeijer H, 2015, journal article
  3. Machine learning-based uncertainty quantification for energy consumption and driving range estimation in electric cargo vehicles — Gandhi M, Chaudhari A, 2026, journal article
  4. Estimation of Energy Consumption in Battery-electric Motorcycles Using a Virtual Vehicle Model and the Development of a Customized Measurement System — Göntér Á, Sipos T, 2026, journal article
  5. Integrated model construction for state of charge estimation in electric vehicle lithium batteries — Liu Y, Dun W, 2024, journal article
  6. Simulation model for rendering and analyzing the prediction of electric vehicle energy consumption in Matlab/Simulink — Janković F, Mujović S, 2023, journal article
  7. Energy Cost Analysis and Operational Range Prediction Based on Medium- and Heavy-Duty Electric Vehicle Real-World Deployments across the United States — Qiu Y, Dobbelaere C, Song S, 2023, journal article
  8. Electric Vehicle Range Estimation Using Regression Techniques — Ahmed M, Mao Z, Zheng Y et al., 2022, journal article
  9. Research on Establishment of Vehicle Energy Distribution Model and Energy Consumption Optimization Based on Electric Hybrid System — Liang P, He H, Cui H et al., 2021, journal article
  10. Rapid Evaluation Method for Accuracy of Range Estimation of Pure Electric Vehicle Range Estimation Based on CLTC-P — Dai T, Zhou B, Zhang Y et al., 2021, journal article
How much research is there on range estimation?
14 publications are indexed here, of which 0 are trials and 0 are syntheses.
Does more research mean a stronger conclusion?
No. Composition matters more than volume — five randomised trials support a claim far better than fifty commentaries, and citation counts do not distinguish between them.
How current is this?
The most recent paper indexed here is from 2026. The set is refreshed weekly from PubMed and Crossref.
Why does this page not tell me the answer?
Because summarising a literature into a conclusion requires reading it, and doing that automatically is how confident nonsense gets published. This page tells you how much weight a conclusion could bear; the articles on this site do the interpreting.

References

Every citation below links to the original peer-reviewed record on PubMed or via DOI. Nothing here is a substitute for medical advice.

  1. Effect of Ambient Temperature on Electric Vehicles’ Energy Consumption and Range: Model Definition and Sensitivity Analysis Based on Nissan Leaf Data Iora P, Tribioli L · World Electric Vehicle Journal · 2019 · Journal article DOI
  2. Electric Vehicle Energy Consumption Modelling and Prediction Based on Road Information Wang J, Besselink I, Nijmeijer H · World Electric Vehicle Journal · 2015 · Journal article DOI
  3. Machine learning-based uncertainty quantification for energy consumption and driving range estimation in electric cargo vehicles Gandhi M, Chaudhari A · Energy Informatics · 2026 · Journal article DOI
  4. Estimation of Energy Consumption in Battery-electric Motorcycles Using a Virtual Vehicle Model and the Development of a Customized Measurement System Göntér Á, Sipos T · Periodica Polytechnica Transportation Engineering · 2026 · Journal article DOI
  5. Integrated model construction for state of charge estimation in electric vehicle lithium batteries Liu Y, Dun W · Energy Informatics · 2024 · Journal article DOI
  6. Energy Cost Analysis and Operational Range Prediction Based on Medium- and Heavy-Duty Electric Vehicle Real-World Deployments across the United States Qiu Y, Dobbelaere C, Song S · World Electric Vehicle Journal · 2023 · Journal article DOI
  7. Simulation model for rendering and analyzing the prediction of electric vehicle energy consumption in Matlab/Simulink Janković F, Mujović S · ETF Journal of Electrical Engineering · 2023 · Journal article DOI
  8. Electric Vehicle Range Estimation Using Regression Techniques Ahmed M, Mao Z, Zheng Y, et al. · World Electric Vehicle Journal · 2022 · Journal article DOI
  9. Rapid Evaluation Method for Accuracy of Range Estimation of Pure Electric Vehicle Range Estimation Based on CLTC-P Dai T, Zhou B, Zhang Y, et al. · E3S Web of Conferences · 2021 · Journal article DOI
  10. Research on Establishment of Vehicle Energy Distribution Model and Energy Consumption Optimization Based on Electric Hybrid System Liang P, He H, Cui H, et al. · World Electric Vehicle Journal · 2021 · Journal article DOI
  11. Development of Hybrid Vehicle Energy Consumption Model for Transportation Applications—Part II: Traction Force-Speed Based Energy Consumption Modeling Pitanuwat S, Aoki H, IIzuka S, et al. · World Electric Vehicle Journal · 2019 · Journal article DOI
  12. Online Prediction of Battery Electric Vehicle Energy Consumption Wang J, Besselink I, Nijmeijer H · World Electric Vehicle Journal · 2016 · Journal article DOI
  13. Model-Based Remaining Driving Range Prediction in Electric Vehicles by using Particle Filtering and Markov Chains Oliva J, Weihrauch C, Bertram T · World Electric Vehicle Journal · 2013 · Journal article DOI
  14. Energy Consumption Prediction of a Vehicle along a User-Specified Real-World Trip Karbowski D, Pagerit S, Calkins A · World Electric Vehicle Journal · 2012 · Journal article DOI