Impact of ambient temperature on light-duty gasoline vehicle fuel consumption under real-world driving conditions

Abstract

The widening gap between real-world vehicle energy consumption and modeled predictions can be attributed to discrepancies between actual ambient temperatures and assumptions made in laboratory tests. This study collected a detailed, extensive dataset comprising 25,640,666 records of real-world vehicle operating (speed, acceleration, etc.) and fuel consumption data alongside 124,938 hourly meteorological profiles (temperature, relative humidity, etc.). High-resolution fuel consumption rates (FCRs) based on ambient temperature were developed, and adjustment factors were introduced based on ambient temperature and vehicle specific power (VSP) binning. Fuel consumption factors (FCFs) were compared across different temperatures by incorporating VSP distributions and the adjusted FCRs, revealing larger FCFs at extreme temperatures compared to moderate ones. Fuel consumption inventories, both with and without temperature adjustments, were evaluated. The results indicated a 6% underestimation of annual fuel consumption in Beijing when disregarding temperature adjustments. The variation was observed across months (in July and August, underestimations can reach 11%) and across VSP bins (larger impact in low VSP bins). The relationship between FCR and ambient temperature is similar to a quadratic curve, with the lowest consumption occurring at 10 °C–20 °C. The FCF adjustment factor does not vary across speed intervals in cold weather and remains stable at approximately 1.15 at −10 °C, but it drops from 1.25 to 1 as speed increases from 5 to 100 km/h in hot weather. This study underscores the importance of considering ambient temperature in vehicle energy consumption modeling and the necessity of temperature-adjusted approaches for accurate fuel consumption estimations.

Keywords:

• Ambient temperature
• CO₂
• emissions
• fuel consumption
• light-duty gasoline vehicle
• vehicle specific power

Authors contributions

The authors confirm their contribution to the paper as follows: study conception and design: Guohua Song, Pengfei Fan; data collection: Pengfei Fan, Hongyu Lu; Hang Yin, analysis and interpretation of results: Pengfei Fan, Hongyu Lu; draft manuscript preparation: Pengfei Fan, Guohua Song, Hongyu Lu, Zhiqiang Zhai, Yizheng Wu, and Lei Yu. All authors reviewed the results and approved the final version of the manuscript.

Ethics statement

The authors confirm that all the research meets ethical guidelines and adheres to the legal requirements of the study country.

The research primarily involved the analysis of aggregated vehicle operating data and meteorological profiles. This study did not involve direct human or animal subjects, and the data utilized were non-identifiable and publically accessible, ensuring confidentiality and compliance with data privacy norms. Given the nature of the study, involving secondary data analysis where individual participants could not be identified, it was determined that formal ethics approval was not required. This determination aligns with the ethical guidelines for research involving non-identifiable data, ensuring that the study maintained high ethical standards throughout its conduct.

Data availability statement

Datasets related to this article can be found at https://doi.org/10.5281/zenodo.12139111.

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Funding

This research was supported by the Fundamental Research Funds for the Central Universities [#2022YJS058], the National Key R&D Program of China [#2018YFB1600701], the Natural Science Foundation of China (NSFC) [#71871015], and the National Natural Science Foundation of China (NSFC) [#71901018].