Comparative Sensitivity Analyses of Energy Consumption in Response to Average Speed Between Electric Vehicles and Conventional Vehicles: Case Study in Beijing, China

Xue Lei, Hongyu Lu, Pengfei Fan, Rui Liu (), Songsong Li, Yizheng Wu and Guohua Song ()
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Xue Lei: Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, 3 Shangyuan Cun, Haidian District, Beijing 100044, China
Hongyu Lu: School of Civil and Environmental Engineering, Georgia Institute of Technology, 790 Atlantic Drive, Atlanta, GA 30332, USA
Pengfei Fan: Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, 3 Shangyuan Cun, Haidian District, Beijing 100044, China
Rui Liu: Beijing Capital Highway Development Group Company Limited, 9A, Liuliqiao Nanli, Fengtai District, Beijing 100161, China
Songsong Li: Beijing Capital Highway Development Group Company Limited, 9A, Liuliqiao Nanli, Fengtai District, Beijing 100161, China
Yizheng Wu: Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, 3 Shangyuan Cun, Haidian District, Beijing 100044, China
Guohua Song: Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, 3 Shangyuan Cun, Haidian District, Beijing 100044, China

Energies, 2025, vol. 18, issue 9, 1-23

Abstract: Understanding the sensitivity of vehicle energy consumption to average speed variations is critical for accurately assessing the environmental impacts of urban transportation systems. While the energy consumption patterns of conventional vehicles (CVs) have been extensively studied, the response characteristics of electric vehicles (EVs) and their fundamental differences from CVs remain insufficiently explored. This knowledge gap may lead to misguided policy interventions—for instance, implementing congestion mitigation strategies that may paradoxically increase EV energy demand. To address this research gap, we developed an energy consumption model based on vehicle-specific power (VSP) distribution analysis, calibrated with over 25 million second-by-second driving records from Beijing. The proposed comparative framework systematically evaluates the sensitivity of EV and CV energy consumption across different speed regimes. The results indicated that EV energy use exhibits a distinctive parabolic trend, with high energy use at both low and high speeds, and a notable increase beyond approximately 70 km/h. A case study indicates that, during the pandemic lockdown, which led to a significant increase in average speed, CV energy use generally decreased, whereas EV energy consumption increased. This discrepancy is primarily attributed to differences in energy consumption rates rather than variations in driving behavior, as reflected in VSP distributions.

Keywords: energy consumption; electric vehicles; VSP distribution; sensitivity analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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