This study conducts micro-simulations of electricity consumption for electric vehicles (EVs) using actual GPS trajectory data from commercial diesel vehicles, with the objective of evaluating practical driving range, economic viability based on payback period, and potential CO2 emissions reduction associated with EV adoption. The results indicate that the estimated driving ranges of EVs differ from catalog specifications, as some exceed and others fall short of the stated values. This highlights the necessity of conducting simulation-based assessments under realistic operating conditions. The shortest payback period among the analyzed cases was estimated to be 5.8 years, suggesting that certain commercial EVs can be economically competitive even without subsidies. Additionally, the CO2 reduction potential was quantified at approximately 60%, emphasizing the environmental benefits of transitioning from diesel to electric in commercial logistics operations.

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Cost-Effectiveness and CO2 Reduction of Commercial EV Adoption Based on GPS Trajectory Data

  • Keiichi Ikeda,
  • Katsuya Sakai

摘要

This study conducts micro-simulations of electricity consumption for electric vehicles (EVs) using actual GPS trajectory data from commercial diesel vehicles, with the objective of evaluating practical driving range, economic viability based on payback period, and potential CO2 emissions reduction associated with EV adoption. The results indicate that the estimated driving ranges of EVs differ from catalog specifications, as some exceed and others fall short of the stated values. This highlights the necessity of conducting simulation-based assessments under realistic operating conditions. The shortest payback period among the analyzed cases was estimated to be 5.8 years, suggesting that certain commercial EVs can be economically competitive even without subsidies. Additionally, the CO2 reduction potential was quantified at approximately 60%, emphasizing the environmental benefits of transitioning from diesel to electric in commercial logistics operations.