Abstract
This paper proposes a simulation approach for the optimal driving range of battery electric vehicles (BEVs) by modeling the driving and charging behavior. The driving and charging patterns of BEV users are characterized by reconstructing the daily travel chain based on the practical data collected from Shanghai, China. Meanwhile, interdependent behavioral variables for daily trips and each trip are defined in the daily trip chain. To meet the goal of the fitness of driving range, a stochastic simulation framework is established by the Monte Carlo method. Finally, with consideration of user heterogeneity, the optimal driving range under different charging scenarios is analyzed. The findings include the following. (1) The daily trip chain can be reconstructed through the behavioral variables for daily trips and each trip, and there is a correlation between the variables examined by the copula function. (2) Users with different daily travel demand have a different optimal driving range. When choosing a BEV, users are recommended to consider that the daily vehicle kilometers traveled are less than 34% of the battery driving range. (3) Increasing the charging opportunity and charging power is more beneficial to drivers who are characterized by high daily travel demand. (4) On the premise of meeting travel demand, the beneficial effects of increased fast-charging power will gradually decline.
Highlights
Battery electric vehicles (BEVs) have the outstanding advantages in zero tailpipe emissions, low noise, convenient maintenance, and high energy conversion efficiency. e deployment of BEVs helps to reduce oil dependence, improve air quality, and reduce pollutions and greenhouse gas emissions [1]
Data Description. is study makes use of a rich database collected from 50 BEVs over a period of 4–12 months. e dataset is provided by Shanghai Electric Vehicles Data Center (SHEVDC) that is developed to remotely monitor electric vehicles driven across the city. e 50 BEVs, used as personal vehicles, are with the same model of Roewe E50, which is a pure electric passenger car with a 22.4 kW·h battery pack and a claimed driving range of 170 km under NEDC conditions [25]
The charging power of Electric Vehicle Supply Equipment (EVSE) is getting bigger, even more than 100 kW, it takes a long time to spread to the average drivers and to apply to each BEV model [34,35]
Summary
Battery electric vehicles (BEVs) have the outstanding advantages in zero tailpipe emissions, low noise, convenient maintenance, and high energy conversion efficiency. e deployment of BEVs helps to reduce oil dependence, improve air quality, and reduce pollutions and greenhouse gas emissions [1]. Battery electric vehicles (BEVs) have the outstanding advantages in zero tailpipe emissions, low noise, convenient maintenance, and high energy conversion efficiency. E deployment of BEVs helps to reduce oil dependence, improve air quality, and reduce pollutions and greenhouse gas emissions [1]. Promoting the development of BEVs is considered as one of the promising solutions for the treatment of severe air pollution in metropolises [2]. Compared to the conventional internal combustion engine vehicles (ICEV), BEVs have a shorter driving range, generally 150 km–400 km. The long driving range design helps to alleviate the user’s range anxiety, it results in a higher expenditure on purchase and simultaneously, the affordability and cost-effectiveness is lowered [8]. Optimizing driving range of BEVs based on users’ daily travel demand is one of the feasible ways to solve this problem, and it is the direction of breakthrough for this paper
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