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    When to Charge a Small-Range Battery Electric Vehicle: Refining Charging Strategies Using a Scenario-Based Approach

    Source: Journal of Transportation Engineering, Part A: Systems:;2022:;Volume ( 148 ):;issue: 009::page 04022067
    Author:
    Qi Zhang
    ,
    Jie Yang
    ,
    Zhiyuan Liu
    DOI: 10.1061/JTEPBS.0000716
    Publisher: ASCE
    Abstract: Small-range battery electric vehicles (BEVs), with driving ranges less than 200 km, are susceptible to charging defects. This study applied a scenario-based approach by modeling a cost function to recommend an optimal charging strategy for small-range BEV users. The proposed cost function considers the operating and range limitation costs of BEVs. The charging threshold, which reflects the charging preference of a user, is adjusted using the cost function and analyzed by comparing different scenarios using real data collected from Shanghai, China. The simulation results indicate that every 2.5 times increase in the charging threshold results in a decrease of approximately 48.9% in the charging times and a 10% reduction in the electrified proportion of a journey. For electrified proportions below 85%, small-range BEVs are no longer an economical option over internal combustion engine vehicles. Moreover, the optimal charging threshold is 35%–41% for BEVs with a 170 km range, and the corresponding daily ownership costs are more reasonable than those of medium and long-range BEVs. The scenario analysis of the availability of the charging piles and battery price further demonstrates the economic advantages of small-range BEVs. These results provide instructible charging strategies for small-range BEV users to alleviate the shortcomings of the range limitations and frequent charging.
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      When to Charge a Small-Range Battery Electric Vehicle: Refining Charging Strategies Using a Scenario-Based Approach

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4286905
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    • Journal of Transportation Engineering, Part A: Systems

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    contributor authorQi Zhang
    contributor authorJie Yang
    contributor authorZhiyuan Liu
    date accessioned2022-08-18T12:36:51Z
    date available2022-08-18T12:36:51Z
    date issued2022/07/14
    identifier otherJTEPBS.0000716.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4286905
    description abstractSmall-range battery electric vehicles (BEVs), with driving ranges less than 200 km, are susceptible to charging defects. This study applied a scenario-based approach by modeling a cost function to recommend an optimal charging strategy for small-range BEV users. The proposed cost function considers the operating and range limitation costs of BEVs. The charging threshold, which reflects the charging preference of a user, is adjusted using the cost function and analyzed by comparing different scenarios using real data collected from Shanghai, China. The simulation results indicate that every 2.5 times increase in the charging threshold results in a decrease of approximately 48.9% in the charging times and a 10% reduction in the electrified proportion of a journey. For electrified proportions below 85%, small-range BEVs are no longer an economical option over internal combustion engine vehicles. Moreover, the optimal charging threshold is 35%–41% for BEVs with a 170 km range, and the corresponding daily ownership costs are more reasonable than those of medium and long-range BEVs. The scenario analysis of the availability of the charging piles and battery price further demonstrates the economic advantages of small-range BEVs. These results provide instructible charging strategies for small-range BEV users to alleviate the shortcomings of the range limitations and frequent charging.
    publisherASCE
    titleWhen to Charge a Small-Range Battery Electric Vehicle: Refining Charging Strategies Using a Scenario-Based Approach
    typeJournal Article
    journal volume148
    journal issue9
    journal titleJournal of Transportation Engineering, Part A: Systems
    identifier doi10.1061/JTEPBS.0000716
    journal fristpage04022067
    journal lastpage04022067-11
    page11
    treeJournal of Transportation Engineering, Part A: Systems:;2022:;Volume ( 148 ):;issue: 009
    contenttypeFulltext
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