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Economic Analysis on Value Chain of Taxi Fleet with Battery-Swapping Mode Using Multiobjective Genetic Algorithm

机译：基于多目标遗传算法的换乘出租车舰队价值链的经济学分析。

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摘要

This paper presents an economic analysis model on value chain of taxi fleet with battery-swapping mode in a pilot city. In the model, economic benefits of charging-swapping station group, taxi company, and taxi driver in the region have been taken into consideration. Thus, the model is a multiobjective function and multiobjective genetic algorithm is used to solve this problem. According to the real data collected from the pilot city, the multiobjective genetic algorithm is tested as an effective method to solve this problem. Furthermore, the effects of price of electricity, price of battery package, life cycle of battery package, cost of battery-swapping devices and infrastructure, and driving mileage per day on the benefits of value holders are analyzed, which provide theoretical and practical reference for the deployment of electric vehicles, for the national subsidy criteria adjusment, technological innovation instruction, commercial mode selection, and infrastructure construction.
机译：本文提出了一个具有电池交换模式的试点城市出租车车队价值链的经济分析模型。在模型中，已考虑了该区域的充电交换站组，出租车公司和出租车司机的经济利益。因此，该模型是一个多目标函数，并且使用多目标遗传算法来解决该问题。根据从试点城市收集的真实数据，测试了多目标遗传算法作为解决该问题的有效方法。此外，分析了电价，电池组价格，电池组寿命，电池交换设备和基础设施的成本以及每天行驶里程对价值持有者利益的影响，为价值持有者的利益提供理论和实践参考。电动汽车的部署，用于国家补贴标准的裁定，技术创新指导，商业模式选择和基础设施建设。

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  • 来源
    《Mathematical Problems in Engineering》 |2012年第12期|175912.1-175912.15|共15页
  • 作者

    Guobao Ning; Zijian Zhen; Peng Wang; Yang Li; Huaixian Yin;

  • 作者单位

    School of Automotive Studies, Tongji University, No. 4800 Cao'an Road, Shanghai 201804, China;

    The High Technology Research and Development Center, No. 1 Sanlihe Road, Beijing 100044, China;

    China Automotive Engineering Research Institute Co., Ltd., Xinghuo Mansion, Fengtai District, Beijing 100071, China;

    Potevio New Energy Co., Ltd., No. 6 Haidian North Second Street, Haidian District, Beijing 100080, China;

    Qingdao University, No. 308 Ningxia Road, Qingdao 266071, China;

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