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Network user equilibrium problems for the mixed battery electric vehicles and gasoline vehicles subject to battery swapping stations and road grade constraints

机译:受电池更换站和道路坡度限制的混合动力电动汽车和汽油汽车的网络用户平衡问题

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There has been growing attention on battery electric vehicles (BEVs) due to their energy efficiency and environmental friendliness. This paper deals with the user equilibrium (UE) problems for the mixed BEVs and traditional gasoline vehicles (GVs) in transportation networks with battery swapping stations and road grade constraints. Under the assumption that electricity consumption rate is not affected by traveling speed or traffic flow, a nonlinear minimization model in terms of path flows is first formulated by incorporating effects of road grade on the electricity consumption rate. The battery swapping action based paths are defined for BEVs in the represented network to facilitate the model building with flow dependent dwell time at the battery swapping stations. The Frank-Wolfe (F-W) algorithm, where descent direction is found by the multi-label method in a pseudo-polynomial time, is adopted to solve the model. Moreover, the aforementioned assumption about the flow independent electricity consumption rate is then relaxed and a system of inequalities has been proposed to formulate the UE conditions. For the nonlinear minimization model, two numerical examples are presented to assess the propose model and algorithm, as well as to analyze the impact of usable battery capacity, BEVs' market share and some attributes of battery swapping stations on the equilibrium link flows and/or swapping flows. The system of inequalities is exactly solved for a small network by path enumeration to demonstrate the non-uniqueness of UE link flow solutions. (C) 2017 Elsevier Ltd. All rights reserved.
机译:由于电池电动车(BEV)的能源效率和环境友好性,因此受到越来越多的关注。本文研究了在具有电池更换站和道路坡度限制的交通网络中混合BEV和传统汽油车(GV)的用户平衡(UE)问题。在假设电耗率不受行驶速度或交通流量影响的情况下,首先通过结合道路坡度对电耗率的影响来建立基于路径流量的非线性最小化模型。在表示的网络中为BEV定义了基于电池交换动作的路径,以促进在电池交换站建立与流量相关的驻留时间的模型。该模型采用Frank-Wolfe(F-W)算法求解,该算法通过伪随机多项式时间的多标签方法找到下降方向。此外,随后放松了关于与流量无关的电耗率的前述假设,并且已经提出了不等式的系统来制定UE条件。对于非线性最小化模型,给出了两个数值示例,以评估提出的模型和算法,并分析可用电池容量,BEV的市场份额以及电池交换站的某些属性对平衡链路流量和/或影响交换流量。通过路径枚举可以很好地解决不小的系统对于一个小型网络的问题,以证明UE链路流解决方案的非唯一性。 (C)2017 Elsevier Ltd.保留所有权利。

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