nav emailalert searchbtn searchbox tablepage yinyongbenwen piczone journalimg journalInfo journalinfonormal searchdiv searchzone qikanlogo popupnotification paper paperNew
2021, 04, v.19;No.74 24-35+117
考虑排放约束的电动汽车混行交通路网均衡模型
基金项目(Foundation): 国家自然科学基金项目(71971162);; 上海市科委重点项目(19DZ1209402)
邮箱(Email):
DOI: 10.19961/j.cnki.1672-4747.2021.03.022
摘要:

随着电动汽车的推广和使用,电动汽车与燃油汽车在路网中交互运行,形成了混行交通环境。本文构建考虑排放约束和途中充电的电动汽车混行交通路网均衡模型。首先,分别定义了电动汽车用户与燃油汽车用户的出行成本函数,其中电动汽车用户出行成本包含行驶时间、充电排队时间及充电时长。其次,构建了考虑排放约束的混行交通路网均衡模型,证明了解的唯一性,推导了模型对应的KKT条件,且与Wardrop第一原理等价。然后,将均衡模型表述为包括用户均衡条件、排放约束、守恒约束的互补性条件形式,通过引入间隙函数,进一步将其转化为等价的无约束最优化问题,并利用基于梯度的算法进行求解。最后,通过算例验证了均衡模型及算法的有效性,结果表明:(1)考虑路网排放约束将影响混行交通量和充电站充电流量空间分布;(2)总需求和电动汽车渗透率不变的条件下,提高减排力度会导致路网总行程时间的增加;(3)给定减排力度时,可以确定路网总行程时间最小时对应的电动汽车最优渗透率。

Abstract:

With the promotion and use of electric vehicles, electric and fuel vehicles operate in a road network interactively, thus forming a mixed traffic environment. In this study, a mixed traffic network model that considers emission constraints is developed. First, the utility functions of users of battery electric and fuel vehicles are defined, with travel time, charging queuing time, and charging time taken as utility components for users of battery electric vehicles. A corresponding mixed traffic network equilibrium model is then established. We prove the uniqueness of the model solution and derive Karush-Kuhn-Tucker conditions corresponding to the mixed traffic network model, which is proven to be equivalent to Wardrop's first principle. Third, the equilibrium model is transformed into complementary conditions that include user equilibrium conditions as well as emission and conservation constraints. A gap function is introduced and reformulated into an equivalent unconstrained optimization problem, which is then solved by a gradientbased algorithm. Finally, the effectiveness of both the model and algorithm are verified through an example network application. The results are as follows.(1) Road network emission constraints influence the spatial distribution of mixed traffic flows and charging demands;(2) An increase in emission reductions leads to an increase in total network travel time;(3) Given emission reductions, the optimal penetration rate of battery electric vehicles corresponding to the minimum total network travel time can be determined.

参考文献

[1]马建,刘晓东,陈轶嵩,等.中国新能源汽车产业与技术发展现状及对策[J].中国公路学报, 2018, 31(8):1-19.

[2]杨文国,高自友.考虑环境因素的广义用户平衡和广义系统最优配流模型[J].中国公路学报, 2003, 16(4):73-77.

[3]熊伟,严新平.基于路径的算法求解考虑排放的交通分配模型[J].交通运输工程学报, 2009, 9(3):71-75, 97.

[4] XU X, CHEN A, CHENG L. Reformulating environmentally constrained traffic equilibrium via a smooth gap function[J].International Journal of Sustainable Transportation, 2015,9(6):419-430.

[5]张鑫,王京梅,吴珂琪,等.低碳排放约束下交通网络均衡分析研究[C]//中国智能交通协会第十三届中国智能交通年会大会论文集.北京:中国智能交通协会,2018:44-53.

[6]《中国公路学报》编辑部.中国汽车工程学术研究综述·2017[J].中国公路学报, 2017, 30(6):1-197.

[7]马建,张大禹,赵轩,等.基于随机加权自适应容积卡尔曼的电池SOC估计[J].中国公路学报, 2019, 32(11):234-244.

[8] JIANG N, XIE C, WALLER T. Path-constrained traffic assignment:model and algorithm[J]. Transportation Research Record Journal of the Transportation Research Board, 2012, 2283:25-33.

[9] HE F, YIN Y, LAWPHONGPANICH S. Network equilibrium models with battery electric vehicles[J]. Transportation Research Part B:Methodological, 2014, 67:306-319.

[10] WANG T G, XIE C, XIE J, et al. Path-constrained traffic assignment:a trip chain analysis under range anxiety[J].Transportation Research Part C:Emerging Technologies,2016, 68:447-461.

[11]谢驰,白婷,王同根.里程焦虑下的电动汽车交通网络均衡[J].中国科技论文, 2017, 12(19):2161-2165, 2171.

[12] XIE C, WANG T G, PU X, et al. Path-constrained traffic assignment:modeling and computing network impacts of stochastic range anxiety[J]. Transportation Research,2017, 103:136-157.

[13] JIANG N, XIE C. Computing and analyzing mixed equilibrium network flows with gasoline and electric vehicles[J]. Computer Aided Civil&Infrastructure Engineering, 2014, 29(8):626-641.

[14] JIANG N, XIE C, DUTHIE J C, et al. A Network equilibrium analysis on destination, route and parking choices with mixed gasoline and electric vehicular flows[J]. EURO Journal on Transportation and Logistics,2014, 3(1):55-92.

[15]杨扬,姚恩建,王梅英,等.电动汽车混入条件下的随机用户均衡分配模型[J].中国公路学报, 2015, 28(9):91-97.

[16]叶露,郭倩芸,倪舒晨,等.混合交通网络充电站选址模型[J].交通运输工程与信息学报, 2019, 17(4):97-104.

[17] CEN X, LO H K, LI L, et al. Modeling electric vehicles adoption for urban commute trips[J]. Transportation Research Part B:Methodological, 2018, 117:431-454.

[18] HUANG Y, KOCKELMAN K. Electric vehicle charging station locations:elastic demand, station congestion, and network equilibrium[J]. Transportation Research Part D:Transport and Environment, 2020, 78:1-16.

[19] ZHANG X, REY D, WALLER S T, et al. Rangeconstrained traffic assignment with multi-modal recharge for electric vehicles[J]. Networks and Spatial Economics,2019, 19(2):633-668.

[20] FERRO G, MINCIARDI R, ROBBA M. A user equilibrium model for electric vehicles:joint traffic and energy demand assignment[J]. Energy, 2020, 198:1-10.

[21] XU M, MENG Q, LIU K. Network user equilibrium problems for the mixed battery electric vehicles and gasoline vehicles subject to battery swapping stations and road grade constraints[J]. Transportation Research Part B:Methodological, 2017, 99:138-166.

[22] LIU Z, SONG Z. Network user equilibrium of battery electric vehicles considering flow-dependent electricity consumption[J]. Transportation Research Part C:Emerging Technologies, 2018, 95:516-544.

[23]徐若辰,钟任新.基于动态投影系统的带非线性边界约束混行路网均衡模型求解算法[J].科学技术与工程,2019, 19(12):325-332.

[24]张维戈,陈连福,黄彧,等. M/G/k排队模型在电动出租汽车充电站排队系统中的应用[J].电网技术, 2015,39(3):724-729.

[25] ZHANG Y, ALIYA B, ZHOU Y, et al. Shortest feasible paths with partial charging for battery-powered electric vehicles in smart cities[J]. Pervasive and Mobile Computing, 2018, 50:82-93.

[26]李浩,陈浩.考虑充电排队时间的电动汽车混合交通路网均衡[J/OL].吉林大学学报(工学版):1-9[2020-12-17]. https://doi. org/10. 13229/j. cnki. jdxbgxb20200421.

[27] LO H K, CHEN A. Traffic equilibrium problem with route-specific costs:formulation and algorithms[J].Transportation Research Part B:Methodological, 2000,34(6):493-513.

[28]徐建闽.我国低碳交通分析及推进措施[J].城市观察,2010(4):13-20.

[29] NIE Y, ZHANG H M, LEE D H. Models and algorithms for the traffic assignment problem with link capacity constraints[J]. Transportation Research Part B:Methodological,2004, 38:285-312.

①前文已提到,充电函数不完全是线性的,当电量小于80%时,充电量与充电时间成正比;当电量超过80%时,充电效率会迅速降低,起到保护电池的目的。因此本文假设电动汽车用户充电最多充至80%,以满足充电函数线性的假设。

基本信息:

DOI:10.19961/j.cnki.1672-4747.2021.03.022

中图分类号:U491.262

引用信息:

[1]李浩,陈浩,陆续,等.考虑排放约束的电动汽车混行交通路网均衡模型[J],2021,19(04):24-35+117.DOI:10.19961/j.cnki.1672-4747.2021.03.022.

基金信息:

国家自然科学基金项目(71971162);; 上海市科委重点项目(19DZ1209402)

投稿时间:

2021-03-22

投稿日期(年):

2021

终审时间:

2021-07-19

终审日期(年):

2021

审稿周期(年):

1

检 索 高级检索

引用

GB/T 7714-2015 格式引文
MLA格式引文
APA格式引文