考虑车线匹配的电动公交多线路联合优化建模

doi:10.16097/j.cnki.1009-6744.2023.04.015

交通运输系统工程与信息 ›› 2023, Vol. 23 ›› Issue (4): 147-154.DOI: 10.16097/j.cnki.1009-6744.2023.04.015

考虑车线匹配的电动公交多线路联合优化建模

段梦媛，奇格奇，关伟^*，徐笑涵

北京交通大学，综合交通运输大数据应用技术交通运输行业重点实验室，北京 100044

收稿日期:2023-03-15 修回日期:2023-04-16 接受日期:2023-04-18 出版日期:2023-08-25 发布日期:2023-08-21
作者简介:段梦媛(1994- )，女，湖北襄阳人，博士生
基金资助:
国家自然科学基金(91746201, 71621001)

Integrated Optimization of Multi-route for Battery Electric Buses Considering Vehicle and Line Matching

DUAN Meng-yuan, QI Ge-qi, GUAN Wei^*, XU Xiao-han

Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, Beijing 100044, China

Received:2023-03-15 Revised:2023-04-16 Accepted:2023-04-18 Online:2023-08-25 Published:2023-08-21
Supported by:
National Natural Science Foundation of China (91746201, 71621001)

摘要/Abstract

摘要： 为研究电动公交的运营优化问题，本文考虑电池容量损耗，以车辆和线路匹配、车辆和电池的更新、车辆服务的车次数为决策变量，建立电动公交的生命周期成本优化模型。设计基于滚动时域调度优化方法，采用GUROBI软件对模型进行求解。以多条公交线路运营数据为背景，对模型有效性进行测试。假设决策周期为20年，算例结果分析得出车辆和电池的最优更新方案，车辆和线路的匹配方案，车辆运营的车次数量方案，最优方案的生命周期成本为35.27 × 107 $，车辆和电池更换次数分别为44和239。针对线路工作负荷大小、车辆与线路匹配策略等参数进行灵敏度分析。结果表明：考虑不同线路工作负荷的差异，设计优化的车辆与线路匹配策略可以减少车辆和电池的购置成本，提高电动公交企业运营效益。

关键词: 城市交通, 车辆线路匹配, 电池容量衰减, 滚动时域调度, 全生命周期

Abstract: To study the bus operation optimization problem, this paper establishes a life-cycle cost optimization model for electric buses considering battery capacity degradation, which takes vehicle and line matching, vehicle and battery renewal, and the number of service trips for buses as decision variables. Then we develop a rolling horizon scheduling optimization method and use GUROBI to solve it. With the operational data of multiple bus lines, the validity of the model is tested. Assuming that the planning horizon is 20 years, the optimal renewal scheme for vehicles and batteries, the matching scheme for vehicles and lines, and the number of trips for bus operations are obtained. The optimal scheme's life cycle cost is $35.27 × 107 , and the number of vehicle and battery replacements is 44 and 239, respectively. Based on the sensitivity analysis of different workloads and the matching strategies, the results show that considering the differences in workloads, the matching strategy of buses and lines can reduce the investment cost of vehicles and batteries and improve the operational efficiency of electric bus enterprises.

Key words: urban traffic, bus and line matching, battery capacity degradation, rolling horizon scheduling, life cycle

中图分类号:

U491

段梦媛, 奇格奇, 关伟, 徐笑涵. 考虑车线匹配的电动公交多线路联合优化建模[J]. 交通运输系统工程与信息, 2023, 23(4): 147-154.

DUAN Meng-yuan, QI Ge-qi, GUAN Wei, XU Xiao-han. Integrated Optimization of Multi-route for Battery Electric Buses Considering Vehicle and Line Matching[J]. Journal of Transportation Systems Engineering and Information Technology, 2023, 23(4): 147-154.

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http://www.tseit.org.cn/CN/Y2023/V23/I4/147

参考文献

[1] REDMER A. Strategic vehicle fleet management: A joint solution of make-or-buy, composition and replacement problems[J]. Journal of Quality in Maintenance Engineering, 2022, 28(2): 327-349.

[2] LI L, LO H K, XIAO F, et al. Mixed bus fleet management strategy for minimizing overall and emissions external costs[J]. Transportation Research Part D: Transport and Environment, 2018, 60: 104-118.

[3] ISLAM A, LOWNES N. When to go electric? A parallel bus fleet replacement study[J]. Transportation Research Part D: Transport and Environment, 2019, 72: 299-311.

[4] 唐春艳, 李小雨. 多车型纯电动公交车使用下的混合车队替换优化[J]. 交通运输系统工程与信息, 2021, 21 (2): 151-157. [TANG C Y, LI X Y. Optimizing mixed transit fleet replacement with multi-type battery electric buses[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(2): 151-157.]

[5] 马晓磊, 闫昊阳, 缪然. 考虑财政补贴的电动公交车队置换优化模型[J]. 交通运输系统工程与信息,2021, 21(3): 200-205. [MA X L, YAN H Y, MIAO R. Optimization model of electric bus fleet replacement considering financial subsidies[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(3): 200-205.]

[6] DELUCCHI M A, LIPMAN T E. An analysis of the retail and lifecycle cost of battery-powered electric vehicles[J]. Transportation Research Part D: Transport and Environment, 2001, 6(6): 371-404.

[7] 吴添, 欧训民, 林成涛. 从消费者的视角分析纯电动城市客车的生命周期成本[J]. 汽车工程, 2012, 34(12): 1150-1154. [WU T, OU X M, LIN C T. Analysis on the whole-life-cycle cost of battery electric city-bus from consumer perspective[J]. Automotive Engineering, 2012, 34(12): 1150-1154.]

[8] WANG J, KANG L, LIU Y. Optimal scheduling for electric bus fleets based on dynamic programming approach by considering battery capacity fade[J]. Renewable and Sustainable Energy Reviews, 2020, 130 (2): 109978.

[9] ZHANG L, ZENG Z, QU X. On the role of battery capacity fading mechanism in the lifecycle cost of electric bus fleet[J]. IEEE Transactions on Intelligent Transportation Systems, 2021, 22(4): 2371-2380.

[10] BOUDART J, FIGLIOZZI M. Key variables affecting decisions of bus replacement age and total costs[J]. Transportation Research Record Journal of the Transportation Research Board, 2012, 2274(2274): 109- 113.

[11] CHAND S, HSU V N, SETHI S. Forecast, solution, and rolling horizons in operations management problems: A classified bibliography[J]. Manufacturing and Service Operations Management, 2002, 4(1): 25-43.

[12] SAHIN F, NARAYANAN A, ROBINSON E P. Rolling horizon planning in supply chains: Review, implications and directions for future research[J]. International Journal of Production Research, 2013, 51(18): 5413- 5436.

[13] 王冰, 席裕庚, 谷寒雨. 一类单机动态调度问题的改进滚动时域方法[J]. 控制与决策, 2005(3): 257-260, 265. [WANG B, XI Y G, GU H Y. An improved rolling horizon procedure for single-machine scheduling with release times[J]. Control and Decision, 2005(3): 257- 260, 265.]

[14] TANG X, LIN X, HE F. Robust scheduling strategies of electric buses under stochastic traffic conditions[J]. Transportation Research Part C: Emerging Technologies, 2019, 105(8): 163-182.

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考虑车线匹配的电动公交多线路联合优化建模

Integrated Optimization of Multi-route for Battery Electric Buses Considering Vehicle and Line Matching

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