交通运输系统工程与信息

交通运输系统工程与信息 ›› 2026, Vol. 26 ›› Issue (3): 36-46.DOI: 10.16097/j.cnki.1009-6744.2026.03.004

• 青年基金项目成果 • 上一篇    下一篇

面向全生命周期成本最优的电气化公路系统参数配置研究

周子伟1 ，方浩文1 ，徐焱*1 ，刘振东2 ，黄成彬1 ，屈海洋3 ，刘文哲3   

  1. 1. 昆明理工大学，交通工程学院，昆明650500；2.瑞典皇家理工学院，工程力学系，斯德哥尔摩10044,瑞典； 3. 中车株洲电力机车有限公司，湖南株洲412001
  • 收稿日期:2026-01-22 修回日期:2026-03-25 接受日期:2026-04-17 出版日期:2026-06-25 发布日期:2026-06-22
  • 作者简介:周子伟（1995— ），男，重庆开州人，讲师，博士。
  • 基金资助:
    国家自然科学基金青年科学基金 (12302048)；云南省基础研究计划项目 (202301BE070001-042)。

Electric Road System Parameter Configuration with Life Cycle Cost Optimization

ZHOU Ziwei1, FANG Haowen1, XU Yan*1, LIU Zhendong2, HUANG Chengbin1, QU Haiyang3, LIU Wenzhe3   

  1. 1. School of Traffic Engineering, Kunming University of Science and Technology, Kunming 650500, China; 2. Department of Engineering Mechanics, KTH Royal Institute of Technology, Stockholm 10044, Sweden; 3. CRRC Zhuzhou Electric Locomotive Co Ltd, Zhuzhou 412001, Hunan, China
  • Received:2026-01-22 Revised:2026-03-25 Accepted:2026-04-17 Online:2026-06-25 Published:2026-06-22
  • Supported by:
    Young Scientists Fund of the National Natural Science Foundation of China (12302048)；Yunnan Fundamental Research Projects (202301BE070001-042)。

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摘要： 为降低电气化公路系统中全程架设接触网模式的高额基建成本，本文针对“分段架设接触网+车载储能”技术构建全生命周期成本优化模型。模型综合考虑基础设施建设、车辆购置、能源消耗、系统维护及电池更换成本，以电池容量、充放电倍率和接触网占比为关键决策变量，采用粒子群优化算法进行多周期动态寻优。以典型煤炭货运场景为例，在电池容量50~150Ah和充放电倍率1~3C条件下分析不同运营年限的最优参数配置。研究结果表明，系统最优配置随运营年限呈显著动态变化：在25~30a运营周期内，高电池容量（150Ah）与高充放电倍率（3C）组合更具经济性，对应接触网占比约43%；当运营周期延长至40~45 a时，最优策略转向低电池容量（50Ah）与低充放电倍率（1C），并将接触网占比提升至约87%，以降低电池更换成本并发挥基础设施长期分摊效应。敏感性分析表明，电池单价与线路建设成本对系统配置影响显著，当电池价格上升20%或线路建设成本下降20%时，最优接触网占比均提升至约87%。研究结果可为不同运营周期下电气化公路系统的规划与投资决策提供参考。

关键词: 交通经济, 最优配置参数, 粒子群算法, 电气化公路, 全生命周期成本, 分段架设接触网

Abstract: To reduce the high infrastructure cost of the full-line catenary installation mode in electric road systems, this paper develops a life cycle cost optimization model for the "segmented catenary installation + on-board energy storage" technology. The model comprehensively considers the costs of infrastructure construction, vehicle purchase, energy consumption, system maintenance and battery replacement. The model uses battery capacity, charge-discharge rate and catenary proportion as the key decision variables, and adopts the particle swarm optimization algorithm for multi-period dynamic optimization. Taking a typical coal freight scenario as an example, the study analyzes the optimal parameter configuration for different operational lifespans under the conditions of battery capacity ranging from 50 Ah to 150 Ah and charge-discharge rate from 1 C to 3 C. The results show that the optimal system configuration presents a significant dynamic variation with the operational lifespan: in the 25~30 years operational cycle, the combination of high battery capacity (150 Ah) and high charge-discharge rate (3 C) is more economical, corresponding to a catenary proportion of about 43%. When the operational cycle is extended to 40~45 years, the optimal strategy shifts to low battery capacity (50 Ah) and low charge-discharge rate (1 C), with the catenary proportion increased to about 87%, so as to reduce battery replacement costs and exert the long-term amortization effect of infrastructure. Sensitivity analysis indicates that battery unit price and line construction cost have a significant impact on system configuration: when the battery price rises by 20% or the line construction cost drops by 20%, the optimal catenary proportion both increases to about 87%. The research results can provide a reference for the planning and investment decision-making of electric road systems under different operational cycles.

Key words: transportation economy, optimal parameter configuration, particle swarm optimization, electric road system, life-cycle cost, segmented installation of overhead catenary

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