Research on energy consumption law and charging strategies design of electric buses

被引:3
作者
Zhang, Zhaosheng [1 ,2 ]
Wang, Ruiyang [1 ,2 ]
Liu, Peng [1 ,2 ]
Wang, Zhenpo [1 ,2 ]
Lin, Ni [1 ,2 ]
Liang, Yiqiang [3 ]
Tang, Chaoyang [3 ]
Xia, Ling [3 ]
机构
[1] Beijing Inst Technol, Natl Engn Res Ctr Elect Vehicles, Beijing 100081, Peoples R China
[2] Beijing Inst Technol, Collaborat Innovat Ctr Elect Vehicles Beijing, Beijing 100081, Peoples R China
[3] Chongqing Changan Automobile Co Ltd, Chongqing 401133, Peoples R China
基金
中国国家自然科学基金;
关键词
Electric bus; Electrification of bus routes; Energy consumption law; Charging strategy; LITHIUM-ION BATTERIES; VEHICLES; MODEL; IMPACT;
D O I
10.1016/j.energy.2025.135327
中图分类号
O414.1 [热力学];
学科分类号
摘要
To address fossil energy scarcity and greenhouse gas emissions, promoting electric buses (EB) has become a key initiative globally. Studying energy consumption law and designing charging strategies for EB are crucial to reducing costs and improving operation quality. In this paper, the energy consumption law is analyzed based on the real operation data of 48 EBs for 6 influencing factors. Several single-factor energy consumption models are proposed and fitted. Relying on data-driven energy consumption estimation under different operational conditions, a multi-condition two-level nested optimization method is proposed to optimize the parameters of charging piles and opportunity charging schedules, aiming to reduce charging piles cost, electricity cost, and delay risks. A case study shows that the proposed method improves the multi-condition comprehensive score by 14.4 % compared to the baseline strategy. While the charging piles cost remains similar, the proposed method significantly reduces electricity cost and delay risks across different conditions.
引用
收藏
页数:24
相关论文
共 48 条
[1]   Electrochemical Impedance Spectroscopy on the Performance Degradation of LiFePO4/Graphite Lithium-Ion Battery Due to Charge-Discharge Cycling under Different C-Rates [J].
Abe, Yusuke ;
Hori, Natsuki ;
Kumagai, Seiji .
ENERGIES, 2019, 12 (23)
[2]   Electric vehicle modelling and energy-efficient routing using particle swarm optimisation [J].
Abousleiman, Rami ;
Rawashdeh, Osamah .
IET INTELLIGENT TRANSPORT SYSTEMS, 2016, 10 (02) :65-72
[3]   Driving behaviour and trip condition effects on the energy consumption of an electric vehicle under real-world driving [J].
Al-Wreikat, Yazan ;
Serrano, Clara ;
Sodre, Jose Ricardo .
APPLIED ENERGY, 2021, 297
[4]  
ARENA, 2021, Next generation electric bus depot
[5]   Aging effect on the variation of Li-ion battery resistance as function of temperature and state of charge [J].
Barcellona, Simone ;
Colnago, Silvia ;
Dotelli, Giovanni ;
Latorrata, Saverio ;
Piegari, Luigi .
JOURNAL OF ENERGY STORAGE, 2022, 50
[6]   Impact of driving characteristics on electric vehicle energy consumption and range [J].
Bingham, C. ;
Walsh, C. ;
Carroll, S. .
IET INTELLIGENT TRANSPORT SYSTEMS, 2012, 6 (01) :29-35
[7]   A parametric study of the energy demands of car transportation: a case study of two competing commuter routes in the UK [J].
Burgess, SC ;
Choi, JMJ .
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, 2003, 8 (01) :21-36
[8]  
Chen Y, 2021, SAE international journal of sustainable transportation. Energy, Environment, and Policy, V2
[9]   Experimental investigation and comparison of energy consumption of electric and conventional vehicles due to the driving pattern [J].
Chlopek, Zdzislaw ;
Lasocki, Jakub ;
Wojcik, Piotr ;
Badyda, Artur J. .
INTERNATIONAL JOURNAL OF GREEN ENERGY, 2018, 15 (13) :773-779
[10]   Energy Consumption Prediction for Electric Vehicles Based on Real-World Data [J].
De Cauwer, Cedric ;
Van Mierlo, Joeri ;
Coosemans, Thierry .
ENERGIES, 2015, 8 (08) :8573-8593