Battery-Aware Operation Range Estimation for Terrestrial and Aerial Electric Vehicles

被引:41
|
作者
Baek, Donkyu [1 ]
Chen, Yukai [1 ]
Bocca, Alberto [1 ]
Bottaccioli, Lorenzo [2 ]
Di Cataldo, Santa [1 ]
Gatteschi, Valentina [1 ]
Pagliari, Daniele Jahier [1 ]
Patti, Edoardo [1 ]
Urgese, Gianvito [1 ]
Chang, Naehyuck [3 ]
Macii, Alberto [1 ]
Macii, Enrico [1 ]
Montuschi, Paolo [1 ]
Poncino, Massimo [1 ]
机构
[1] Politecn Torino, Dept Control & Comp Engn, I-10138 Turin, Italy
[2] Politecn Torino, Energy Ctr Lab, I-10138 Turin, Italy
[3] Korea Adv Inst Sci & Technol, Sch Elect Engn, Daejeon 34141, South Korea
基金
新加坡国家研究基金会;
关键词
State of charge; Battery non-ideality; Energy-efficient scheduling; Electric vehicles; Operation range estimation; CHARGE ESTIMATION; STATE; MANAGEMENT; MODELS; SYSTEM;
D O I
10.1109/TVT.2019.2910452
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The range of operations of electric vehicles (EVs) is a critical aspect that may affect the user's attitude toward them. For manned EVs, range anxiety is still perceived as a major issue and recent surveys have shown that one-third of potential European users are deterred by this problem when considering the move to an EV. A similar consideration applies to aerial EVs for commercial use, where a careful planning of the flying range is essential not only to guarantee the service but also to avoid the loss of the EVs due to charge depletion during the flight. Therefore, route planning for EVs for different purposes (range estimation, route optimization) and/or application scenarios (terrestrial, aerial EVs) is an essential element to foster the acceptance of EVs as a replacement of traditional vehicles. One essential element to enable such accurate planning is an accurate model of the actual power consumption. While very elaborate models for the electrical motors of EVs do exist, the motor power does not perfectly match the power drawn from the battery because of battery non-idealities. In this paper, we propose a general methodology that allows to predict and/or optimize the operation range of EVs, by allowing different accuracy/complexity tradeoffs for the models describing the route, the vehicle, and the battery, and taking into account the decoupling between motor and battery power. We demonstrate our method on two use cases. The first one is a traditional driving range prediction for a terrestrial EV; the second one concerns an unmanned aerial vehicle, for which the methodology will be used to determine the energy-optimal flying speed for a set of parcel delivery tasks.
引用
下载
收藏
页码:5471 / 5482
页数:12
相关论文
共 50 条
  • [1] Intelligent Battery-Aware Energy Management System for Electric Vehicles
    Mahmoud, Dina G.
    Elkhouly, Omar A.
    Azzazy, Muhammad
    Alkady, Gehad I.
    Adly, Ihab
    Daoud, Ramez M.
    Amer, Hassanein H.
    ElSayed, Hany
    Guirguis, Mark
    Abdelshafi, Mohamed Gamal
    2019 24TH IEEE INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION (ETFA), 2019, : 1635 - 1638
  • [2] Design and Analysis of Battery-Aware Automotive Climate Control for Electric Vehicles
    Vatanparvar, Korosh
    Al Faruque, Mohammad Abdullah
    ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS, 2018, 17 (04)
  • [3] A Travel Range Estimation Model for Battery Electric Vehicles
    Tseng, Chia-Wei
    Yang, Yao-Tsung
    Chou, Li-Der
    2015 4TH INTERNATIONAL CONFERENCE ON ENERGY AND ENVIRONMENTAL PROTECTION (ICEEP 2015), 2015, : 3132 - 3135
  • [4] Battery-Aware Electric Truck Delivery Route Exploration
    Baek, Donkyu
    Chen, Yukai
    Chang, Naehyuck
    Macii, Enrico
    Poncino, Massimo
    ENERGIES, 2020, 13 (08)
  • [5] Battery-Aware Electric Truck Delivery Route Planner
    Baek, Donkyu
    Chen, Yukai
    Macii, Enrico
    Poncino, Massimo
    Chang, Naehyuck
    2019 IEEE/ACM INTERNATIONAL SYMPOSIUM ON LOW POWER ELECTRONICS AND DESIGN (ISLPED), 2019,
  • [6] Battery-Aware Cooperative Merging Strategy of Connected Electric Vehicles Based on Reinforcement Learning With Hindsight Experience Replay
    Dong, Hanxuan
    Zhang, Hailong
    Ding, Fan
    Tan, Huachun
    Peng, Jiankun
    IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION, 2022, 8 (03) : 3725 - 3741
  • [7] Battery-Aware Energy-Optimal Electric Vehicle Driving Management
    Vatanparvar, Korosh
    Wan, Jiang
    Al Faruque, Mohammad Abdullah
    2015 IEEE/ACM INTERNATIONAL SYMPOSIUM ON LOW POWER ELECTRONICS AND DESIGN (ISLPED), 2015, : 353 - 358
  • [8] Significance of internal battery resistance on the remaining range estimation of electric vehicles
    Enthaler, Achim
    Gauterin, Frank
    2013 INTERNATIONAL CONFERENCE ON CONNECTED VEHICLES AND EXPO (ICCVE), 2013, : 94 - 99
  • [9] Trust in Range Estimation System in Battery Electric Vehicles-A Mixed Approach
    Wang, Jiyao
    Tu, Ran
    Wang, Ange
    He, Dengbo
    IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS, 2024, 54 (03) : 250 - 259
  • [10] Driving range estimation for battery electric vehicles based on driving cycle identification
    Yin, Andong
    Zhao, Han
    Zhou, Bin
    Jiang, Hao
    Lu, Ruigang
    Qiche Gongcheng/Automotive Engineering, 2014, 36 (11): : 1310 - 1315