Management of Kinetic and Electric Energy in Heavy Trucks

被引:17
|
作者
Hellstrom, Erik [1 ]
Aslund, Jan [1 ]
Nielsen, Lars [1 ]
机构
[1] Linkoping Univ, Dept Elect Engn, Div Vehicular Syst, Linkoping, Sweden
关键词
D O I
10.4271/2010-01-1314
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
Hybridization and velocity management are two important techniques for energy efficiency that mainly have been treated separately. Here they are put in a common framework that from the hybridization perspective can be seen as an extension of the equivalence factor idea in the well known strategy ECMS. From the perspective of look-ahead control, the extension is that energy can be stored not only in kinetic energy, but also electrically. The key idea is to introduce more equivalence factors in a way that enables efficient computations, but also so that the equivalence factors have a physical interpretation. The latter fact makes it easy to formulate a good residual cost to be used at the end of the look-ahead horizon. The formulation has different possible uses, but it is here applied on an evaluation of the size of the electrical system. Previous such studies, for e.g. ECMS, have typically used a driving cycle, i.e. a fix velocity profile, but here the extra freedom to choose an optimal driving pattern is added.
引用
收藏
页码:1152 / 1163
页数:12
相关论文
共 50 条
  • [41] Research on the braking energy reuse management strategy of hybrid electric mining trucks based on motor load rate
    Wang, Yilin
    Yang, Weiwei
    Zhang, Wenming
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2024, 238 (07) : 1951 - 1963
  • [42] Predictive Kinetic Energy Management for Large Electric Vehicles using Radar Information
    Yoon, DoHyun Daniel
    Ayalew, Beshah
    Ivanco, Andrej
    Chen, Yanchen
    2020 IEEE CONFERENCE ON CONTROL TECHNOLOGY AND APPLICATIONS (CCTA), 2020, : 82 - 87
  • [43] ADMM applied to energy management of ancillary systems in trucks
    Nilsson, Magnus
    Johannesson, Lars
    Askerdal, Mikael
    2015 AMERICAN CONTROL CONFERENCE (ACC), 2015, : 3459 - 3466
  • [44] Energy and Lifetime Management for Fuel Cell Powered Trucks
    Pell, Johannes
    Schörghuber, Christoph
    ATZheavy Duty Worldwide, 2020, 13 (04) : 42 - 47
  • [45] A Predictive Energy Management Strategies for Mining Dump Trucks
    Yu Y.
    Wang Y.
    Li Q.
    Jiao B.
    Energy Engineering: Journal of the Association of Energy Engineering, 2024, 121 (03): : 769 - 788
  • [46] Saving Energy through Predictive Control of Longitudinal Dynamics of Heavy Trucks
    Kock, Peter
    Welfers, Hans-Josef
    Passenberg, B.
    Gnatzig, S.
    Stursberg, O.
    Ordys, A. W.
    ENERGIEEINSPARUNG DURCH ELEKTRONIK IM FAHRZEUG, 2008, 2033 : 53 - +
  • [47] Saving energy through predictive control of longitudinal dynamics of heavy trucks
    MAN Nutzfahrzeuge AG, Kingston University, London, United Kingdom
    不详
    不详
    不详
    VDI Ber., 2008, 2033 (53-67):
  • [48] A Research on Hybrid Energy Storage System for Battery Electric Mining Trucks
    Zhang W.
    Yang J.
    Zhang W.
    Ma F.
    Qiche Gongcheng/Automotive Engineering, 2019, 41 (06): : 641 - 646and653
  • [49] Optimal route selection for electric delivery trucks for the utilization of renewable energy
    Ueda, Kazuki
    Morita, Hiroshi
    Ohta, Yutaka
    Iwata, Akihiro
    Journal of Japan Industrial Management Association, 2024, 75 (02) : 37 - 48
  • [50] Optimization of Power-System Parameters and Energy-Management Strategy Research on Hybrid Heavy-Duty Trucks
    Zhou, Yongjian
    Yang, Rong
    Zhang, Song
    Lan, Kejun
    Huang, Wei
    ENERGIES, 2023, 16 (17)