Optimal Control of Energy Flow between Electrified Auxiliaries and Powertrain in Hybrid-Electric Heavy-Duty Vehicles

被引:0
|
作者
Dellermann, Matthias [1 ]
Gehring, Ottmar [1 ]
Zirn, Oliver [2 ]
机构
[1] Daimler Truck AG, Adv Engn Mechatron Syst, Stuttgart, Germany
[2] Esslingen Univ Appl Sci, Automot Engn Fac, Esslingen, Germany
关键词
MANAGEMENT; TRUCKS; SYSTEMS; LOADS;
D O I
10.23919/acc45564.2020.9147635
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Predictive control strategies are state of the art in hybrid vehicles today. In this contribution, an optimal control strategy for a 48V powernet of a heavy-duty long-haul truck is investigated. A holistic approach is presented to control the power supply of actuatable electrified auxiliaries along with the common hybrid-electric driving functions. As a consequence, numerous state-control-combinations have to be calculated. To handle this computational effort the presented method utilizes heuristic information about the driven route. Thereby, the route is segmented into classes of related power demand. Subsequently, Dynamic Programming is applied to solve the optimal control problem. As example for an electrified auxiliary the compressor of the air-condition is chosen. A baseline control strategy for a reactive 48V system is compared to the optimal solution based on simulations. The features and use cases of the optimal control are discussed. It will be shown that applying the optimal control approach for the 48V system with knowledge about the whole route results in additional benefit in fuel consumption.
引用
收藏
页码:4161 / 4168
页数:8
相关论文
共 50 条
  • [21] Energy conversion efficiency of hybrid electric heavy-duty vehicles operating according to diverse drive cycles
    Banjac, Titina
    Trenc, Ferdinand
    Katrasnik, Tomaz
    [J]. ENERGY CONVERSION AND MANAGEMENT, 2009, 50 (12) : 2865 - 2878
  • [22] Energy conversion and optimal energy management in diesel-electric drivetrains of hybrid-electric vehicles
    Lyshevski, SE
    [J]. ENERGY CONVERSION AND MANAGEMENT, 2000, 41 (01) : 13 - 24
  • [23] Energy Efficient Platooning of Connected Electrified Vehicles Enabled by a Mixed Hybrid Electric Powertrain Architecture
    Yi, Chenyu
    Hofmann, Heath
    Epureanu, Bogdan I.
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (11) : 20383 - 20397
  • [24] Energy Management of a Dual-engine System for Hybrid Heavy-duty Vehicles
    Hu, Jiayi
    Song, Ziyou
    Li, Jianqiu
    Hu, Zunyan
    Xu, Liangfei
    Ouyang, Minggao
    [J]. 2019 IEEE TRANSPORTATION ELECTRIFICATION CONFERENCE AND EXPO (ITEC), 2019,
  • [25] The impact of disruptive powertrain technologies on energy consumption and carbon dioxide emissions from heavy-duty vehicles
    Smallbone, Andrew
    Jia, Boru
    Atkins, Penny
    Roskilly, Anthony Paul
    [J]. ENERGY CONVERSION AND MANAGEMENT-X, 2020, 6
  • [26] Optimal Torque Control of the Launching Process with AMT Clutch for Heavy-Duty Vehicles
    Geng, Xiaohu
    Liu, Weidong
    Liu, Xiangyu
    Wen, Guanzheng
    Xue, Maohan
    Wang, Jie
    [J]. MACHINES, 2024, 12 (06)
  • [27] Novel evaluation method of fuel consumption and emission for heavy-duty hybrid electric vehicles
    F. W. Yan
    P. Zhang
    C. Q. Du
    D. Guo
    [J]. International Journal of Automotive Technology, 2014, 15 : 773 - 779
  • [28] NOVEL EVALUATION METHOD OF FUEL CONSUMPTION AND EMISSION FOR HEAVY-DUTY HYBRID ELECTRIC VEHICLES
    Yan, F. W.
    Zhang, P.
    Du, C. Q.
    Guo, D.
    [J]. INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY, 2014, 15 (05) : 773 - 779
  • [29] Reachability analysis of hybrid lateral control problem for automated heavy-duty vehicles
    Wang, JY
    Tomizuka, M
    [J]. PROCEEDINGS OF THE 2001 AMERICAN CONTROL CONFERENCE, VOLS 1-6, 2001, : 1 - 6
  • [30] Nonlinear Model Predictive Control for Heavy-Duty Hybrid Electric Vehicles Using Random Power Prediction Method
    Chen, Luming
    Liao, Zili
    Ma, Xiaojun
    [J]. IEEE ACCESS, 2020, 8 : 202819 - 202835