• DocumentCode
    72982
  • Title

    Power Demand Analysis and Performance Estimation for Active-Combination Energy Storage System Used in Hybrid Electric Vehicles

  • Author

    Qu Xiaodong ; Wang Qingnian ; Yu YuanBin

  • Author_Institution
    State Key Lab. of Automotive Simulation & Control, Jilin Univ., Changchun, China
  • Volume
    63
  • Issue
    7
  • fYear
    2014
  • fDate
    Sept. 2014
  • Firstpage
    3128
  • Lastpage
    3136
  • Abstract
    Because of the drawbacks of ultracapacitors (UCs) and batteries, an active combination of UCs and Li-ion batteries has been proposed as an energy storage system (ESS) for hybrid electric vehicles (HEVs). Given the complexity of the active control system in an active-combination energy storage system (ACES), the performance match for the ACES used in an HEV is much more complex. In this paper, a widely applicable method to analyze the design process of the ESS used in HEVs is presented. The concept of the power-energy (PE) function is proposed to illustrate the power demand from the HEV and the energy and power capability of the ESS. This concept draws a clear contrast between demand and capability, particularly for the ACES. At the same time, the efficiency of the ACES could be estimated on the basis of this method. Furthermore, by using operating data from a hybrid electric bus in Changchun, China, power demand analysis and performance estimation are carried out for the optimal design of the ACES.
  • Keywords
    hybrid electric vehicles; secondary cells; supercapacitors; ACES; ESS; HEV; PE function; active-combination energy storage system; hybrid electric bus; hybrid electric vehicles; performance estimation; power demand analysis; power-energy function; Batteries; Conferences; Energy loss; Hybrid electric vehicles; Materials; Power demand; Battery??ultracapacitor (UC) hybrids; Hybrid electric vehicles; battery-ultracapacitor hybrids; hybrid electric vehicles (HEVs); power demand analysis;
  • fLanguage
    English
  • Journal_Title
    Vehicular Technology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9545
  • Type

    jour

  • DOI
    10.1109/TVT.2014.2302017
  • Filename
    6719581