0D-1D coupling for an integrated fuel economy control strategy for a hybrid electric bus

Laura Tribioli, Fabrizio Martini, Giovanni Pede, Carlo Villante

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Hybrid electric vehicles (HEVs) are worldwide recognized as one of the best and most immediate opportunities to solve the problems of fuel consumption, pollutant emissions and fossil fuels depletion, thanks to the high reliability of engines and the high efficiencies of motors. Moreover, as transport policy is becoming day by day stricter all over the world, moving people or goods efficiently and cheaply is the goal that all the main automobile manufacturers are trying to reach. In this context, the municipalities are performing their own action plans for public transport and the efforts in realizing high efficiency hybrid electric buses, could be supported by the local policies. For these reasons, the authors intend to propose an efficient control strategy for a hybrid electric bus, with a series architecture for the power-train. To this aim, an integrated approach realized by coupling a zero-dimensional model of the vehicle with a mono-dimensional model of the thermal engine to evaluate fuel consumption and find the most suitable control strategy for the engine (totally decoupled to the mission). A kinematic approach has been implemented. The power required to the motor is defined by knowing the speed and altitude profiles related to the path, while the power request for the engine is calculated by means of a first order filter, which properly cuts the power load of the motor. A sensitivity analysis has been performed in order to define the optimal operating strategy for the engine, to minimize the fuel consumption. Moreover, a control on the state of charge (SOC) has been implemented to assure a correct use of batteries and avoid damages. Copyright © 2011 SAE International.
Original languageEnglish
Pages (from-to)-
JournalSAE Technical Papers
DOIs
Publication statusPublished - 2011
Externally publishedYes

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All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Safety, Risk, Reliability and Quality
  • Pollution
  • Industrial and Manufacturing Engineering

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