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Predictive planning of the battery state of charge trajectory for hybrid-electric passenger cars

  • Gunter Heppeler
  • Marcus Sonntag
  • Oliver Sawodny
Conference paper
Part of the Proceedings book series (PROCEE)

Abstract

To achieve efficient usage of hybrid power-trains, predictive operational strategies can be developed, which take into account future driving situations by knowledge of driving cycle. The algorithm presented in this paper calculates a State of Charge (SoC) trajectory, which minimizes fuel consumption by using a trip preview and the corresponding power demand of the vehicle. This trajectory can be used together with instantaneous operational strategies with no or only short prediction (e.g. an adaptive Equivalent Consumption Minimization Strategy (ECMS)). The algorithm explicitly takes into account the limits of the battery and therefore avoids situations, in which the power-train would be operated inefficiently without prediction due to the constraints. The effectiveness of the algorithm is shown by comparing it with operational strategies without prediction and an offline potential analysis.

Keywords

Internal Combustion Engine Power Demand Driving Cycle Battery State Electric Driving 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Fachmedien Wiesbaden 2015

Authors and Affiliations

  • Gunter Heppeler
    • 1
  • Marcus Sonntag
    • 1
  • Oliver Sawodny
    • 1
  1. 1.University of StuttgartStuttgartGermany

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