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Predictive Energy Management for Electric Variable Transmission HEV

  • Harbin Institute of Technology
  • Chalmers University of Technology

Research output: Contribution to journalConference articlepeer-review

Abstract

This paper introduces predictive energy management for a hybrid electric powertrain with an electric variable transmission. The optimization of the energy management in hybrid mode is formulated as a bi-level program, in which one static level optimizes the engine speed of a compound unit consists of the engine and electric variable transmission (EVT). The other layer optimizes a dynamic program by splitting power between the compound unit and the battery using equivalent consumption minimization strategy (ECMS). By combining ECMS with dynamic programming (ECMS-DP), the proposed strategy allows the engine on/off control to be also taken into account by iteratively updating the costate. Finally, the efficient ECMS-DP optimization is incorporated into the framework of model predictive control (MPC) and solved in a moving horizon fashion. Computation efficiency and optimization results are presented by simulation.

Original languageEnglish
Pages (from-to)417-422
Number of pages6
JournalIFAC-PapersOnLine
Volume52
Issue number5
DOIs
StatePublished - 2019
Event9th IFAC Symposium on Advances in Automotive Control, AAC 2019 - Orléans, France
Duration: 23 Jun 201927 Jun 2019

Keywords

  • ECMS-DP
  • Hybrid electric vehicle
  • electric variable transmission
  • predictive control

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