A power distribution strategy for heavy duty HEV with series hybrid powertrain based on model predictive control method

Muyao Wang, Chao Yang*, Weida Wang, Ruihu Chen, Ying Li

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)

Abstract

Aiming at the problem of power distribution strategy of heavy-duty HEV with series hybrid powertrain, this paper proposed a power distribution strategy based on model predictive control (MPC). The strategy establishes the related energy consumption index and the physical constraints of the whole vehicle. It predicts the power and speed of vehicle powertrain in a given prediction time domain and distributes generator power and motor power reasonably according to the demand power. In order to reduce the computation of solving quadratic programming subproblems, the improved sequential quadratic programming (ISQP) algorithm is involved to solve the rolling horizon optimization problem. To prove the effectiveness of the strategy, the simulation is carried out under a given condition. The simulation results show that the strategy has better fuel economy than the rule-based strategy under the given condition.

Original languageEnglish
Pages (from-to)72-77
Number of pages6
JournalIFAC-PapersOnLine
Volume54
Issue number10
DOIs
Publication statusPublished - 2021
Event6th IFAC Conference on Engine Powertrain Control, Simulation and Modeling E-COSM 2021 - Tokyo, Japan
Duration: 23 Aug 202125 Aug 2021

Keywords

  • Heavy duty HEV
  • MPC
  • Rolling horizon optimization
  • SQP
  • Series hybrid powertrain

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