Cooperative control strategy for plug-in hybrid electric vehicles based on a hierarchical framework with fast calculation

Y. Zhang, C. Guo, G. Li, Y. Liu, Z. Chen

Research output: Contribution to journalArticlepeer-review

Abstract

Developing optimal control strategies with capability of real-time implementation for plug-in hybrid electric vehicles (PHEVs) has drawn explosive attention. In this study, a novel hierarchical control framework is proposed for PHEVs to achieve the instantaneous vehicle-environment cooperative control. The mobile edge computation units (MECUs) and the on-board vehicle control units (VCUs) are included as the distributed controllers, which enable vehicle-environment cooperative control and reduce the computation intensity on the vehicle by transferring partial work from VCUs to MECUs. On this basis, a novel cooperative control strategy is designed to successively achieve the energy management planned by the iterative dynamic programming (IDP) in MECUs and the energy utilization management achieved by the model predictive control (MPC) algorithm in the VCU. The performance of raised control strategy is validated by simulation analysis, highlighting that the cooperative control strategy can achieve superior performance in real-time application that is close to the global optimization results solved offline.
Original languageEnglish
Article number119627
Pages (from-to)1-19
Number of pages19
JournalJournal of Cleaner Production
Volume251
Early online date11 Dec 2019
DOIs
Publication statusPublished - 1 Apr 2020

Keywords

  • cooperative control strategy
  • hierarchical framework
  • iterative dynamic programming (IDP)
  • model predictive control (MPC)
  • plug-in hybrid electric vehicles (PHEVs)

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