Optimization of fuel consumption and NO x emission for mild HEV via hierarchical model predictive control

Yuka Umezawa, Ken Yamauchi, Hiroki Seto, Toshiro Imamura, Toru Namerikawa

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


In this paper, we consider the fuel economy optimization problem for a mild hybrid electric vehicle (HEV) using hierarchical model predictive control. In the proposed algorithm, two problems are addressed: eco-driving and torque distribution. In the eco-driving problem, vehicle speed was controlled. Considering the reduction in fuel consumption and NOx emissions, the torque required to follow the target speed was calculated. Subsequently, in the torque distribution problem, the distribution between the engine and motor torques were calculated. In this phase, engine characteristics were considered. These problems differ in terms of time scales; therefore, a hierarchical model predictive control is proposed. Lastly, the numerical simulation results demonstrated the efficacy of this research.

Original languageEnglish
Pages (from-to)221-234
Number of pages14
JournalControl Theory and Technology
Issue number2
Publication statusPublished - 2022 May


  • Energy management
  • Hierarchical control
  • Mild HEV
  • Model predictive control

ASJC Scopus subject areas

  • Control and Optimization
  • Information Systems
  • Aerospace Engineering
  • Signal Processing
  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Modelling and Simulation


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