Hybrid Vehicle CO2 Emissions Reduction Strategy Based on Model Predictive Control

Carlos A. Reusser, Ramón Herrera Hernández, Tek Tjing Lie

Research output: Contribution to journalArticlepeer-review


This work proposes a hybrid drive controlled configuration, using a minimum emissions search algorithm, which ensures the operation of the Internal Combustion Engine (ICE) in its fuel efficiency range, minimizing CO (Formula presented.) emissions by controlling the power flow direction of the Electric Machine (EM). This action is achieved by means of Power Converters, in this case a bi-directional DC-DC Buck-Boost Converter in the DC-side and a DC-AC T-type Converter as the inverting stage. Power flow is controlled by means of a bi-directional Model Predictive Control (MPC) scheme, based on an emissions optimization algorithm. A novel drivetrain configuration is presented where both, the ICE and the EM are in tandem arrangement. The EM is driven depending on the traction requirements and the emissions of the ICE. The EM is capable of operates in motor and generator mode ensuring the Minimum Emission Operating Point (MEOP) of the ICE regardless of the mechanical demand at the drivetrain. Simulation and validation results using a Hardware in the Loop (HIL) virtual prototype under different operation conditions are presented in order to validate the proposed overall optimization strategy.

Original languageEnglish
Article number1474
JournalElectronics (Switzerland)
Issue number6
StatePublished - Mar 2023


  • AC drive
  • HIL
  • T-type
  • dc-link balance mechanism
  • emissions
  • fuel efficiency
  • minimum emissions operating point algorithm
  • model predictive control


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