Hybrid Vehicle CO2 Emissions Reduction Strategy Based on Model Predictive Control

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 CO2 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.

Automated summary

This work proposes a hybrid drive controlled configuration that minimizes CO2 emissions by controlling the power flow direction of the Electric Machine (EM) using a minimum emissions search algorithm. The power flow is controlled by a bi-directional Model Predictive Control (MPC) scheme based on an emissions optimization algorithm. The proposed drivetrain configuration ensures the Minimum Emission Operating Point (MEOP) of the ICE regardless of the mechanical demand at the drivetrain. The simulation and validation results using a Hardware in the Loop (HIL) virtual prototype validate the proposed overall optimization strategy.