Optimal integrated energy management and shift control in parallel hybrid electric vehicles with dual-clutch transmission

Abstract

This paper addresses the integration of the energy management and the shift control in parallel hybrid electric vehicles with dual-clutch transmission to reduce the fuel consumption, decrease the pollutant emissions, and improve the driving comfort simultaneously. Dynamic programming with a varying weighting factor in the cost function is proposed to balance the shift frequency and the fuel consumption for the power-split control and gear schedule design. Simulation results present that the drivability can be improved with a varying weighting factor due to fewer shift events while the fuel consumption is only slightly increased compared to dynamic programming with a constant weighting factor. A shift-energy-management strategy integrating the upshift and power-split control based on a multi-objective optimization is presented where model predictive control is employed to ensure engine load rate constraints. The strategy can smoothen the engine torque through torque compensation from the electric motor to prevent engine transient emissions resulting from a sudden load change. In a simulation study, the NOx and HC emissions could be reduced by 1.4% and 2.6% with 2% increase of the overall fuel consumption for the Federal Test Procedure 75 by smoothening the engine torque. For the New European Driving Cycle, 0.9% and 1.1% reduction of NOx and HC emissions could be achieved with only 0.3% more fuel consumption.