Real-time Optimization Control Strategy of CVT Hybrid Electric Vehicles Considering the Driving Comfort

Abstract

For hybrid electric vehicles (HEVs), the energy management strategy (EMS) can have a significant impact on the fuel economy and emission reduction. In traditional optimization method-based EMS, if fuel economy is the only criterion in the cost function, the result will lead to irrational control signals, thus resulting in deteriorate drivability performance. To deal with this problem, an improved adaptive equivalent fuel consumption minimization strategy (A-ECMS) is proposed, penalty terms are introduced into the cost function to punish frequent engine start/stop events and excessive speed ratio change. Simulation tests are carried out under four kinds of standard driving cycles. By changing the weighting factors, the trade-off between the fuel economy and performance indexes can be evaluated. Finally, the proposed method is compared with the traditional ECMS under the UDDS cycle. The simulation results show that the proposed strategy not only optimizes the fuel economy, but also greatly improves the objectives of the engine start/stop state, changing rate of CVT speed ratio and electric oil pump energy consumption.

Keywords

• Hybrid electric vehicle;CVT;A-ECMS;Drivability;Penalty function