Optimization of energy management system for parallel hybrid electric vehicles using torque control algorithm

Improvement of the fuel consumption and exhaust gases have been one of the important issues in automobile. Hybrid electric vehicles (HEVs) that have one internal combustion engine (ICE) and electric motors (EMs), can meet this requirement. To improve them simultaneously, a well-organized energy management system (EMS) should be developed. In this paper, a novel EMS considering torque control is developed, in which a function called the torque control function is introduced to control the driving mode, the target ICE torque, and the target EM torque. In addition, a sequential approximate optimization using a radial basis function network is adopted to determine the torque control function. CO₂ and NO_x are so closely related the fuel consumption and the exhaust gases, and they are then simultaneously minimized. A multi-objective design optimization is the formulated, and the torque control function is determined with a small number of simulation runs. The worldwide harmonized light duty driving test cycle is used to examine the validity of the proposed EMS using the torque control function.