Abstract: In order for ISG hybrid electric vehicles to reduce fuel consumption and emissions, a controller model for timely distributing driving torque to the internal combustion engine and ISG motor based on the adaptive neural-fuzzy inference system (ANFIS) algorithm is established. The performance model of the vehicle is based on the characteristics of internal combustion engine and ISG motor. Data of optimal operating points for training ANFIS system is obtained by finding the extremum of a multivariable function. An ANFIS system is designed and developed to control the torque distribution for ISG hybrid vehicles. Simulation results show improved performance and validity of the energy management strategy based on ANFIS.

Key words: ISG hybrid electric vehicles, torque distribution, optimal operating points