Aiming at the multi-objective optimization ( MOO) problem of the range-extended electric vehicle regenerative braking control strategy，a real-time adaptive regenerative braking control strategy was proposed based on the MOO model and optimal optimization theory． Firstly，the vehicle simulation model was established on AVL / Cruise and Matlab /Simulnk software，and a MOO model was built with the system braking performance ( BP) ， regenerative braking loss efficiency ( RBLE) and battery capacity loss rate ( BCLR) as the objective functions based on NSGA-Ⅱ algorithm． Then Parato optimal solution was obtained through off-line optimization under the comprehensive regenerative braking performance． Combined with the optimization results，a real-time adaptive fuzzy controller was designed． The controller considers the road adhesion and the state of battery，and can adjust the distribution of the regenerative braking work-point online． Simulation results on WLTP driving cyclic conditions show that the adaptive regenerative braking control strategy can effectively balance the relationship among BP，RBLE and BCLR，and it can effectively reduce BP and RBLE while maintaining a small BCLR．