Dual-planetary hybrid electric vehicles excel in fuel efficiency and emissions due to the complete decoupling of engine from vehicle speed. However, the complex structures pose challenges in coordinating power sources during multi-mode operation. A dual-planetary gear hybrid system was designed based on the equivalent tree graph method and a co-simulation model was established by combining AVL CRUISE and Simulink. A dynamic chaos sine-cosine multi-objective particle swarm optimization (DCSC-MOPSO) algorithm was proposed to perform multi-objective optimization targeting power, fuel economy, and smoothness. The simulation results demonstrate that the DCSC-MOPSO algorithm exhibits significant advantages in Pareto solution set search and objective balancing. Compared to the initial solution, the power, fuel economy, and smoothness improve by an average of 39.79%, 17.77%, and 25.24%, respectively, indicating a substantial enhancement in the overall system performance.