Owing to the importance of the fuel economy and emission performance of parallel hybrid electric vehicles (PHEVs), parallel hybrid systems are a critical research topic in the vehicle industry. However, previous research has endeavored to reflect the real situation of optimization objectives, which tends to result in low-quality solutions. To address this issue, a novel multi-objective optimization approach based on the multi-objective slime mold algorithm (MOSMA) is used to optimize the hybrid power system of a PHEV. Then, with the objectives of reducing fuel consumption, CO emission, and the sum of HC and NOx emissions, a mathematical model for three-objective optimization is established. The six parameters affecting the hybrid system performance are optimized by considering the dynamic power performance and battery charge state balance constraints. Finally, ADVISOR is used as a simulation platform to verify the optimization results. The results before and after optimization demonstrate that MOSMA can effectively address the multi-objective optimization of hybrid vehicles; concretely, the fuel consumption and the sum of HC and NOx emissions are reduced by 9.5 and 7.4%, respectively. More notably, the decrease in CO emission is as much as 34.4%.