Abstract: Studied the maximum power point tracking system, dual stage Maximum Power Point Tracking (MPPT) method of Particle Swarm Optimization (PSO) and incremental conductance algorithm was proposed. The proposed method can solve the problems of incremental conductance algorithm's worse tracking precision under large step and slower tracking speed and larger power fluctuation in the dynamic tracking process under small step tracking. The proposed method consists of two stages:the stage of optimal duty prediction and the stage of MPPT. The stage of optimal duty prediction uses improved PSO to search the working voltage and current near the maximum power point of the photovoltaic cells, next calculates the optimal duty according to the searched voltage and current. This stage can solve the problems of slower tracking speed and larger power fluctuation under small step tracking. The optimal duty is received and the system is controlled by the incremental conductance algorithm when the duty generated by the incremental conductance algorithm is closed to the optimal duty, or the optimal duty is used to control system in the stage of MPPT. Simulation results show that the proposed method can acquire faster tracking speed, have better tracking precision, and reduce the power fluctuation in the dynamic tracking process. So the proposed method can achieve the maximum power point tracking bitterly.