In large-scale control optimization problems, a decentralized control structure can offer great scalability and rapidity advantages over a centralized implantation. Alternating Direction Method of Multipliers (ADMM) is a decentralized optimization algorithm which has the important benefit of being quite general in its scope and applicability in continuous systems. In this paper, a new projected ADMM algorithm is defined and it can work in hybrid systems. The key point is to add a convexification and a projection process during each iteration of ADMM algorithm. We have applied it to a charging control problem of electric vehicles. Simulation results show that the proposed algorithm can converge to a similar result as a centralized control within a limited iteration time. Due to its availability, simplicity and scalability, the projected ADMM algorithm may be attractive in some practical engineering application.