Constraint programming is one of the most popular approaches for solving the well-known Resource-Constrained Project Scheduling Problem (RCPSP) and its generalizations (i.e. RCPSP MAX, MRCPSP). However, since even a classical statement of RCPSP is NP-complete, constraint programming is not able to nd suitable solutions in reasonable time for large-scale instances. In this paper, we propose some new propagation techniques based on resource capacity and time lags propagation to make constraint programming more efficient for solving RCPSP and its generalized statement RCSPSP MAX which consider precedence relations with time lags. We show that these new algorithms are able to make tasks domains tighter and to improve the performance of existing propagators.