Dynamic voltage scaling(DVS), which adjusts the clock speed and supply voltage dynamically, is an effective technique in reducing the energy consumption of embedded real-time systems. The energy efficiency of a DVS algorithm largely depends on the performance of the slack estimation method used in it. In this paper, we propose novel DVS algorithms for periodic hard real-time tasks based on an improved slack estimation algorithm. Unlike the existing techniques, the proposed method can be applied to most priority-driven scheduling policies. Especially, we apply the proposed slack estimation method to EDF and RM scheduling policies. The experimental results show that the DVS algorithms using the proposed slack estimation method reduce the energy consumption by 20∼40 % over the existing DVS algorithms.