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The state of charge (SOC) and the maximum available electricity estimation are two of the most important parts of satellite lithium-ion battery life prediction. However, compared with the fast time-varying SOC, the parameters of the maximum available power change slowly. It proposed a multi-time scale extended Kalman filter (EKF) prediction algorithm based-on the equivalent circuit model to estimate the SOC and the maximum available capacity at different time scales. The SOC estimation is used as an observation on the macroscopic scale to update the maximum available power. The simulation results of NCA/C lithium-ion battery show that the proposed multi-time scale EKF prediction algorithm has higher accuracy of SOC and maximum available power estimation compared with tradtional EKF algorithm, and improves the computational efficiency.