One of the main difficulties in acoustic echo cancelation (AEC) is the adaptation strategy of the adaptive filter in different situations. Recently, the Kalman filter theory has been introduced to accommodate for the adaptation control in AEC applications, due to its optimal performance in many system identification problems. In this paper, a frequency-domain simplified Kalman filter for partitioned-block-based AEC is studied. The contribution is twofold. First, the relationship between the Kalman filter and an optimal variable step-size algorithm is revealed, which contributes to the motivation of this paper. Second, the influence of system uncertainty on the performance of the Kalman filter is analyzed, and a new uncertainty control method is developed. Simulation results confirm the superiority of the proposed method to the conventional ones.