The dynamic characteristic evaluation is an important prerequisite for safe and reliable operation of the medium-voltage DC integrated power system (MIPS), and the dynamic state estimation is an essential technical approach to the evaluation. Unlike the electromechanical transient process in a traditional power system, periodic change in pulse load of the MIPS is an electromagnetic transient process. As the system state suddenly changes in the range of a smaller time constant, it is difficult to estimate the dynamic state due to periodic disturbance. This paper presents a dynamic mathematical model of the MIPS according to the network structure and control strategy, thereby overcoming the restrictions of algebraic variables on the estimation and developing a dynamic state estimation method based on the extended Kalman filter. Using the method of adding fictitious process noise, it is possible to solve the problem that the linearized algorithm of the MIPS model is less reliable when an abrupt change occurs in the pulse load. Therefore, the accuracy of the dynamic state estimation and the stability of the filter can be improved under the periodic disturbance of pulse load. The simulation and experimental results confirm that the proposed model and method are feasible and effective.