The flexible direct current traction power supply system (DC-TPSS) is a nonlinear system involving kinematics and electrics. Automatic train supervision (ATS) systems are prone to positioning errors and integrate supervision and control systems (ISCS) tend to have missing electrical data of train, making it challenging to accurately obtain the system state in real time. To address these issues, this paper presents a train positioning method that combines the electrical with kinematic measurements for an accurate estimation using a Kalman filter. By solving the real-time power equations for each interval, this method generates pseudo-measured values for the train, addressing the lack of train information in ISCS. Subsequently, a measurement matrix and equations are dynamically generated from the real-time state of the network topology. The weighted least squares (WLS) method is used to filter out bad data for accurate estimates. a flexible DC-TPSS model is finally constructed to verify the accuracy of the algorithm, with the algorithm embedded in the ISCS for in-loop data validation. The results show that the proposed method achieves high-accuracy estimations of the train electrical quantities and position, with significantly reducing variance in the voltage estimation results.