To realize real-time evaluation of the steering pump motor’s operating performance， a physical model of the steering pump motor is firstly constructed in this paper， which considers the operating mechanism of the steering pump motor. By solving the pump motor’s external characteristic equation， hydraulic circuit balance equation， and internal flow calculation equation， etc.， the preliminary evaluation and calculation of the internal unmeasurable parameters can be realized. Then， the influence mechanism of various parameters on the performance of the steering pump motor is obtained. At the same time， LSTM deep learning method is used to build a data-driven model of the steering pump motor to learn and predict the variation rule of the volume efficiency of the steering pump motor under different working conditions. The volume efficiency is then input into the physical model to form a mixed model of steering pump motor performance evaluation， so as to improve the accuracy and applicability of steering pump motor performance evaluation under different working conditions. The example analysis shows that the hybrid model can calculate and evaluate the internal and external parameters such as internal pressures， flow rate， speed and torque of the steering pump motor with high accuracy under complex working conditions， and the model error is less than 10%.