The configuration and control strategy of hybrid powertrain systems are significant for the development of hybrid electric vehicles (HEV) because they significantly affect their comprehensive performance. In this paper, the types, features, and applications of the mainstream hybrid powertrain configurations on the market in recent years are summarized and the effects of different configurations on the comprehensive performance of HEVs are compared. Moreover, the technical routes for each hybrid configuration are highlighted, as configuration optimization methods have become a technical difficulty. In addition, the technological advances in the steady-state energy management strategy and dynamic coordinated control strategy for hybrid powertrain systems are studied. The optimization of the steady-state energy management strategy mainly involves assigning the working point and working range of each power source reasonably. However, with the increase in the complexity of optimization algorithms, real-time control of HEVs still needs to be improved. The optimization of the dynamic coordinated control strategy mainly focuses on the stability and smoothness of the dynamic process involving switching and shifting the working mode. The optimization of the dynamic control process for the system remains to be further improved. It is pointed out that the configurations and strategies should be optimized jointly to obtain a comprehensive improvement in the system performance. This paper provides an informative basis and technical support for the design and optimization of a hybrid powertrain system.

For electrically driven commercial vehicles equipped with three-speed automatic mechanical transmission (AMT), the transmission control unit (TCU) without vehicle mass and road gradient estimation function will lead to frequent shifting and insufficient power during vehicle full-load or grade climbing. Therefore, it is necessary to estimate the mass and road gradient for the electrically driven commercial vehicles equipped with the three-speed AMT, and to adjust the shift rule according to the estimation results. Given the above problems, this paper focuses on the control and development of the electrically driven three-speed AMT and takes the shift controller with the vehicle mass and road gradient estimation as the research goal. The mathematical model and simulation model of vehicle dynamics are established to verify the shift function of TCU. The least squares method and calibration techniques are applied to estimate the vehicle mass and road gradient. According to the estimation results, the existing shift strategy is optimized, and the software-in-the-loop simulation of the transmission controller is carried out to verify the function of the control algorithm software. The hardware-in-the-loop test model is established to verify the shift strategy’s optimization effect, which shortens the controller’s forward development cycle. According to the estimation results of mass and gradient, the error result of the proposed method is controlled within 4.5% for mass and 8.6% for gradient. The experiment verifies that the optimized shift strategy can effectively improve the dynamic performance of the vehicle. The HIL experimental results show that the vehicle can maintain low gear while climbing the hill, and the vehicle speed does not decrease significantly.