By increasing the need to reduce pollution, improve performance, and increase fuel efficiency in heavy-duty vehicles, the use of hybrid-electric systems has gained attention as an innovative and effective solution. This research aims to improve the energy consumption and select an appropriate configuration for a hybrid tracked vehicle. Initially, various architectures of hybrid systems will be analyzed, and the most suitable configuration will be identified. Then, a dynamic model of the tracked vehicle will be developed by using MATLAB software, and a step-by-step design algorithm, including determining initial requirements, mathematical modeling, selecting key components, and implementing an energy management controller, will be simulated. The final model will be validated with data from a reference to evaluate the accuracy. Simulation results showed that the series hybrid configuration performed better in terms of battery state of charge stability compared to the parallel architecture, providing approximately 18% superiority in maintaining battery charge level. Additionally, to improve power system stability and reduce electrical load on the battery, a supercapacitor was used as a complementary energy storage element, which increases the operation time in electric driving mode by approximately 8 minutes, indicating better instantaneous power management and reduced electrical load on the battery. Furthermore, a comparison of multi-speed gearboxes with two-speed types showed that the multi-speed gearboxes lead to significant improvements in energy consumption efficiency by providing the possibility of optimal gear selection. The findings of this research can serve as a valuable basis for the future design and development of advanced heavy-duty hybrid vehicles.