Hybrid TDO–SDRN approach-based energy management of a hybrid electric vehicle

The article introduces a hybrid TDO–SDRN approach for energy management in hybrid electric vehicles, focusing on optimizing fuel efficiency and operational performance. It discusses the challenges posed by conventional energy management techniques and the limitations of existing optimization methods. The proposed approach integrates Tasmanian Devil Optimization for search capabilities and Spiking Deep Residual Networks for error minimization and predictive power. The method is validated through simulations and comparisons with existing techniques, demonstrating its superiority in fuel economy and system efficiency. The article also covers the configuration of a series hybrid electric tracked vehicle, the modeling of the energy management system, and the results of the proposed approach under different driving conditions. The novel combination of TDO and SDRN offers a flexible, scalable, and computationally efficient solution for the complexities of hybrid electric vehicle powertrain systems.