ABSTRACT The decarbonization of the transportation sector is imperative for achieving targeted reductions in greenhouse gas emissions, necessitating the integration of renewable energy pathways. While battery electric vehicles (BEVs) are widely promoted as an environmentally sustainable solution, their utility is often constrained by the significant battery mass and corresponding weight penalty required to achieve extended operational ranges. This fundamental limitation has motivated the rigorous development of fuel cell hybrid electric vehicles (FCHEVs) as a viable technological alternative. In recent years, simulation of powertrain systems has emerged as a prevalent methodology for assessing vehicle performance and energy efficiency across various electric, hybrid, and FCHEV architectures. However, a significant portion of the existing literature on hybrid vehicles focuses on component‐level optimization or specific hybrid topologies, often relying on simulations that assume idealized, flat‐terrain road profiles, thereby neglecting the impact of topographical gradients. This study addresses this research gap by developing a comprehensive powertrain system model for a battery/fuel cell hybrid vehicle implemented in MATLAB/Simulink. The model's performance is dynamically evaluated under the WLTP, ARTEMIS, and NEDC driving cycles, which are distinctly applied to the GraphHooper Maps‐derived real‐world inclined route in Elazığ. The simulations yield critical performance indicators, including the power distribution dynamics among powertrain components, changes in battery state of charge (SoC), and vehicle speed control. Furthermore, an adaptive PID controller is implemented to ensure that the vehicle's instantaneous speed precisely tracks the reference speed trajectory. This work aims to provide a high‐fidelity simulation approach that more accurately reflects real‐world driving conditions, facilitating a robust evaluation of hybrid vehicle performance in realistic operational scenarios. In this context, for the WLTP, ARTEMIS, and NEDC driving cycles applied to a 3.1‐km real‐world route, the battery SoC was improved by 1.5%, 1.8%, and 1.6%, respectively, in the hybrid configuration. Moreover, owing to the proposed adaptive control strategy, the vehicle speed tracked the reference profile with an average accuracy of 99.8%.
Yilmaz et al. (Sun,) studied this question.