Adaptive frequency separation-based energy management strategy using fuzzy logic for fuel cell-battery hybrid vehicles

The transition to clean and sustainable transportation highlights the importance of hydrogen and fuel cell technologies as promising solutions for reducing greenhouse gas emissions. This paper presents the development and assessment of an adaptive frequency separation-based energy management strategy using fuzzy logic for fuel cell–battery hybrid vehicles. The studied system integrates a proton exchange membrane fuel cell as the primary source and a lithium-ion battery as the secondary source, both interfaced with the DC bus through DC/DC converters. A PI controller ensures DC bus voltage stability, while a sliding mode hysteresis controller provides robust regulation of the fuel cell current. Unlike conventional frequency separation methods, which only allocate low-frequency demand to the fuel cell and high-frequency demand to the battery, the proposed strategy introduces an adaptive correction mechanism based on the state of charge (SOC) of the battery and instantaneous load variations. This ensures efficient power allocation according to source dynamics while actively regulating the SOC within a safe operating range. Simulation results under UDDS and NEDC driving cycles confirm that the proposed strategy maintains the SOC between 40% and 80% with convergence toward the target value of 60%, while reducing the apparent hydrogen consumption by 30%. These improvements highlight the robustness and efficiency of the proposed strategy, making it a promising solution to extend the lifespan of hybrid energy sources in hybrid fuel cell electric vehicles.