퍼지제어 기반 수소연료전지 하이브리드 철도차량의 에너지 관리 전략에 관한 연구

Abstract

This study proposes a fuzzy control-based Energy Management Strategy (EMS) for a hydrogen fuel cell hybrid train to improve energy efficiency and operational adaptability. The proposed fuzzy controller employs the battery state-of-charge (SOC) error, vehicle power demand, and route-based operation prediction as input variables, and determines the output power of hydrogen fuel cell (HFC) as the control output. The 27 fuzzy inference rules enables flexible and adaptive energy allocation under diverse driving conditions. In addition, two representative SOC management strategies—Charge Depletion Mode (CDM) and Charge Sustaining Mode (CSM)—are applied to evaluate the performance of the proposed algorithm. The effectiveness of the strategy is validated through MATLAB/Simulink simulations, demonstrating enhanced hydrogen consumption efficiency and improved battery SOC stability. Unlike conventional rule-based EMS approaches, the proposed method ensures adaptive energy management by incorporating route-based predictive information into the fuzzy inference process, thereby enhancing its practical applicability to train operations.