This paper presents advancements to an existing fault detection and protection scheme tailored for DC traction power systems. Current surges, influenced by the operational frequency of trains, transient phases, and varying electrical power demands, among other factors, elevate the fault risk within traction systems. These faults are akin to those caused by external disturbances. The novel algorithm proposed here identifies short circuit faults by analyzing the train’s position between substations and the current consumption from each substation. It dynamically adjusts threshold values based on real-time current measurements, ensuring precise fault detection. Traditional Détection Dé-faut Lign (DDL) systems often fail to reliably detect remote faults or prolonged excess current situations. This paper addresses these shortcomings by concentrating on faults specific to DC Traction Systems and introduces a cutting-edge intelligent current fault detection algorithm. This algorithm overcomes the rigid threshold limitations of conventional methods, enhancing ground fault protection, ground fault current fault protection, and short-circuit fault protection, all while accounting for the dynamic electrical load of railway systems. The study utilizes simulation data from Light Rail Transit (LRT) trains in Singapore and Malaysian Railnetwork to model the railway’s electrical system. A comparative analysis of conventional and proposed schemes is conducted, with simulation results and a discussion on practical implementation and requirements provided.