In view of the severe voltage fluctuations in the traction network, which result in a significant waste of regenerative braking energy (RBE), and excessive line losses during the operation of trains at multiple passenger stations, a dynamic adjustment method has thus been proposed for the charge and discharge threshold based on the train operating position and the state of charge (SOC) of onboard supercapacitors. By applying the energy priority principle, the operating conditions of the system are precisely classified to achieve a stable traction network voltage. In addition, to further mitigate the “step” phenomenon in the traction network, a voltage threshold variation rate strategy, which is based on SOC, has thus been introduced. Compared with the fixed voltage threshold variation rate, the proposed strategy can more effectively reduce line losses. Finally, a particle swarm optimization algorithm with dynamic weight factors is employed to optimize control parameters, with the Pareto optimal solution set obtained by using data from trains operating in Changsha. The results indicate that, under the same control parameters, the proposed strategy significantly improves the system, s energy-saving efficiency and voltage stability compared to other control strategies.