Variable-Horizon MPC-Based Energy Management for Battery–Supercapacitor Hybrid Power Supply of Contactless Rail Vehicles

The absence of overhead catenary systems in contactless trams imposes stringent requirements on onboard energy efficiency and real-time power management. Hybrid energy storage systems combining batteries and supercapacitors provide an effective solution; however, conventional energy management strategies often suffer from limited global optimality under frequent traction–braking conditions. To address this issue, this paper proposes a variable-horizon model predictive control (MPC)-based energy management strategy for a battery–supercapacitor hybrid power supply system in contactless trams. A power-level-matching method is first adopted for capacity configuration, and the MPC prediction horizon is then dynamically adjusted to cover the entire traction phase, enabling global energy loss optimization while satisfying voltage, current, and SOC constraints. Simulation results obtained in MATLAB/Simulink demonstrate that the proposed strategy effectively suppresses excessive battery current and premature supercapacitor depletion. Compared with the conventional single-step MPC, the total energy loss is reduced by 9.88%, indicating improved energy efficiency and operational performance.