Systematic Hybridized Traction System Design Using a Joint Multi-Stage-Multi-Objective Optimization Method

The hybridized traction system (HTS) is increasingly used in rolling stock applications due to its high fuel efficiency and eco-friendliness. Since the HTS integrates various energy sources, its topology, component sizing (CS), and energy management strategy (EMS) are critical for achieving optimal HTS design. However, existing methods primarily focus on optimizing CS and/or EMS, without considering the impact of topology. To address this limitation, this paper proposes a joint multi-stage-multi-objective (MSMO) optimization method for systematic HTS design, considering topology, CS, and EMS simultaneously. This approach achieves multiple goals of reducing economic costs, lightweighting the system, and decreasing carbon dioxide (CO2) emissions. The MSMO optimization method consists of three key processes. First, it applies a topological traversal algorithm to generate a preliminary set of designs, using comparative selection to identify and eliminate infeasible elements. Next, the selected subset undergoes coarse optimization for CS and EMS, and then a limited number of topologies are survived by comparing the values of the exponential tangent weighted sum model (ETWSM). Finally, the surviving topologies undergo fine optimization of CS and EMS, with the optimal system topology selected by further comparing ETWSM values, thus achieving joint optimization of topology, CS, and EMS. Two case studies of rolling stocks with multiple power sources systems, including diesel-battery-supercapacitor-fuel cell, validate the capability and effectiveness of the proposed method.