Multi-Stage Battery Charging Scheduling Optimization at Battery Swapping Stations

Battery swapping has become a prominent method of energy supply for electric vehicles, featuring short service time and streamlined charging management. This paper explores efficient battery charging scheduling (BCS) strategies at battery swapping stations (BSSs). By analyzing the operational characteristics of batteries, a multi-stage BCS model is proposed. Unlike the conventional constant-power single-stage BCS model, the proposed multi-stage BCS model allows batteries to be charged to different expected state of energy (SoE) levels in different stages, and the charging power rate can be adaptively adjusted to avoid over-voltage or accelerated degradation when the battery approaches its highest SoE level. Considering both the battery SoEs and real-time swapping demands and taking the batteries to be charged in each stage as control variables, a multi-objective integer programming problem is formulated to minimize the average charging cost as well as to maximize the average SoE of charged batteries. This problem is solved using the Gurobi solver, and the effectiveness and advantages of the proposed BCS strategy are demonstrated through a case study of a practical BSS for heavy-duty electric trucks.