用于光伏微电网能量管理策略适应的VRLA-Gel蓄电池组原位性能评估

Abstract This paper presents a practical, non-invasive two-step discharge method to estimate the remaining usable capacity of VRLA-Gel battery banks operating in field conditions without requiring disassembly or reliance on historical BMS data. The proposed approach begins with a short pulse discharge to quickly identify fresh and underperforming batteries based on voltage dips and discharge trajectories. This initial screening reduces testing time by nearly 50%. It is followed by a staggered discharge phase, which enables finer classification of the remaining underperforming batteries into average and weak groups by mapping capacity trends onto a reference scatter plot. In the first step, a reference database is developed from individually tested VRLA-Gel batteries of unknown usage history, categorized by their dynamics. This reference is then applied to evaluate a 1620Ah 48 V/77kWh in-situ battery bank deployed in a real PV microgrid to determine its remaining performance. Results showed that the method could classify in-situ battery banks into fresh, average, and weak groups with over 90 % classification consistency agreement. The method is particularly suited for retrofit conditions where historical logging or BMS data is incomplete or unavailable. It supports microgrid resilience by extending battery life, reducing unnecessary replacements, and delaying recycling—a contribution toward environmental sustainability and economic optimization. The proposed method is also adaptable to other VRLA-dependent applications, with modifications of the scatter plot as a new reference at respective discharge C-rates.