RAC: Reconfiguration-Assisted Charging in Large-Scale Lithium-Ion Battery Systems

Abstract

Large-scale lithium-ion battery packs are widely adopted in systems such as electric vehicles and energy backup in power grids. Due to factors such as manufacturing difference and heterogeneous discharging conditions, cells in the battery pack may have different statuses, such as diverse voltage levels. This cell diversity is commonly known as the cell imbalance issue. For the charging of battery packs, the cell imbalance not only early on terminates the charging process before all cells are fully charged, but also leads to different desired charging currents among cells. In this paper, based on the advancement in reconfigurable battery systems, we demonstrate how to utilize system reconfigurability to mitigate the impact of cell imbalance on an efficient charging process. With the proposed reconfigurationassisted charging (RAC), cells in the system are categorized according to their real-time voltages, and the charging process is performed in a category-by-category manner. To charge cells in a given category, a graph-based algorithm is presented to charge cells with their desired charging currents, respectively. We evaluate RAC through both experiments and simulations. The results demonstrate that the RAC increases the capacity charged into cells by about 25% and yields a dramatically reduced variance.

Next-Generation Battery Management Systems: Dynamic Reconfiguration

“…To do so, the first step is to sort all battery cells according to the amount of charge which, unfortunately, cannot be physically measured. Thus, different alternatives are applied to the battery sorting, e.g., the cell's SoC [ [25], and terminal voltage [19], in which the former two are usually used in combination with state estimation.…”

“…As a result, it becomes challenging to model the exact dynamic behavior of switches. In some studies, for simplicity, R DS(on) is simply ignored [25] or assumed constant [37]. However, accurate switch modeling is still worth exploiting when R DS(on) is comparable with the internal resistance of battery cells and imposes considerable influence on the total resistances.…”

“…• Constraints on the sequential or synchronized switch operations to avoid any circuit faults. Among the problems in Table II, those formulated in [11,25,33,43] focus on only one period, either the present control period or a full discharging process. To solve such optimization problems, graph theory has been deployed based on the graph representation of system configurations.…”

“…To solve such optimization problems, graph theory has been deployed based on the graph representation of system configurations. For example, minimizing the total additional resistance was transformed to a minimum path cover problem in [25], and maximizing the battery pack's charge delivery was achieved by constructing and solving a maximum-weight independent set problem [43]. In [11], the power loss curves and terminal voltages of different system configurations were evaluated offline in advance and subsequently used for determining the optimal configuration online in response to the voltage and current demands.…”

“…The number of switches assigned to each battery cell and their connection pattern determine the system's reconfigurability. A number of circuit designs for RBSs in the literature [2,[6][7][8][9][10][11][25][26][27][28][29][30][31][32][33][34][35] are illustrated in Fig. 2, where two to six switches are connected to each battery cell to realize various connection and operation possibilities.…”