Cell-Level State of Charge Estimation for Battery Packs Under Minimal Sensing

• DOI: 10.48550/arxiv.2109.08332
• Publication Date: 2021-01-01
• Authors: Dong Zhang; Luis D. Couto; Ross Drummond; Shashank Sripad; Venkatasubramania...
• Keywords: Battery pack; State of charge; Observability

This manuscript presents an algorithm for individual Lithium-ion (Li-ion) battery cell state of charge (SOC) estimation in a large-scale pack under minimal sensing, where only pack-level voltage and current are measured. For packs consisting up to thousands cells electric vehicle or stationary energy storage applications, it is desirable estimate SOCs without local measurements order reduce sensing costs. Mathematically, pure series connected yield dynamics given by ordinary differential equations classical full sensing. In contrast, parallel--series evidently more challenging because the governed nonlinear differential--algebraic (DAE) system. The majority conventional studies on SOC benefit from idealizing as lumped single which ultimately lose track cell-level conditions blind potential risks over-charge over-discharge. work explicitly models with high fidelity cell-by-cell resolution based interconnection models, examines observability measurements. A DAE-based observer linear output error injection formulated, can be reconstructed number mathematically guaranteed asymptotic convergence algebraic estimates established considering Lipschitz continuity property system nonlinearities. Simulation results Graphite/NMC illustrate SOCs, currents, voltages.