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

Abstract

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

Detecting faulty lithium-ion cells in large-scale parallel battery packs using current distributions

“…29 Turning the DAE parallel pack model into an ODE brings insight into the distribution of currents between the branches in the pack, in contrast to the numerical approach where the computational solution only gives a limited insight into the mechanisms by which the pack's currents re-distribute themselves. The numerical solution for computing the parallel pack branch currents is, however, widely used, in both modelling studies, [30][31][32][33] estimator designs [34][35][36][37] and modelling results based upon the PyBAMM 38 open-source software. 39 The extent to which this computational solution has been used indicates the applicability of the analytic solution of Equation 3 to understand these nonlinear parallel pack dynamics.…”