Interval Observer for SOC Estimation in Parallel-Connected Lithium-ion Batteries

Zhang, Dong; Couto, Luis D.; Gill, Preet; Benjamin, Sébastien; Zeng, Wente; Moura, Scott J.

doi:10.23919/acc45564.2020.9147468

Cited by 11 publications

(6 citation statements)

References 21 publications

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“…• The study is carried out on a string of cells (or a string of parallel modules), which represents a much wider and general class of topology in a pack. The previous study in [39] only considers parallel-connected cells.…”

Section: State-of-the-art Extended Kalman Filter (Ekf)mentioning

confidence: 99%

“…In this work, we advance our preliminary work in [39] by proposing a thermal enhanced interval observer for SOC estimation in battery packs for a string of cells. This article's main contributions against our previous work [39] are summarized as follows:…”

Section: Introductionmentioning

confidence: 99%

“…5). This significantly eliminates design conservatism in [39] and effectively renders improved estimation accuracy under extreme conditions with large applied currents.…”

Section: Introductionmentioning

confidence: 99%

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Thermal-Enhanced Adaptive Interval Estimation in Battery Packs With Heterogeneous Cells

Zhang

Couto

Gill

et al. 2022

IEEE Trans. Contr. Syst. Technol.

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The internal states of Lithium-ion batteries need to be carefully monitored during operation to manage energy and safety. In this paper, we propose a thermal enhanced adaptive interval observer for state of charge (SOC) and temperature estimation for a battery pack. For a large battery pack with hundreds or thousands of heterogeneous cells, each individual cell characteristic are different from others. Practically, applying estimation algorithms on each and every cell would be mathematically and computationally intractable, since battery packs are often characterized by combinations of differential equations (state dynamics) and algebraic constraints (Kirchhoff's laws). These issues are tackled using an interval observer based on monotone/cooperative system theory, whose novelty lies in considering cell heterogeneity as well as state-dependent parameters as unknown, but bounded uncertainties. The resulting interval observer maps the bounded uncertainties to a feasible set of SOC and temperature estimation for all cells in the pack at each time instant. The present work addresses the significant conservatism under extreme conditions with large currents via a thermal enhanced adaptive scheme. The proposed interval estimation is scalable and computationally tractable since it is independent of the number of cells in a pack, as numerically demonstrated in a comparison with respect to a state-of-the-art single cell state observer. Stability and inclusion of the adaptive interval observer are proven and validated through simulations.

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Section: State-of-the-art Extended Kalman Filter (Ekf)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Thermal-Enhanced Adaptive Interval Estimation in Battery Packs With Heterogeneous Cells

Zhang

Couto

Gill

et al. 2022

IEEE Trans. Contr. Syst. Technol.

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“…Namely, they may be characterized by different model parameters (capacity, internal resistance etc. ), different SOC levels, and different temperature distribution [39]. The above-mentioned heterogeneity among cells can be caused by manufacturing, temperature variability, and battery degradation.…”

Section: Problem Formulation and Motivationmentioning

confidence: 99%

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

Zhang¹,

Couto²,

Drummond³

et al. 2021

Preprint

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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.

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“…oped equivalent-circuit based models enabling simulation of current dynamics in parallel-connected systems. Similar models have also recently been applied to develop SOC estimators (Zhang et al, 2020), study the influence of cellto-cell variances on the thermal design of battery packs (Fill and Birke, 2021), and simulate the aging behavior of grid battery systems (Reniers and Howey, 2022). However, despite the existing literature, fundamental analysis of such systems remain challenging due to a lack of first-principles descriptions of current-sharing behavior in parallel-connected batteries.…”

Section: Introductionmentioning

confidence: 99%