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16 pages, 5142 KB

Open AccessArticle

State of Charge Estimation of Single-Flow Zinc-Nickel Batteries Based on the Improved Unscented Kalman Filter and Extended Kalman Filter Algorithm

by Chunning Song, Haijing Gu and Yu Zhang

Processes 2025, 13(1), 231; https://doi.org/10.3390/pr13010231 - 15 Jan 2025

Cited by 3 | Viewed by 1608

Abstract

Single-flow zinc–nickel batteries are a novel type of flow batteries that feature a simple structure, large-scale energy storage capacity, and low cost. The state of charge (SOC) is a crucial indicator of battery performance, providing essential data for the management and control of the battery management system. However, in the estimation of SOC using a traditional unscented Kalman filter, the covariance matrix P often falls into a non-positive definite state during the decomposition steps, leading to algorithm failure. To address this issue, this paper incorporates the singular-value decomposition method into the unscented Kalman filter, resulting in an improved unscented Kalman filter algorithm. Considering the potential low accuracy of a single filtering method for SOC estimation, the improved unscented Kalman filter algorithm is combined with the extended Kalman filter for joint estimation. Experimental comparisons demonstrate that the improved unscented Kalman filter and extended Kalman filter joint estimation achieve higher estimation accuracy compared to using the improved unscented Kalman filter alone. Full article

(This article belongs to the Section Energy Systems)

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19 pages, 9925 KB

Open AccessArticle

Modeling and Simulation of Single Flow Zinc–Nickel Redox Battery Coupled with Multi-Physics Fields

by Chunning Song, Kaixuan Zhang and Nanjun Li

Batteries 2024, 10(5), 166; https://doi.org/10.3390/batteries10050166 - 19 May 2024

Cited by 5 | Viewed by 3709

Abstract

Metallic zinc (Zn) presents a compelling alternative to conventional electrochemical energy storage systems due to its environmentally friendly nature, abundant availability, high water compatibility, low toxicity, low electrochemical potential (−0.762 V vs. SHE), and cost-effectiveness. While considerable efforts have been devoted to enhancing the physical and chemical properties of zinc-ion battery materials to improve battery efficiency and longevity, research on multi-physics coupled modeling for a deeper understanding of battery performance remains relatively scarce. In this study, we established a comprehensive two-dimensional model for single-flow zinc–nickel redox batteries to investigate electrode reactions, current-potential behaviors, and concentration distributions, leveraging theories such as Nernst–Planck and Butler–Volmer. Additionally, we explored the distribution of the velocity field using the Brinkman theory in porous media and the Navier–Stokes equations in free-flow channels. The validated model, informed by experimental data, not only provides insights into the performance of the battery, but also offers valuable recommendations for advancing single-flow zinc–nickel battery technology. Our findings offer promising avenues for enhancing the design and performance of not only zinc–nickel flow batteries, but also applicable for other flow battery designs. Full article

(This article belongs to the Special Issue Energy Storage of Redox-Flow Batteries)

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16 pages, 4682 KB

Open AccessArticle

Joint Estimation of SOC and SOH for Single-Flow Zinc–Nickel Batteries

by Chunning Song, Yu Zhang, Qijin Ling and Shaogeng Zheng

Energies 2022, 15(13), 4781; https://doi.org/10.3390/en15134781 - 29 Jun 2022

Cited by 9 | Viewed by 2442

Abstract

The single-flow zinc–nickel battery (ZNB) is a new type of flow battery with a simple structure, large-scale energy storage, and low cost, and thus has attracted much attention in the battery field recently. The state of charge (SOC) and state of health (SOH) are key indicators of the battery, and their inaccurate estimation can damage the battery. However, little has been done so far to study how to jointly estimate SOC and SOH for the ZNB. In this paper, the method of adaptive IDUKF is proposed. A second-order equivalent circuit model is applied to improve the accuracy. At the same time, the double unscented Kalman filter (DUKF), which is optimized by the improved Harris hawk optimization (IHHO) algorithm, is used to estimate the SOC and parameters online. Then, the capacity update model is introduced to simulate the change in SOH. Finally, the proposed method is applied to a 16 Ah ZNB, and the experimental results confirm the validity of the proposed method. Full article

(This article belongs to the Special Issue Advanced Technologies in Redox Flow Batteries)

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18 pages, 3714 KB

Open AccessArticle

A Robust Algorithm for State-of-Charge Estimation under Model Uncertainty and Voltage Sensor Bias

by Yang Guo and Ziguang Lu

Energies 2022, 15(4), 1537; https://doi.org/10.3390/en15041537 - 19 Feb 2022

Cited by 11 | Viewed by 2814

Abstract

Accurate estimation of the state of charge (SOC) of zinc–nickel single-flow batteries (ZNBs) is an important problem in battery management systems (BMSs). A nonideal electromagnetic environment will usually cause the measured signal to contain nonnegligible noise and bias. At the same time, due to the influence of battery ageing, environmental temperature changes, and a complex reaction mechanism, it is difficult to establish a very accurate system model that can be applied to various complex working conditions. The unscented Kalman filter (UKF) is a widely used SOC estimation algorithm, but the UKF will reduce the estimation accuracy and divergence under the influence of inaccurate model and sensor errors. To improve the performance of the UKF, a robust desensitized unscented Kalman filter (RDUKF) is proposed to realize an accurate SOC estimation of batteries in the context of different disturbances. Then, the proposed method is applied to cases of error interference, such as Gaussian noise, voltage sensor drift, an unknown initial state, and inaccurate model parameters. The simulation and experimental results show that compared with the standard UKF algorithm, the proposed estimation algorithm can effectively suppress the influence of various errors and disturbances and achieve higher accuracy and robustness. Full article

(This article belongs to the Topic Energy Storage and Conversion Systems)

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17 pages, 5803 KB

Open AccessFeature PaperArticle

Equivalent Circuit Model Construction and Dynamic Flow Optimization Based on Zinc–Nickel Single-Flow Battery

by Shouguang Yao, Xiaofei Sun, Min Xiao, Jie Cheng and Yaju Shen

Energies 2019, 12(4), 582; https://doi.org/10.3390/en12040582 - 13 Feb 2019

Cited by 5 | Viewed by 3924

Abstract

Based on the zinc–nickel single-flow battery, a generalized electrical simulation model considering the effects of flow rate, self-discharge, and pump power loss is proposed. The results compared with the experiment show that the simulation results considering the effect of self-discharge are closer to the experimental values, and the error range of voltage estimation during charging and discharging is between 0% and 3.85%. In addition, under the rated electrolyte flow rate and different charge–discharge currents, the estimation of Coulomb efficiency by the simulation model is in good agreement with the experimental values. Electrolyte flow rate is one of the parameters that have a great influence on system performance. Designing a suitable flow controller is an effective means to improve system performance. In this paper, the genetic algorithm and the theoretical minimum flow multiplied by different flow factors are used to optimize the variable electrolyte flow rate under dynamic SOC (state of charge). The comparative analysis results show that the flow factor optimization method is a simple means under constant charge–discharge power, while genetic algorithm has better performance in optimizing flow rate under varying (dis-)charge power and state of charge condition in practical engineering. Full article

(This article belongs to the Special Issue Energy Storage and Management for Electric Vehicles)

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11 pages, 3921 KB

Open AccessArticle

Study on Electrode Potential of Zinc Nickel Single-Flow Battery during Charge

by Shouguang Yao, Peng Liao, Min Xiao, Jie Cheng and Wenwen Cai

Energies 2017, 10(8), 1101; https://doi.org/10.3390/en10081101 - 27 Jul 2017

Cited by 20 | Viewed by 8093

Abstract

In this study of zinc nickel single-flow batteries (ZNB), the ion concentration of the convection area and the electrode surface of the battery runner were investigated first. Then, the relationships between the electrode over-potential (or equilibrium potential) and the charge time were studied. This was based on the electrochemical reaction rate equation and the equilibrium potential equation, from which a mathematical model of the stack voltage (as affected by the internal parameters of the battery) was obtained. By comparison with experimental data, it was determined that the relative error of the simulated stack voltage of a 300 Ah battery was restricted to <0.62% while charging under the condition of 100 A constant-current charging. This shows that the mathematical model can accurately describe the dynamic characteristics of the battery stack voltage, and is very accurate for predicting the stack voltage of the battery during charging under 100 A constant-current charging conditions. Full article

(This article belongs to the Section D: Energy Storage and Application)

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