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Lyapunov-Based Thermal Fault Diagnosis of Cylindrical Lithium-Ion Batteries

机译:基于Lyapunov的圆柱形锂离子电池的热故障诊断

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摘要

With the continuous improvement of lithium-ion batteries in energy and power density, their safety and reliability concern is becoming increasingly urgent for energy storage systems. Thermal faults are one of the most critical faults in lithium-ion batteries that must be diagnosed in real time, because they can be potentially catastrophic. Motivated by this fact, a diagnostic algorithm is presented in this article to diagnose several thermal faults in cylindrical lithium-ion batteries, including heat generation fault and thermal parameter fault. This diagnostic algorithm is based on an electrothermal-coupled model describing both electrical and thermal dynamic behaviors of batteries. A Lyapunov-based battery internal resistance estimator is proposed to describe the dynamics of the surface and the core temperature of a battery cell, because the heat generation caused by the electrical loss is highly dependent on battery resistance. An observer-based fault detection framework is then established based on surface temperature measurements and resistance estimates, where stability and convergence are guaranteed by Lyapunov direct method. Furthermore, the adaptation law of fault evaluation threshold is designed to suppress modeling and measurement uncertainties. Simulation studies are presented to illustrate the effectiveness of the proposed model and diagnosis algorithm.
机译:随着锂离子电池的能量和功率密度的不断改进,它们的安全性和可靠性问题对于储能系统而言越来越紧迫。热故障是锂离子电池中最关键的故障之一,必须实时诊断,因为它们可能是灾难性的。通过此事实,本文提出了一种诊断算法,以诊断圆柱形锂离子电池中的几个热故障,包括发热故障和热参数故障。该诊断算法基于电热耦合模型,描述了电池的电气和热动力学行为。提出了基于Lyapunov的电池内阻估计器来描述电池电池的表面和核心温度的动态,因为电损耗引起的热量高度依赖于电池电阻。然后基于表面温度测量和电阻估计建立了基于观察者的故障检测框架,其中Lyapunov直接方法保证了稳定性和收敛性。此外,故障评估阈值的适应法旨在抑制建模和测量不确定性。提出了仿真研究以说明所提出的模型和诊断算法的有效性。

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