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Physics-based control-oriented reduced-order degradation model for LiNiMnCoO2 - graphite cell

机译:基于物理的控制导向阶下的LiniMnCOO2 - 石墨细胞下降阶劣劣化模型

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Li-ion battery performance degrades with aging and usage, and the degradation highly depends on how the cell is operated. As such, models used for system design and optimization should ideally capture the impact of those effects, and battery management system should take degradation into consideration and control cell operation carefully. Physics-based electrochemical models have shown the capability of predicting cell performance and degradation, but are computationally time consuming, often precluding its use in control-oriented design/optimization. Based on the constitutive laws which are widely adopted in the electrochemical models, a control-oriented reduced-order degradation model for a commercial LiNiMnCoO2/graphite cell is derived to improve computational efficiency without sacrificing model fidelity. Three primary degradation mechanisms that occur in a typical Li-ion cell are captured: 1) Solid Electrolyte Interface (SEI) layer growth, 2) SEI layer fracture and re-healing, and 3) Active Material loss. The extensive validation against a wide range of experimental data illustrates the ability of the model to accurately predict the capacity loss. (C) 2019 Elsevier Ltd. All rights reserved.
机译:锂离子电池性能随着老化和用途劣化,降低高度取决于电池的操作方式。因此,用于系统设计和优化的模型应理想地捕获这些效果的影响,电池管理系统应仔细考虑和控制细胞操作。物理基电化学模型表明了预测细胞性能和降解的能力,而是计算上耗时,通常会阻止其在面向控制的设计/优化中的使用。基于在电化学模型中广泛采用的本构规定,推导出用于商业LiniMnCOO2 /石墨电池的对导向的降低降低模型,以提高计算效率而不牺牲模型保真度。捕获典型锂离子电池中发生的三次初级降解机制:1)固体电解质界面(SEI)层生长,2)SEI层断裂和重新愈合,以及3)活性物质损失。针对广泛的实验数据的广泛验证说明了模型准确预测容量损耗的能力。 (c)2019 Elsevier Ltd.保留所有权利。

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