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首页> 外文期刊>IEEE Transactions on Industrial Electronics >Estimation of State of Charge, Unknown Nonlinearities, and State of Health of a Lithium-Ion Battery Based on a Comprehensive Unobservable Model
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Estimation of State of Charge, Unknown Nonlinearities, and State of Health of a Lithium-Ion Battery Based on a Comprehensive Unobservable Model

机译：基于综合不可观测模型的锂离子电池充电状态，未知非线性和健康状态估算

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This paper considers the estimation of the state of charge and state of health for lithium-ion batteries, while an inclusive model is taken into account. The model includes two $RC$ subnetworks, which represent the fast and slow transient responses of the terminal voltage. Nevertheless, the linear part of the model is unobservable. On the other hand, the nonlinear behavior of the open-circuit voltage versus state of charge is also included in the model. The proposed observer tackles the aforementioned problems to attain a reliable estimation of the state of charge. Moreover, as opposed to the methods in which the nonlinearities or uncertainties in the model are disregarded or those terms are discarded using a conventional sliding-mode observer, an analytical method is considered to estimate the additive nonlinear or uncertainty term in the model. This approach leads to a very accurate model of the battery to be used in a battery management system. Moreover, an online parameter estimation method is proposed to estimate the battery's state of health. The proposed scheme benefits from an adaptive rule for the online estimation of the series resistance in the lithium-ion battery based on the accurately identified model. Experimental tests certify the performance and feasibility of the proposed schemes.
机译：本文考虑了锂离子电池的充电状态和健康状态的估计，同时考虑了包含性模型。该模型包括两个 $ RC $ 子网络，它们代表了终端电压的快速和慢速瞬态响应。然而，模型的线性部分是不可观察的。另一方面，模型中还包括开路电压与电荷状态的非线性行为。提议的观察者解决了上述问题，以获得对充电状态的可靠估计。此外，与忽略模型中的非线性或不确定性或使用常规滑模观测器丢弃那些项的方法相反，可以考虑采用分析方法来估计模型中的累加非线性或不确定性项。这种方法可以在电池管理系统中使用非常精确的电池模型。此外，提出了一种在线参数估计方法来估计电池的健康状态。所提出的方案受益于基于精确识别的模型的在线估算锂离子电池串联电阻的自适应规则。实验测试证明了所提出方案的性能和可行性。

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