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A Novel Model-Based Estimation Scheme for Battery-Double-Layer Capacitor Hybrid Energy Storage Systems

机译:电池双层电容器混合储能系统的基于模型的新型估计方案

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Battery-double-layer capacitor (DLC) units are becoming popular hybrid energy storage systems (HESS) for vehicle propulsion, auxiliary power units, and renewable energy applications. Safe and optimal operation of the HESS requires real-time monitoring of its constituent subsystems. In this paper, we use a model-based approach to monitor HESS behavior and propose an online combined state and parameter estimation scheme using coupled electrical-thermal dynamical models for each subsystem. In particular, we focus on an HESS composed of a lead-acid (PbA) battery and a DLC for which experiments have been designed to identify the initial model parameters. The estimation scheme uses a novel cascaded observer-based structure which: 1) is designed based on sliding mode methodology and 2) exploits the coupling of the electrical and thermal dynamics. Using Lyapunov's arguments, theoretical conditions are derived which characterize the convergence of the state and parameter estimates in the presence of uncertainties. The effectiveness of the estimation scheme is evaluated via simulation and experimental studies on the PbA battery, the DLC, and the HESS system.
机译:电池双层电容器(DLC)单元正成为流行的混合动力储能系统(HESS),用于车辆推进,辅助动力单元和可再生能源应用。 HESS的安全和最佳运行要求对其组成子系统进行实时监控。在本文中,我们使用基于模型的方法来监视HESS行为,并针对每个子系统使用耦合的电热动力学模型提出一种在线组合状态和参数估计方案。特别是,我们专注于由铅酸(PbA)电池和DLC组成的HESS,针对这些HESS设计了旨在识别初始模型参数的实验。该估计方案使用了一种新颖的基于观察者的级联结构,该结构:1)基于滑模方法进行设计,2)利用电和热动力学的耦合。利用李雅普诺夫的观点,得出了在存在不确定性的情况下表征状态和参数估计收敛的理论条件。通过对PbA电池,DLC和HESS系统的仿真和实验研究,评估了评估方案的有效性。

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