A State-of-Charge (SOC) real-time estimation plays an essential role in effective energy management. This paper proposes the use of an Artificial Neural Network (ANN) to design a state-of-charge estimator for a Graphite/LiCoO2 lithium-ion battery pack. The software MATLAB was used to develop and test several network configurations to find the ideal weights for the ANN. The results demonstrate that the Mean Squared Error (MSE) achieved renders the ANN as an effective technique. Thus, it predicted the battery bank’s SOC values with accuracy using only voltage, current, and charge/discharge time as inputs.

Power quality problems are not new to power systems, but they cannot be overlooked. In the context of Smart Grids, power systems are undergoing a transformation characterized by the high penetration of renewable sources and electronic devices in the grids, in addition to greater computerization of operations. Thus, alternatives in the representation and visualization of these integrated quality parameters become more and more necessary, both for a better understanding of these phenomena and for advanced applications with the use of images.With this in mind, this paper aims to present an alternative for visualizing PQ disturbances through 2-D images from scalograms based on the continuous wavelet transform (CWT) and multiresolution analysis. For this, signals from three dierent sources, mathematical equations, models of transmission anddistribution of energy in MATLAB / Simulink, and real signals from a database were used. For the creation of the scalogram images, the signal processing technique, and the use of a color map were used to show the performance. The results showed the eciency of the method for visualization and characterization of addressed disturbances. The enkaptics phenomena were also highlighted, which show the simultaneity and relationship between dierent types of signal variation. The work contributes to using signals from dierent sources, synthetic, from simulation or real signals, to oer a methodology that describes tools for a method of visualization.

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Este trabalho apresenta a implementação e testes de controladores PID com escalonamento de ganhos utilizando lógica fuzzy. Os testes descritos foram realizados na Planta Experimental de Nível do laboratório de Controle do Instituto Federal Fluminense Campus Campos Centro. Para o escalonamento de ganhos do PID foram utilizadas duas abordagens diferentes: a primeira abordagem foi proposta por Campos e Saito (2004) e utiliza a referência do sistema como entrada; a segunda proposta por Zhao, Tomizuka e Isaka (1993) utiliza o erro e a variação do erro como entrada do sistema fuzzy. Para melhor elaboração dos controladores foi realizada uma caracterização do sistema a partir de técnicas de identificação e um mapeamento das regiões de operação do sistema. A partir dos resultados obtidos, uma análise de desempenho dos controladores foi elaborada com o intuito de verificar suas respectivas performances e compará-los a fim de identificar o melhor controlador dentre os testados para a aplicação.

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