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With the popularity of Electrical Vehicles (EVs), Lithium-ion battery industry is developing rapidly. To ensure the battery safe usage and to reduce its average lifecycle cost, an accurate State of Charge (SOC) tracking algorithms for real-time implementation are required for different applications. Many SOC estimation methods have been proposed in the literature. However, only a few of them consider the real-time applicability. This paper classifies the recently proposed online SOC estimation methods into five categories. Their principal features are illustrated, and the main pros and cons are provided. The SOC estimation methods are compared and discussed in terms of accuracy, robustness, and computation burden. Afterward, as the most popular type of model based SOC estimation algorithms, seven nonlinear filters existing in literature are compared in terms of their accuracy and execution time as a reference for online implementation.

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Lithium-ion (Li-ion) batteries are complex energy storage devices with their performance behavior highly dependent on the operating conditions (i.e., temperature, load current, and state-of-charge (SOC)). Thus, in order to evaluate their techno-economic viability for a certain application, detailed information about Li-ion battery performance behavior becomes necessary. This paper proposes a comprehensive seven-step methodology for laboratory characterization of Li-ion batteries, in which the battery's performance parameters (i.e., capacity, open-circuit voltage (OCV), and impedance) are determined and their dependence on the operating conditions are obtained. Furthermore, this paper proposes a novel hybrid procedure for parameterizing the batteries' equivalent electrical circuit (EEC), which is used to emulate the batteries' dynamic behavior. Based on this novel parameterization procedure, the performance model of the studied Li-ion battery is developed and its accuracy is successfully verified (maximum error lower than 5% and a mean error below 8.5 mV) for various load profiles (including a real application profile), thus validating the proposed seven-step characterization methodology.

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