Nowadays, battery storage systems are very important in both stationary and mobile applications. In particular, lithium ion batteries are a good and promising solution because of their high power and energy densities. The modeling of these devices is very crucial to correctly predict their state of charge (SoC) and state of health (SoH). The literature shows that numerous battery models and parameters estimation techniques have been developed and proposed. Moreover, surveys on their electric, thermal, and aging modeling are also reported. This paper presents a more complete overview of the different proposed battery models and estimation techniques. In particular, a method for classifying the proposed models based on their approaches is proposed. For this classification, the models are divided in three categories: mathematical models, physical models, and circuit models.

Today's residential battery energy storage systems (BESSs) are off the shelf products used to increase the selfconsumption of residential photovoltaic (PV) plants and to reduce the losses related to energy transfer in distribution grids. This work investigates the economic viability of adding a BESS to a residential grid-connected PV plant by using a methodology for optimising the size of the BESS. The identification of the optimal size which minimises the total cost of the system is not trivial; indeed, it is a trade-off between OPEX and CAPEX, which are mainly affected by the battery technology, usage profile, expected lifetime, and efficiency. Here, an analysis of the opportunity to install a storage system together with a grid-connected residential PV plant is performed. Three typical low-voltage prosumers (Italy, Switzerland, and the UK) are investigated in order to take into account the different legislative and tariff framework over Europe. Numerical results reported here show that present costs of storages are still too high to allow an economic convenience of the storage installation. Moreover, an indication of the necessary incentives to allow the spreading of these systems is given.

A reliable and accurate estimation of the parameters of batteries equivalent models is of paramount importance in many applications. This paper is focused on electric vehicle framework. A simplified method for estimating these parameters is presented and validated. The proposed methodology introduces the concept of apparent state of discharge (ASOD), i.e., the traditional state of discharge adjusted in order to take into account the effects of current and temperature. This ASOD is, then, used to estimate the open circuit voltage and, consequently, the output voltage of the battery cells. The effectiveness of this method has been experimentally tested on a real Lithium-ion cell in order to estimate the expected range of an electric vehicle

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Lithium-ion capacitors (LiC) are novel storage devices with a high power density and high energy density compared to conventional supercapacitors. This paper proposes a method to validate the previously developed characterization and modeling methods, which are the same as those used for a conventional supercapacitor with double layer activated carbon technology. This paper presents two relevant contributions. First, a full frequency range model and the experimental parameter identification of two kinds of LiC cells are presented. In order to extend the LiC cell parameter identification to a module composed of several series-connected cells, an aggregate model of the LiC module was investigated and validated. The results of experiments and numerical simulations demonstrate the value and effectiveness of the proposed model when the cells operate at room temperature.