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 self‐consumption 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.

Lithium‐ion batteries are a key technology for current and future energy storage in mobile and stationary application. In particular, they play an important role in the electrification of mobility and therefore the battery lifetime prediction is a fundamental aspect for successful market introduction. Numerous studies developed ageing models capable of predicting battery life span. Most of the previous works compared the effect of the ageing factors to a battery’s cycle life. These cycles are identical, which is not the case for electric vehicles applications. Indeed, most of the available information is based on results from laboratory testing, under very controlled environments, and using ageing protocols, which may not correctly reflect the actual utilization. For this reason, it is important to link the effect of duty cycles with the ageing of the batteries. This paper proposes a simple method to investigate the effect of the duty cycle on the batteries lifetime through tests performed on different cells for different kinds of cycle. In this way, a generic complex cycle can be seen as a composition of elemental cycles by means of Rainflow procedures. Consequently, the ageing due to any cycle can be estimated starting from the knowledge of simpler cycles.

Lithium-ion capacitors (LiCs) are novel storage devices with a high power density and high energy density compared to conventional supercapacitors (SCs). This paper proposes a method to validate the previously developed characterization and modeling methods, which are the same as those used for a conventional SC 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.