The last decade has seen a significant increase in electromobility. With this trend, it will be necessary to start dealing with the subsequent recycling and disposal of electric vehicles, including the batteries. Currently, the battery is one of the most expensive components of an electric vehicle, which in part hinders their sufficient competitiveness with the internal combustion engine. Furthermore, the lifetime of a battery for use in an electric vehicle is assumed to be 8–10 years/160,000 km, after which the battery capacity drops to 80% of the initial capacity. However, it transpires that a battery at the end of its life in an electric vehicle does not need to be disposed of immediately, but can be used in other applications wherein the emphasis is not so strictly on an excellent power and capacity capability related to its volume or weight. Thus, reusing batteries can help reduce their cost for use in electric vehicles, increase their utility value, and reduce the environmental impact of batteries. This paper discusses methods for researching battery aging in electric vehicles, testing methods for batteries during the transition from first life to second life, and prospective battery second-life use and its specifics. The main contribution of this perspective article is to provide a comprehensive view of the current state of second-life batteries and an overview of the challenges that need to be overcome in order to use them on a large industrial scale.

Electrochemical impedance spectroscopy (EIS) is a measurement method widely used for non-destructive analysis and diagnostics in various electrochemical fields. From the measured dependence of the battery impedance on the frequency, it is possible to determine the parameters of various equivalent electrical circuit models of the battery. The conventional method of battery measurement using single-sine EIS is currently one of the most widely used methods for the analysis of lithium-ion batteries. However, its most significant disadvantage is the relatively long measurement time. For this reason, there is a growing demand for faster methods using fast-Fourier transform or pseudo-random sequences. A description of various EIS methods applications is provided in this paper. Graphical abstract

The efficiency of fibre reinforcement in concrete can be drastically increased by orienting the fibres using a magnetic field. This orientation occurs immediately after pouring fresh concrete when the fibres can still move. The technique is most relevant for manufacturing prefabricated elements such as beams or columns. However, the parameters of such a field are not immediately apparent, as they depend on the specific fibre reaction to the magnetic field. In this study, a numerical model was created in ANSYS Maxwell to examine the mechanical torque acting on fibres placed in a magnetic field with varying parameters. The model consists of a single fibre placed between two Helmholtz coils. The simulations were verified with an experimental setup as well as theoretical relationships. Ten different fibre types, both straight and hook-ended, were examined. The developed model can be successfully used to study the behaviour of fibres in a magnetic field. The fibre size plays the most important role together with the magnetic saturation of the fibre material. Multiple fibres show significant interactions.

A key part in optimising the performance of fibre-reinforced concrete (FRC) lies in ensuring the correct orientation of fibres, especially in structural components where directional stress resistance is critical, such as beams and slabs. However, assessing the orientation of fibres in hardened concrete poses a significant challenge. This study explores the use of the non-destructive evaluation of fibre orientation within FRC by measuring a quality factor (Q-factor) of an electrical coil with an inserted FRC specimen. Through numerical simulations, the effectiveness of the Q-factor measurements were evaluated using several scenarios of fibre positions, quantity, and orientations. It was discovered that the Q-factor is sensitive to these variables and, therefore, it is a suitable tool for material diagnostics.