An effective management of the onboard energy storage system is a key point for the development of electric vehicles. This requires the accurate estimation of the battery state over time and in a wide range of operating conditions. The battery state is usually expressed as state-of-charge and state-ofhealth. Its estimation demands an accurate model to represent the static and dynamic behaviour of the battery. Developing such a model requires the online identification of the battery parameters. This paper aims at comparing the performance of two popular system identification techniques, i.e., the Extended Kalman Filter and the classic Least Squares method. A significant contribution of this work is the definition of a benchmark which is representative of the real use of the battery in an electric vehicle. Simulation results show the peculiarities of both methods and their effectiveness.

This paper aims at investigating and modelling the hysteresis in the relationship between state-of-charge and opencircuit voltage of lithium-iron-phosphate batteries. A first-order charge relaxation equation was used to describe the hysteresis dynamics. This equation was translated into a voltage-controlled voltage source and included within an equivalent electric circuit of the battery used in online state-of-charge estimators. The effectiveness of the obtained battery model was verified comparing simulated and experimental data.

This paper investigates the applicability of the scalar Preisach model to describe the hysteresis in the state of charge versus open-circuit voltage plane of lithium-iron-phosphate batteries. The model is implemented using the Everett function, identified with experimental data related to first-order reversal hysteresis branches. To show the effectiveness of the approach and the predictive capabilities of the Preisach model in this peculiar application, numerical simulations of a major hysteresis loop and a set of minor loops are compared with the experimental data

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The paper aims to provide a more accurate analysis of a magnetostrictive energy harvesting device by proposing a FEM model which, assuming a realistic nonlinear characteristic of the material, is able to describe the harvesting phenomena in presence of the eddy currents induced by the Villari effect. The study is focused on the investigation of the influence of those parameters, such as pre-stress and bias, on the field dynamics and, consequently, on the eddy currents loss phenomena which cannot be disregarded if a reliable prediction of the global performances of these devices is required. The numerical results are computed by considering a compressive stress-driven vibration source and show spatial profiles of the fields, losses, and recovered powers in different operating conditions. Comparisons with the linear model are also provided