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Lithium-ion batteries (LIBs) from electrified vehicles (EVs) that have reached the automotive end of life (EoL) may provide a low-cost, highly available energy storage solution for grid-connected systems, such as peak shaving and ancillary services. There are several issues related to the integration of second life batteries (SLBs) in power systems, such as the variability of the pack design and cell chemistry, in-field assessments of the state of health (SoH), and estimations of the expected lifetimes of SLBs in different power system applications. Model-based approaches are commonly used in the automotive industry for estimating/predicting the capacity and power fade trajectories of LIBs during their life. However, a large variety of models are available with different fidelities, complexities, and computational costs. The accuracy of these estimations is critical for the derivation of business models for SLB applications. This paper presents a qualitative and quantitative assessment of the performance of two well-accepted, state-of-the-art aging models, initially developed for automotive applications and here applied to different SLB applications to predict both the capacity and power fade. These models are evaluated with respect to several performance metrics, such as fidelity of estimation and capability of extrapolation outside the calibration data range. The considered models are classified as semi-empirical physics-based and empirical models, respectively. Three different SLB power profiles, bulk energy for DC fast charge stations and two frequency regulation profiles, are considered, corresponding to different ranges of the SoC, C-rates, and battery temperatures, with the aim of exciting different aging mechanisms. The numerical results provide insight for the selection of aging models for SLB applications based on their performances and limitations. [ABSTRACT FROM AUTHOR]

Neutral Point Clamped (NPC) converters with n levels are traditionally controlled in such a way that the DC-link capacitors operate at 1/(n − 1) of the total DC-link voltage level. The voltage level across the DC-link capacitors has to be properly regulated by the capacitor unbalance control to contain the harmonic distortion of the converter output voltages. State-of-the-art modulation techniques address the problem of the DC-link voltage regulation for NPC inverters. However, they highly show reduced performance when unbalanced DC-link voltages are considered. In this paper, a novel Space Vector Modulation (SVM) is proposed for NPC converters with an unbalanced DC-link. At every modulation interval, the technique defines the optimal switching pattern by considering the actual unbalanced DC-link conditions. The proposed modulation allows improving the harmonic content of the NPC converter output voltage with respect to a traditional ML-SVM, when the same operating conditions are considered. As an extension, the proposed modulation technique will guarantee the same output voltage quality of a traditional ML-SVM with unbalanced DC-link, while improving the conversion efficiency thanks to a reduction of switching frequency. [ABSTRACT FROM AUTHOR]

A Multi-Source Electric Vehicle Charging Station (MS-EVCS) is a local entity that combines the grid energy with Distributed Energy Resources (DERs) with the aim of reducing the grid impact due to electric vehicles (EVs) charging events. The integration of stationary and in-vehicle Energy Storage Systems (ESSs) in MS-EVCSs has gained increasing interest thanks to the possibility of storing energy at off-peak hours to be made available at peak-hours. However, the ESS technology and the vehicle-to-grid (V2G) concept show several issues due to cost, battery life cycle, reliability, and management. The design of the MS-EVCS energy management system is of primary importance to guarantee the optimal usage of the available resources and to enhance the system benefits. This study presents a novel energy management strategy for Real-Time (RT) control of MS-EVCS considering DERs, stationary ESS, and V2G. The proposed energy management control allows defining the MS-EVCS control policy solving several cascaded-problems with the aim of achieving the minimum operating cost when the battery degradation and the stochastic nature of the sources are considered. The key feature of the proposed methodology is the lower computational effort with respect to traditional optimal control methodologies while achieving the same optimal solution. [ABSTRACT FROM AUTHOR]