The global promotion of electric vehicles (EVs) through various incentives has led to a significant increase in their sales. However, the prolonged charging duration remains a significant hindrance to the widespread adoption of these vehicles and the broader electrification of transportation. While DC-fast chargers have the potential to significantly reduce charging time, they also result in high power demands on the grid, which can lead to power quality issues and congestion. One solution to this problem is the integration of a battery energy storage system (BESS) to decrease peak power demand on the grid. This paper presents a review of the state-of-the-art use of DC-fast chargers coupled with a BESS. The focus of the paper is on industrial charger architectures and topologies. Additionally, this paper presents various reliability-oriented design methods, prognostic health monitoring techniques, and low-level/system-level control methods. Special emphasis is placed on strategies that can increase the lifetime of these systems. Finally, the paper concludes by discussing various cooling methods for power electronics and stationary/EV batteries.

This paper develops a multi-objective co-design optimization framework for the optimal sizing and selection of battery and power electronics in hybrid battery energy storage systems (HBESSs) connected to the grid. The co-design optimization approach is crucial for such a complex system with coupled subcomponents. To this end, a nondominated sorting genetic algorithm (NSGA-II) is used for optimal sizing and selection of technologies in the design of the HBESS, considering design parameters such as cost, efficiency, and lifetime. The interoperable framework is applied considering three first-life battery cells and one second-life battery cell for forming two independent battery packs as a hybrid battery unit and considers two power conversion architectures for interfacing the hybrid battery unit to the grid with different power stages and levels of modularity. Finally, the globally best HBESS system obtained as the output of the framework is made up of LTO first-life and LFP second-life cells and enables a total cost of ownership (TCO) reduction of 29.6% compared to the baseline.

This paper presents a comprehensive performance assessment of a two-stage power electronic (PE) converter for interfacing the grid of a lithium-ion battery energy storage system (Li-BESS) for building-integrated PV (BIPV) applications. A performance assessment of the control system was conducted for the two-stage PE interface with a common DC-link, which consisted of a bi-directional boost converter with a cascaded PI controller and an AC/DC converter with proportional-integral (PI) and proportional-resonant (PR) controllers. The assessment covered loss analysis and useful lifetime estimation for the 10 kW PE interface with a wide-bandgap SiC power MOSFET at different loads for both the charging and discharging modes of a 50 kWh lithium-ion battery system. Additionally, a performance comparison of various switching frequencies was performed. It was observed that the system was stable up to a switching frequency of 30 kHz, and that increasing the switching frequency improved the responsiveness of the converter by decreasing the settling time; however, there were diminishing returns at higher switching frequencies. To obtain a proper balance between responsiveness and lower loss, a switching frequency of 10 kHz was selected.

Battery health data from real-world applications are vital for optimizing and predicting battery lifetime. This study presents the design and verification of an active battery-diagnostic system and method to collect such data. The system measures battery pack capacity and resistance by applying a diagnostic protocol via a bi-directional charger. This was demonstrated on a stationary-energy-storage application, under real-world conditions, to verify the system’s design requirements. Measurements at the start and the end of the demonstration period of a month resulted in an observed degradation of 1.79 ± 0.34% battery capacity and an increase of 1.42 ± 0.75% in battery resistance. The successful measurements of capacity and resistance prove the compatibility of the system with real-world battery systems and confirm the design requirements were met. The system was able to perform autonomous and in situ measurements while only requiring the addition of software to the battery management system and by using the bi-directional charger of the energy storage system. By repeatedly applying the same diagnostic protocol over time, this system enables consistent tracking of battery health.