• Energy Research
• 2021-2025close

Nowadays, the implementation of smart charging concepts and management strategies with vehicle-to-everything (V2X) functionalities, is required to address the increasing number of battery electric buses (BEBs) in cities. However, the introduction of these new functionalities to the charging systems might affect the lifetime of the charging infrastructure. This has not been investigated yet, although it is an important aspect for the BEB operators. Therefore, this paper performs a detailed reliability assessment to study the impact of smart and bidirectional (V2X) charging on the lifetime of SiC-based high-power off-board charging infrastructure used for BEBs in a depot for overnight charging. In this paper, four different charging current profiles, generated by a smart charging algorithm, are considered. In addition, an electro-thermal model of the charging system is developed to accurately estimate the junction temperature of the switching devices when subjected to the applied charging current profiles. The thermal stress is converted into a number of cycles to failures and accumulated damage by means of a rainflow cycle counting algorithm, a lifetime model and Miner’s damage rule. Finally, a Monte Carlo analysis and a Weibull probability function fit are applied to obtain the system reliability. The results have demonstrated that smart charging strategies can improve the lifetime of the charging system by at least a factor of three compared to conventional uncoordinated charging. Moreover, an uncoordinated charging strategy fails to fulfill the lifetime requirements in the parts per million range, while bidirectional charging could even further enhance the lifetime with a factor of one and a half.

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.

Modular multilevel converters (MMCs) with integrated battery energy storage systems (BESSs) are becoming crucial for modern power grids. This paper investigates the modeling and control of a grid-connected MMC-BESS, with a specific emphasis on state-of-charge (SoC) balancing. Compared to conventional hard arm SoC balancing control (HASBC), this paper proposes an alternative soft arm SoC balancing control (SASBC). The simulation results and analysis indicate the following: 1. SASBC provides superior performance in achieving SoC balance both between and within the arms, as compared to HASBC. 2. The MMC-BESS power fluctuates between phases, arms, and individual submodules to balance the SoC of batteries. After the accomplishment of SoC equalization, the power is equally distributed, and the circulating current is well eliminated. 3. MMC-BESS can operate in both the charging and discharging modes, and the total harmonic distortion (THD) of the output current is reduced from 6.80% to 1.13% after SoC balancing is achieved. 4. A robustness test shows the control system’s effective performance in handling component variations.

This paper focuses on the development and experimental validation of a single-phase modular multilevel converter (MMC) based on a battery energy storage system (BESS) for residential uninterruptible power supply (UPS) with two-level active SoC balancing control. The configuration and mathematical modeling of the single-phase MMC-BESS are first presented, followed by the details of the control strategies, including dual-loop output voltage and current control in islanded mode, grid-connected control, circulating current control, and two-level active state-of-charge (SoC) balancing control. The design and optimization of the quasi-proportional-resonant (QPR) controllers were investigated by using particle swarm optimization (PSO). Simulation models were built to explore the operating characteristics of the UPS under islanded mode with an RL load and grid-connected mode and assess the control performance. A 500 W experimental prototype was developed and is herein presented, including results under different operating conditions of the MMC-BESS. The experimental results show that for both RL load and grid-connected tests, balancing was achieved. The response time to track the reference value was two grid periods (0.04 s). In the islanded mode test, the THD was 1.37% and 4.59% for the voltage and current, respectively, while in the grid-connected mode test, these values were 1.72% and 4.24% for voltage and current, respectively.

This paper describes smart power management and charging scheduling strategy for a multiple port electric vehicle (EV) charging station, connected to battery storage systems and renewable energy sources. The charging station can charge different types of EVs, like electric scooters and passenger cars at different power levels. The energy management optimizes the usage of the power sources to fulfill the charging demand by analyzing the overall load demand, the electricity tariff, and the information provided by the EV user. The station's control system is set up to satisfy the charging demand primarily with a solar photovoltaic (PV) array and an energy storage system (ESS) as a battery. In the case of PV power generation and battery power shortage, it draws power from the grid to fulfill the charging demand. Additionally, a charging scheduling strategy is described in this paper in which the charging current setpoint for each charger is estimated by an optimization process in the local charger controller. The overall system management and charging scheduling are simulated and verified in the MATLAB/Simulink environment.

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.