整流器(神经网络)
转换器
波形
电气工程
电压
功率(物理)
工程类
电子工程
计算机科学
物理
人工神经网络
量子力学
随机神经网络
机器学习
循环神经网络
作者
Grzegorz Wrona,Mariusz Zdanowski,Przemysław Trochimiuk,Jacek Rąbkowski,Radosław Sobieski
出处
期刊:Energies
[MDPI AG]
日期:2023-08-04
卷期号:16 (15): 5797-5797
被引量:5
摘要
This work presents the experimental validation of a 40 kW electric vehicle (EV) charger. The proposed system comprises two 20 kW modules connected in parallel at the input and output. Each module has two stages—as a grid converter Vienna Rectifier (VR) was chosen, and as an isolated DC/DC stage, two Series-Resonant Dual-Active-Bridges (SRDABs) in input-series-output-parallel (ISOP) configurations were applied. The AC/DC and DC/DC stages were enclosed in 2U rack standard housing. A bipolar DC-link with ±400 V DC voltage was employed to connect both stages of the charger module while the charger’s output is dedicated to serving 800 V batteries. VRs operated at 66 kHz switching frequency and the SRDABs operated at 100 kHz. The converters used in the charger structure were based on silicon carbide (SiC) power devices. The description and parameters of the built hardware prototypes of both—AC/DC and DC/DC—converters are provided. Moreover, the experimental validation of each stage and the whole charging system, including oscilloscope waveforms and power analyzer measurements at nominal power, are included. Such a configuration enables energy conversion with high efficiency without a negative impact on the grid and high-quality grid waveforms.
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