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引用次数: 14
摘要
经典的DC/DC变换器通常由电感和电容器组成，如降压变换器、升压变换器、降压-升压变换器、lo变换器和cuk变换器。由于传统的变换器都是由电容器和电感组成的，所以它们具有体积大、功率密度低的特点。该开关电感已成功应用于DC/DC变换器中，为构建高功率密度变换器开辟了道路。例如，麻省理工学院的John G. Kassakian教授为21世纪未来的电动汽车设计了一种新的供电系统(见IEEE Spectrum, p.22-7, 1996)。该系统的核心是一个两象限DC/DC转换器，在+42 V和-14 VDC之间进行转换。本文讨论了变换器的工作模式及其神经网络控制。
Switched inductor two-quadrant DC/DC converter with neural network control
Classical DC/DC converters usually consist of inductors and capacitors such as buck converter, boost converter, buck-boost converter, Luo-converters and Cuk-converter. Because all classical converters consist of capacitors and inductors, they have big size and low power density. The switched-inductor has been successfully employed in DC/DC converters and opened the way to build the converters with high power density. For example, Professor John G. Kassakian of MIT designed a new power supply system for the future electric car in the 21st century (see IEEE Spectrum, p.22-7, 1996). The heart of this system is a two-quadrant DC/DC converter operating the conversion between +42 V and -14 VDC. In this paper the author discusses the operating modes of the converter and its control by neural nets.
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