基于高偏移阈值的补偿感应耦合电能系统传输特性分析
文献类型:期刊论文
作者 | 王侃![]() ![]() ![]() |
刊名 | 电力电容器与无功补偿
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出版日期 | 2017 |
卷号 | 38期号:4页码:164-170 |
关键词 | 感应耦合电能传输 PSS补偿 功率因数 补偿系数 |
ISSN号 | 1674-1757 |
其他题名 | Transmission Characteristic Analysis of Compensation Inductively Coupled Power System Based on High Deviation Threshold |
产权排序 | 1 |
通讯作者 | 王侃 |
中文摘要 | 在传统感应耦合电能传输(inductively coupled power transfer,ICPT)系统拓扑中,系统谐振频率的漂移会引起耦合效率的下降。针对该问题,本文提出一种新型的基于PSS(原边采用并联串联补偿,副边采用串联补偿)补偿的ICPT系统拓扑。对其电路模型进行了分析和建模,得出不同品质因数下,补偿系统的电压、电流增益、传输效率的特性曲线,该补偿拓扑具有较高的补偿因数;分析了系统中补偿系数对谐振元件电压电流的应力影响,选取合适的补偿系数以降低系统的设计成本。最后,设计了1台基于PSS补偿拓扑的ICPT系统样机,实验验证了对PSS补偿拓扑的特性分析。 |
英文摘要 | In the topology of traditional inductively coupled power transfer ( ICPT for short) system, the drift of reasonant frequency of the system can cause reduction of coupling efficiency. As for this issue, in this paper a kind of new type PSS ( the primary side adopts shunt -series compensation, the secondary a - dopts series compensation ) compensation, based on ICPT system topology is proposed. Its circuit model is analyzed, the model is set up, it is obtained such as the gain of voltage and current of compensation system, and the curve of transmission efficiency under different quality factors. The topology has higher compensation factor and the stress influence of the compensation coefficient in the system on the voltage and current of resonant components is analyzed, and the appropriate compensation coefficient is selected to reduce the design cost of system. Finally, a set of ICPT system sample based on PSS compensation is designed and the characteristic analysis for the PSS compensation topology is verified by the experiment. |
语种 | 中文 |
源URL | [http://ir.sia.cn/handle/173321/21120] ![]() |
专题 | 沈阳自动化研究所_装备制造技术研究室 |
作者单位 | 1.中国科学院大学 2.中国科学院沈阳自动化研究所 |
推荐引用方式 GB/T 7714 | 王侃,袁学庆,廖颜华. 基于高偏移阈值的补偿感应耦合电能系统传输特性分析[J]. 电力电容器与无功补偿,2017,38(4):164-170. |
APA | 王侃,袁学庆,&廖颜华.(2017).基于高偏移阈值的补偿感应耦合电能系统传输特性分析.电力电容器与无功补偿,38(4),164-170. |
MLA | 王侃,et al."基于高偏移阈值的补偿感应耦合电能系统传输特性分析".电力电容器与无功补偿 38.4(2017):164-170. |
入库方式: OAI收割
来源:沈阳自动化研究所
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