电源学报2024，Vol.22Issue(z1)：25-33,9.DOI:10.13234/j.issn.2095-2805.2024.S1.25
提高双有源桥变换器动态性能的预测电流模式控制
Predictive Current Mode Control of Dual-active-bridge Converter to Improve Its Dynamic Performance
摘要
Abstract
A predictive current mode control algorithm is proposed in this paper to improve the dynamic performance of a dual-active-bridge ( DAB ) converter during load switching.First,the voltage and current waveforms of the DAB converter during a switching cycle are analyzed,and the prediction equation is derived.In the next control cycle,the control value is updated immediately according to the prediction equation,so that the current response bandwidth is close to the switching frequency,thereby improving the output voltage dynamic response speed.Then the algebraic relationship between the instantaneous value of output current and that of inductance current is also deduced,and the output current is used to replace the inductance current affected by the switching oscillation to improve the noise immunity.Second,a reduced-order model of DAB is established,and the traditional two-pole two-zero( 2P2Z ) voltage mode controller is deduced,which is further compared with the proposed algorithm.Finally,simulation results and experimental results under various operating conditions show that compared with the 2P2Z voltage mode control,the proposed algorithm reduces the closed-loop output impedance of the converter,enables the inductance current to respond quickly in a control cycle,and greatly improves the dynamic performance of output voltage during load switching.关键词
双有源桥变换器/预测电流模式控制/输出阻抗/动态性能Key words
Dual-active-bridge ( DAB ) converter/predictive current mode control/output impedance/dynamic performance分类
信息技术与安全科学引用本文复制引用
俞宏洋,李辉..提高双有源桥变换器动态性能的预测电流模式控制[J].电源学报,2024,22(z1):25-33,9.基金项目
上海市科委重点项目(20dz1206100) （20dz1206100）
上海市军民融合发展专项项目(2019-jmrh1-kj40)This work is supported by Shanghai Science and Technology Commission Program under the grant 20dz1206100 （2019-jmrh1-kj40）
Shanghai Civil Military Integration Development Project under the grant 2019-jmrh1-kj40 （）
