提高双有源桥变换器动态性能的预测电流模式控制OA北大核心
Predictive Current Mode Control of Dual-active-bridge Converter to Improve Its Dynamic Performance
提出一种预测电流模式控制算法,以提高双有源桥变换器在负载切换时的动态性能.首先,分析了双有源桥变换器开关周期内的电压、电流波形,推导出预测方程,在下一控制周期立即根据预测方程更新控制量,使得电流响应带宽接近开关频率,因此提高输出电压动态响应速度.然后,推导了输出电流瞬时值和电感电流瞬时值的代数关系,使用输出电流代替受开关振荡影响的电感电流以提高抗噪声能力.其次,建立了双有源桥的降阶模型,推导了传统双极点双零点2P2Z(two-pole tow-zero)电压模式控制器并和所提算法进行比较.最后,通过仿真和多种工况的实验结果表明,相比2P2Z电压模式控制,所提算法降低了变换器闭环输出阻抗,使得电感电流能够在一个控制周期内快速响应,极大提高了输出电压在负载切换时的动态性能.
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.
俞宏洋;李辉
上海电力大学自动化工程学院,上海 200090
动力与电气工程
双有源桥变换器预测电流模式控制输出阻抗动态性能
Dual-active-bridge ( DAB ) converterpredictive current mode controloutput impedancedynamic performance
《电源学报》 2024 (0z1)
25-33 / 9
上海市科委重点项目(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;Shanghai Civil Military Integration Development Project under the grant 2019-jmrh1-kj40
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