基于滤波X最小均方差(filtered-X least mean square,简称FXLMS)控制方法实施振动主动控制的基本结构,提出了参考信号自提取的控制器结构和算法,直接利用系统误差信号获得对原激扰信号的一个估计,并用估计值作为自适应滤波器的参考信号...基于滤波X最小均方差(filtered-X least mean square,简称FXLMS)控制方法实施振动主动控制的基本结构,提出了参考信号自提取的控制器结构和算法,直接利用系统误差信号获得对原激扰信号的一个估计,并用估计值作为自适应滤波器的参考信号,以实现与外激扰信号的相关性。在针对控制算法进行Matlab仿真分析的基础上,构建了压电机敏柔性板试验模型和测控平台,并进行了算法验证。试验结果表明,该控制算法不仅实现了参考信号从振动结构中直接提取,并具有较快的收敛速度和良好的控制效果。展开更多
In order to characterize the voltage behavior of a lithium-ion battery for on-board electric vehicle battery management and control applications,a battery model with a moderate complexity was established.The battery o...In order to characterize the voltage behavior of a lithium-ion battery for on-board electric vehicle battery management and control applications,a battery model with a moderate complexity was established.The battery open circuit voltage (OCV) as a function of state of charge (SOC) was depicted by the Nernst equation.An equivalent circuit network was adopted to describe the polarization effect of the lithium-ion battery.A linear identifiable formulation of the battery model was derived by discretizing the frequent-domain description of the battery model.The recursive least square algorithm with forgetting was applied to implement the on-line parameter calibration.The validation results show that the on-line calibrated model can accurately predict the dynamic voltage behavior of the lithium-ion battery.The maximum and mean relative errors are 1.666% and 0.01%,respectively,in a hybrid pulse test,while 1.933% and 0.062%,respectively,in a transient power test.The on-line parameter calibration method thereby can ensure that the model possesses an acceptable robustness to varied battery loading profiles.展开更多
文摘基于滤波X最小均方差(filtered-X least mean square,简称FXLMS)控制方法实施振动主动控制的基本结构,提出了参考信号自提取的控制器结构和算法,直接利用系统误差信号获得对原激扰信号的一个估计,并用估计值作为自适应滤波器的参考信号,以实现与外激扰信号的相关性。在针对控制算法进行Matlab仿真分析的基础上,构建了压电机敏柔性板试验模型和测控平台,并进行了算法验证。试验结果表明,该控制算法不仅实现了参考信号从振动结构中直接提取,并具有较快的收敛速度和良好的控制效果。
基金Project(50905015) supported by the National Natural Science Foundation of China
文摘In order to characterize the voltage behavior of a lithium-ion battery for on-board electric vehicle battery management and control applications,a battery model with a moderate complexity was established.The battery open circuit voltage (OCV) as a function of state of charge (SOC) was depicted by the Nernst equation.An equivalent circuit network was adopted to describe the polarization effect of the lithium-ion battery.A linear identifiable formulation of the battery model was derived by discretizing the frequent-domain description of the battery model.The recursive least square algorithm with forgetting was applied to implement the on-line parameter calibration.The validation results show that the on-line calibrated model can accurately predict the dynamic voltage behavior of the lithium-ion battery.The maximum and mean relative errors are 1.666% and 0.01%,respectively,in a hybrid pulse test,while 1.933% and 0.062%,respectively,in a transient power test.The on-line parameter calibration method thereby can ensure that the model possesses an acceptable robustness to varied battery loading profiles.
