高能动力电池是供配电系统的核心储能模块,针对高能动力电池的应用构建了二阶等效电路模型。在等效电路模型的基础上,提出联合递推最小二乘(Recursive Least Squares,RLS)法和扩展卡尔曼滤波(Extended Kalman Filter,EKF)的荷电状态(Sta...高能动力电池是供配电系统的核心储能模块,针对高能动力电池的应用构建了二阶等效电路模型。在等效电路模型的基础上,提出联合递推最小二乘(Recursive Least Squares,RLS)法和扩展卡尔曼滤波(Extended Kalman Filter,EKF)的荷电状态(Stage of Charge,SOC)算法,并在其基础上改进为基于温度补偿的联合RLS法和EKF融合的SOC算法。基于MATLAB软件,设计改进前和改进后联合算法的仿真验证程序,并对结果进行了比较分析。仿真结果表明,基于温度补偿的联合算法可实现当SOC处于(0.25,1)的区域内,相对误差基本小于5%,验证了所提出的建模方法和求解方法的有效性。展开更多
锂电池荷电状态(state of charge,SOC)的准确估计依赖于精确的锂电池模型参数。在采用带遗忘因子的递推最小二乘法(forgetting factor recursive least square,FFRLS)对锂电池等效电路模型进行参数辨识时,迭代初始值选取不当会造成辨识...锂电池荷电状态(state of charge,SOC)的准确估计依赖于精确的锂电池模型参数。在采用带遗忘因子的递推最小二乘法(forgetting factor recursive least square,FFRLS)对锂电池等效电路模型进行参数辨识时,迭代初始值选取不当会造成辨识精度低、收敛速度慢的问题。为此,将电路分析法与FFRLS相结合,提出基于改进初值带遗忘因子的递推最小二乘法(improved initial value-FFRLS,IIV-FFRLS)。首先,通过离线辨识得到各荷电状态点对应的等效电路模型参数并进行多项式拟合;然后,利用初始开路电压(open circuit voltage,OCV)和OCV-SOC曲线获得初始SOC,代入参数拟合函数得到初始参数;最后,将初始参数带入递推公式得到IIV-FFRLS迭代初始值。对4种锂电池工况进行参数辨识,结果表明:与传统方法相比,IIV-FFRLS的平均相对误差、收敛时间分别减小58%、23%以上;IIV-FFRLS具有更高的辨识精度与更快的收敛速度。展开更多
永磁同步电机(permanent magnet synchronous motor,PMSM)的磁链准确辨识是实现高性能电机控制的基础。针对传统递推最小二乘(recursive least squares,RLS)法受噪声影响小但存在数据饱和,影响辨识精度和动态性问题,以及遗忘最小二乘(re...永磁同步电机(permanent magnet synchronous motor,PMSM)的磁链准确辨识是实现高性能电机控制的基础。针对传统递推最小二乘(recursive least squares,RLS)法受噪声影响小但存在数据饱和,影响辨识精度和动态性问题,以及遗忘最小二乘(recursive least squares with forgetting factor,FRLS)法避免数据饱和但存在参数估计误差与动态跟踪性能矛盾的问题,文章提出一种基于折息最小二乘(recursive least squares with discount factor,DRLS)法的磁链辨识方法。该算法在FRLS法中引入加权因子构成折息因子,采用递推方法进行磁链辨识,减小参数估计误差,提高磁链辨识精度及动态跟踪能力。通过MATLAB仿真及半实物仿真试验,验证所提磁链识别方法的有效性。展开更多
The combination of structural health monitoring and vibration control is of great importance to provide components of smart structures.While synthetic algorithms have been proposed,adaptive control that is compatible ...The combination of structural health monitoring and vibration control is of great importance to provide components of smart structures.While synthetic algorithms have been proposed,adaptive control that is compatible with changing conditions still needs to be used,and time-varying systems are required to be simultaneously estimated with the application of adaptive control.In this research,the identification of structural time-varying dynamic characteristics and optimized simple adaptive control are integrated.First,reduced variations of physical parameters are estimated online using the multiple forgetting factor recursive least squares(MFRLS)method.Then,the energy from the structural vibration is simultaneously specified to optimize the control force with the identified parameters to be operational.Optimization is also performed based on the probability density function of the energy under the seismic excitation at any time.Finally,the optimal control force is obtained by the simple adaptive control(SAC)algorithm and energy coefficient.A numerical example and benchmark structure are employed to investigate the efficiency of the proposed approach.The simulation results revealed the effectiveness of the integrated online identification and optimal adaptive control in systems.展开更多
为了有效改善燃料电池混合动力系统的能耗,减少燃料电池性能衰减,保持辅助动力源的荷电状态(state of charge,SOC),提出一种基于遗忘因子递推最小二乘算法(forgetting factor recursive least square,FFRLS)的在线辨识方法和极小值原理...为了有效改善燃料电池混合动力系统的能耗,减少燃料电池性能衰减,保持辅助动力源的荷电状态(state of charge,SOC),提出一种基于遗忘因子递推最小二乘算法(forgetting factor recursive least square,FFRLS)的在线辨识方法和极小值原理的综合能量管理方法。该方法能根据在线辨识的结果和直流母线需求功率,完成对主动力源及辅助动力源的功率分配工作,并与基于离线辨识的算法结果以及等效氢耗最小能量管理方法(equivalent consumption minimization strategy,ECMS)进行对比分析。结果表明,该方法对等效氢耗的优化比离线以及ECMS的效果分别提升了6.33%和4.35%,对燃料电池性能衰减则分别优化了4.72%和6.98%,并能更好地维持辅助动力源的SOC。展开更多
文摘高能动力电池是供配电系统的核心储能模块,针对高能动力电池的应用构建了二阶等效电路模型。在等效电路模型的基础上,提出联合递推最小二乘(Recursive Least Squares,RLS)法和扩展卡尔曼滤波(Extended Kalman Filter,EKF)的荷电状态(Stage of Charge,SOC)算法,并在其基础上改进为基于温度补偿的联合RLS法和EKF融合的SOC算法。基于MATLAB软件,设计改进前和改进后联合算法的仿真验证程序,并对结果进行了比较分析。仿真结果表明,基于温度补偿的联合算法可实现当SOC处于(0.25,1)的区域内,相对误差基本小于5%,验证了所提出的建模方法和求解方法的有效性。
文摘永磁同步电机(permanent magnet synchronous motor,PMSM)的磁链准确辨识是实现高性能电机控制的基础。针对传统递推最小二乘(recursive least squares,RLS)法受噪声影响小但存在数据饱和,影响辨识精度和动态性问题,以及遗忘最小二乘(recursive least squares with forgetting factor,FRLS)法避免数据饱和但存在参数估计误差与动态跟踪性能矛盾的问题,文章提出一种基于折息最小二乘(recursive least squares with discount factor,DRLS)法的磁链辨识方法。该算法在FRLS法中引入加权因子构成折息因子,采用递推方法进行磁链辨识,减小参数估计误差,提高磁链辨识精度及动态跟踪能力。通过MATLAB仿真及半实物仿真试验,验证所提磁链识别方法的有效性。
文摘The combination of structural health monitoring and vibration control is of great importance to provide components of smart structures.While synthetic algorithms have been proposed,adaptive control that is compatible with changing conditions still needs to be used,and time-varying systems are required to be simultaneously estimated with the application of adaptive control.In this research,the identification of structural time-varying dynamic characteristics and optimized simple adaptive control are integrated.First,reduced variations of physical parameters are estimated online using the multiple forgetting factor recursive least squares(MFRLS)method.Then,the energy from the structural vibration is simultaneously specified to optimize the control force with the identified parameters to be operational.Optimization is also performed based on the probability density function of the energy under the seismic excitation at any time.Finally,the optimal control force is obtained by the simple adaptive control(SAC)algorithm and energy coefficient.A numerical example and benchmark structure are employed to investigate the efficiency of the proposed approach.The simulation results revealed the effectiveness of the integrated online identification and optimal adaptive control in systems.
文摘为了有效改善燃料电池混合动力系统的能耗,减少燃料电池性能衰减,保持辅助动力源的荷电状态(state of charge,SOC),提出一种基于遗忘因子递推最小二乘算法(forgetting factor recursive least square,FFRLS)的在线辨识方法和极小值原理的综合能量管理方法。该方法能根据在线辨识的结果和直流母线需求功率,完成对主动力源及辅助动力源的功率分配工作,并与基于离线辨识的算法结果以及等效氢耗最小能量管理方法(equivalent consumption minimization strategy,ECMS)进行对比分析。结果表明,该方法对等效氢耗的优化比离线以及ECMS的效果分别提升了6.33%和4.35%,对燃料电池性能衰减则分别优化了4.72%和6.98%,并能更好地维持辅助动力源的SOC。
