To solve the problem of data fusion for prior information such as track information and train status in train positioning,an adaptive H∞filtering algorithm with combination constraint is proposed,which fuses prior in...To solve the problem of data fusion for prior information such as track information and train status in train positioning,an adaptive H∞filtering algorithm with combination constraint is proposed,which fuses prior information with other sensor information in the form of constraints.Firstly,the train precise track constraint method of the train is proposed,and the plane position constraint and train motion state constraints are analysed.A model for combining prior information with constraints is established.Then an adaptive H∞filter with combination constraints is derived based on the adaptive adjustment method of the robustness factor.Finally,the positioning effect of the proposed algorithm is simulated and analysed under the conditions of a straight track and a curved track.The results show that the positioning accuracy of the algorithm with constrained filtering is significantly better than that of the algorithm without constrained filtering and that the algorithm with constrained filtering can achieve better performance when combined with track and condition information,which can significantly reduce the train positioning error.The effectiveness of the proposed algorithm is verified.展开更多
荷电状态(State of charge,SOC)估计是电池管理系统的核心功能之一,它在电动汽车的生命周期中起着重要作用.针对锂离子电池温度影响模型参数,进而导致SOC估计不准确的问题,本文提出了基于鲁棒H_(∞)滤波的SOC估计方法.首先,以二阶Theve...荷电状态(State of charge,SOC)估计是电池管理系统的核心功能之一,它在电动汽车的生命周期中起着重要作用.针对锂离子电池温度影响模型参数,进而导致SOC估计不准确的问题,本文提出了基于鲁棒H_(∞)滤波的SOC估计方法.首先,以二阶Thevenin等效电路模型做为锂离子电池基础模型,并将温度对电池模型参数的影响建模为标称电阻值和电池总容量的加性变量,视温度变化为系统的外部扰动.其次,采用滑动线性法对电池模型进行线性化,并在此基础上运用线性矩阵不等式技术设计了对SOC进行估计的鲁棒H_(∞)滤波器.最后,分别采用四种不同类型的动态电流激励进行仿真实验验证,并将SOC的估计结果与kalman滤波对SOC的估计结果进行对比.结果表明所设计的鲁棒H_(∞)滤波器能够实现对SOC更为准确的跟踪,同时对外部扰动具有较好的鲁棒性.展开更多
基金the National Natural Science Fund of China(61471080)Training Plan for Young Backbone Teachers in Colleges and Universities of Henan Province(2018GGJS171).
文摘To solve the problem of data fusion for prior information such as track information and train status in train positioning,an adaptive H∞filtering algorithm with combination constraint is proposed,which fuses prior information with other sensor information in the form of constraints.Firstly,the train precise track constraint method of the train is proposed,and the plane position constraint and train motion state constraints are analysed.A model for combining prior information with constraints is established.Then an adaptive H∞filter with combination constraints is derived based on the adaptive adjustment method of the robustness factor.Finally,the positioning effect of the proposed algorithm is simulated and analysed under the conditions of a straight track and a curved track.The results show that the positioning accuracy of the algorithm with constrained filtering is significantly better than that of the algorithm without constrained filtering and that the algorithm with constrained filtering can achieve better performance when combined with track and condition information,which can significantly reduce the train positioning error.The effectiveness of the proposed algorithm is verified.
文摘荷电状态(State of charge,SOC)估计是电池管理系统的核心功能之一,它在电动汽车的生命周期中起着重要作用.针对锂离子电池温度影响模型参数,进而导致SOC估计不准确的问题,本文提出了基于鲁棒H_(∞)滤波的SOC估计方法.首先,以二阶Thevenin等效电路模型做为锂离子电池基础模型,并将温度对电池模型参数的影响建模为标称电阻值和电池总容量的加性变量,视温度变化为系统的外部扰动.其次,采用滑动线性法对电池模型进行线性化,并在此基础上运用线性矩阵不等式技术设计了对SOC进行估计的鲁棒H_(∞)滤波器.最后,分别采用四种不同类型的动态电流激励进行仿真实验验证,并将SOC的估计结果与kalman滤波对SOC的估计结果进行对比.结果表明所设计的鲁棒H_(∞)滤波器能够实现对SOC更为准确的跟踪,同时对外部扰动具有较好的鲁棒性.
