为改善车网耦合系统在多工况运行下的直流电压抗干扰能力,提出了一种基于滑模观测器的动车组网侧整流器滑模控制策略(sliding mode control method based on sliding mode observer,SMO+SMC)。首先,通过建立CRH3型动车组在dq坐标系下的...为改善车网耦合系统在多工况运行下的直流电压抗干扰能力,提出了一种基于滑模观测器的动车组网侧整流器滑模控制策略(sliding mode control method based on sliding mode observer,SMO+SMC)。首先,通过建立CRH3型动车组在dq坐标系下的数学模型,推导了滑模观测器的设计方程。接着,利用滑模观测器实时观测牵引电机输出功率后间接得到整流器直流侧电流,将滑模观测器的输出提供给滑模控制的外环电压控制模块,实现滑模观测器和滑模控制的结合。最后,将PI、滑模控制和SMO+SMC策略分别应用于CRH3型动车组仿真模型,对多工况下整流侧直流电压控制效果进行分析验证,并基于HIL小步长实时仿真测试平台进行了半实物实验。仿真和实验结果表明,SMO+SMC策略可以提高动车组运行速度改变时的直流电压抗干扰能力和车网耦合运行时网侧电流的稳定性。展开更多
A method used to detect anomaly and estimate the state of vehicle in driving was proposed.The kinematics model of the vehicle was constructed and nonholonomic constraint conditions were added,which refer to that once ...A method used to detect anomaly and estimate the state of vehicle in driving was proposed.The kinematics model of the vehicle was constructed and nonholonomic constraint conditions were added,which refer to that once the vehicle encounters the faults that could not be controlled,the constraint conditions are violated.Estimation equations of the velocity errors of the vehicle were given out to estimate the velocity errors of side and forward.So the stability of the whole vehicle could be judged by the velocity errors of the vehicle.Conclusions were validated through the vehicle experiment.This method is based on GPS/INS integrated navigation system,and can provide foundation for fault detections in unmanned autonomous vehicles.展开更多
文摘为改善车网耦合系统在多工况运行下的直流电压抗干扰能力,提出了一种基于滑模观测器的动车组网侧整流器滑模控制策略(sliding mode control method based on sliding mode observer,SMO+SMC)。首先,通过建立CRH3型动车组在dq坐标系下的数学模型,推导了滑模观测器的设计方程。接着,利用滑模观测器实时观测牵引电机输出功率后间接得到整流器直流侧电流,将滑模观测器的输出提供给滑模控制的外环电压控制模块,实现滑模观测器和滑模控制的结合。最后,将PI、滑模控制和SMO+SMC策略分别应用于CRH3型动车组仿真模型,对多工况下整流侧直流电压控制效果进行分析验证,并基于HIL小步长实时仿真测试平台进行了半实物实验。仿真和实验结果表明,SMO+SMC策略可以提高动车组运行速度改变时的直流电压抗干扰能力和车网耦合运行时网侧电流的稳定性。
基金Projects(90820302,60805027) supported by the National Natural Science Foundation of ChinaProject(200805330005) supported by Research Fund for Doctoral Program of Higher Education of China+1 种基金Projects(2009FJ4030) supported by Academician Foundation of Hunan Province,ChinaProject supported by the Freedom Explore Program of Central South University,China
文摘A method used to detect anomaly and estimate the state of vehicle in driving was proposed.The kinematics model of the vehicle was constructed and nonholonomic constraint conditions were added,which refer to that once the vehicle encounters the faults that could not be controlled,the constraint conditions are violated.Estimation equations of the velocity errors of the vehicle were given out to estimate the velocity errors of side and forward.So the stability of the whole vehicle could be judged by the velocity errors of the vehicle.Conclusions were validated through the vehicle experiment.This method is based on GPS/INS integrated navigation system,and can provide foundation for fault detections in unmanned autonomous vehicles.
