基于扩展卡尔曼滤波算法的港口智能无人内集卡状态估计研究

Research on State Estimation of Port Intelligent Unmanned InternalTruck Based on Extended Kalman Filter Algorithm

为了保证港口智能无人内集卡行驶安全和作业效率,使用Trucksim软件模拟货车的运行条件,同时采用Simulink软件建立魔术轮胎模型并设计扩展卡尔曼滤波算法,对智能无人内集卡的纵向车速、横摆角速度和质心侧偏角进行估计。在典型工况下对比实际输出参数与估计参数,结果验证了算法的准确性与实时性,可为智能无人内集卡行驶状态参数估计研究提供技术指导。

In order to ensure the safety and operational efficiency of the intelligent unmanned inner truck in the port,Trucksim software is used to simulate the operating conditions of the truck.At the same time,Simulink software is used to establish a dugoff tire model and design an extended Kalman filtering algorithm to estimate the longitudinal speed,yaw rate,and center of mass sideslip angle of the intelligent unmanned inner container truck.The actual output parameters and estimated parameters under typical operating conditions have been contrasted and the accuracy and real-time performance of the algorithm have been verified,which can provide technical guidance for the research of intelligent unmanned internal truck driving state parameter estimation.