The invention discloses a vehicle parameter estimation method based on a BP neural network and an improved unscented Kalman filter. The method comprises the following steps: determining a state equation and an observation equation of the unscented Kalman filter according to an established three-degree-of-freedom vehicle dynamics model; determining an input quantity, a state quantity and an observed quantity of the unscented Kalman filter; improving the unscented Kalman filter to obtain a state quantity estimation result of the improved unscented Kalman filter; the front wheel turning angle and the longitudinal acceleration of the vehicle serve as training input, and a residual value of a state quantity estimation result and a sensor true value is obtained through BP neural network training fitting; and taking the state quantity estimation result and the residual value as actual output of the vehicle parameter prediction model. According to the method, the improved unscented particle filter is adopted to predict and estimate the vehicle kinetic parameters, the BP neural network fitting residual error is established by using the vehicle state parameters, and the defect that a current high-precision vehicle parameter sensor cannot be loaded on a vehicle is overcome.
本发明公开了一种基于BP神经网络和改进的无迹卡尔曼滤波器的车辆参数估计方法,包括:根据建立的三自由度车辆动力学模型确定无迹卡尔曼滤波器的状态方程和观测方程;确定无迹卡尔曼滤波器的输入量、状态量以及观测量;对无迹卡尔曼滤波器进行改进,得到改进后的无迹卡尔曼滤波器的状态量估计结果;将车辆的前轮转角、车辆纵向加速度作为训练输入,经过BP神经网络训练拟合得到状态量估计结果与传感器真实值的残差值;将状态量估计结果和残差值作为车辆参数预测模型的实际输出。本发明采用改进无迹粒子滤波器对车辆动力学参数进行预测估计,利用车辆状态参数搭建BP神经网络拟合残差,弥补了目前高精度车辆参数传感器无法装车的缺陷。
Vehicle parameter estimation method based on BP neural network and improved unscented Kalman filter
一种基于BP神经网络和改进的无迹卡尔曼滤波器的车辆参数估计方法
2024-10-18
Patent
Electronic Resource
Chinese
IPC: | G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen |
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