【摘要】 针对汽车状态估计中过程噪声和量测噪声统计特性不确定的状况,通过UKF算法与遗传算法相结合,提出一种新的自适应滤波算法,以降低噪声对估计结果的干扰。为达到较高的精度,建立了7自由度非线性车辆动力学模型,结合"魔术公式"轮胎模型对汽车行驶过程中的纵、侧向速度、轮胎力和质心侧偏角分别进行了估计。在利用UKF对汽车状态参数进行估计的同时,引入遗传算法,根据适应度函数对过程噪声和量测噪声进行寻优,实现了噪声的自适应作用,估计精度大幅提高。仿真和道路模拟试验的结果表明,UKF结合遗传算法的方法,能提高估计精度且具有很好的抗干扰性。更多还原

【Abstract】 In view of the uncertain situation of the statistical characteristics of process noise and measurement noise in vehicle state estimation, a new adaptive filtering algorithm is put forward by combining UKF algorithm with genetic one for reducing the disturbance of noise to the results of estimation. In order to achieve higher accuracy, a 7 DOF nonlinear vehicle dynamics model is established and by combining ‘magic formula’ tire model, the longitudinal and lateral velocities, tire force and the sideslip angle of mass center are estimated respectively. While UKF algorithm is applied to estimate vehicle states, the genetic algorithm is introduced, and the process noise and measurement noise are optimized based on fitness function to realize the adaptation of noise with the accuracy of estimation greatly enhanced. The results of simulation and road test show that the combination of UKF and genetic algorithms can improve the accuracy of vehicle state estimation with good disturbance resistance.更多还原