中国机械工程2024，Vol.35Issue(6)：973-981,992,10.DOI:10.3969/j.issn.1004-132X.2024.06.003
基于鲸鱼优化算法-支持向量回归的汽车运动状态估计
Vehicle Motion State Estimation Based on WOA-SVR
摘要
Abstract
In order to accurately obtain vehicle motion state information without relying on the ac-curacy of the dynamics model,a vehicle state estimation algorithm was proposed based on WOA-SVR.Firstly,by analyzing the basic characteristics of vehicle dynamics,a SVR architecture was de-signed for estimating the separation of lateral velocity,yaw rate,and vehicle speed.Then,the SVR model was trained on a dataset composed of multiple driving conditions,and the WO A was used to optimize the penalty factor c and kernel function parameter g in the relaxation variables during the training processes.Finally,the estimation algorithm was validated through virtual simulation of single line shift and frequency sweep tests,as well as ABS braking and double line shift actual vehicle tests.The results show that this algorithm effectively improves estimation accuracy and is robust to changes in speed,enabling accurate estimation of vehicle motion states without relying on dynamics models.关键词
车辆状态估计/动力学模型/机器学习/支持向量回归/鲸鱼优化算法Key words
vehicle state estimation/dynamics model/machine learning/support vector regres-sion(SVR)/whale optimization algorithm(WOA)分类
交通工程引用本文复制引用
尤勇,孟云龙,吴景涛,王长青..基于鲸鱼优化算法-支持向量回归的汽车运动状态估计[J].中国机械工程,2024,35(6):973-981,992,10.基金项目
天津市教委科研项目(2023KJ298) （2023KJ298）
国家自然科学基金(52205052) （52205052）
