摘要
针对电动轮汽车车速与道路坡度估计问题,本文中基于纵向非线性动力学方程设计1阶扩张状态观测器对车速与坡度进行联合估计,分析了估计稳态误差;同时,采用带遗忘因子的递归最小二乘估计算法分离加速度传感器信号中的坡度信息,并设置了比例系数来融合两类坡度信息,最终得到道路坡度估计值。搭建MATLAB/Simulink-Carsim联合仿真平台进行变坡度路面仿真,并在实际坡道路面完成实车测试。仿真与试验结果表明,所提出的方法简单、可行。
Aiming at the estimation of vehicle speed and road gradient,a first-order extended state observer based on longitudinal non-linear dynamic equation is designed to jointly estimate the vehicle speed and road gradient with the steady-state error of estimation analyzed.Meanwhile,the recursive least squares estimation algorithm with forgetting factor is used to separate the gradient information from acceleration sensor signals,and the proportional coefficients are set to fuse two-types of gradient information and finally obtain the estimation value of road gradient.The MATLAB/Simulink-Carsim co-simulation platform is built to conduct a simulation on variable gradient road,and a real vehicle test is also carried out on a slope.The results of simulation and real vehicle test show that the proposed method is simple and feasible.
作者
陈浩
袁良信
孙涛
郑四发
连小珉
Chen Hao;Yuan Liangxin;Sun Tao;Zheng Sifa;&Lian Xiaomin(Department of Automotive Engineering,Tsinghua University,Beijing 100084;Suzhou TS-Sky-Blue Electric Vehicle Co.,Ltd.,Suzhou 215200;Suzhou Automobile Research Institute,Tsinghua University,Suzhou 215200)
出处
《汽车工程》
EI
CSCD
北大核心
2020年第2期199-205,256,共8页
Automotive Engineering
基金
苏州-清华创新引领行动专项(2016SZ0303)资助
关键词
电动轮汽车
车速与坡度估计
扩张状态观测器
递归最小二乘法
信息融合
in-wheel motor electric vehicle
speed and gradient estimation
extended state observer
recursive least squares method
information fusion
