电动轮汽车车速与道路坡度估计*

doi:10.19562/j.chinasae.qcgc.2020.02.009

汽车工程 ›› 2020, Vol. 42 ›› Issue (2): 199-205.doi: 10.19562/j.chinasae.qcgc.2020.02.009

电动轮汽车车速与道路坡度估计^*

陈浩¹, 袁良信¹, 孙涛², 郑四发^1,3, 连小珉¹

1.清华大学汽车工程系,北京 100084;
2.苏州紫荆清远新能源汽车技术有限公司,苏州 215200;
3.清华大学苏州汽车研究院,苏州 215200

收稿日期:2018-11-16 出版日期:2020-02-25 发布日期:2020-02-25
通讯作者: 连小珉,教授,E-mail:lianxm@tsinghua.edu.cn
基金资助:
*苏州清华创新引领行动专项(2016SZ0303)资助

Estimation of In-wheel Motor Driven Electric Vehicle Speed and Road Gradient

Chen Hao¹, Yuan Liangxin¹, Sun Tao², Zheng Sifa^1,3, Lian Xiaomin¹

1.Department of Automotive Engineering, Tsinghua University, Beijing 100084;
2.Suzhou TS-Sky-Blue Electric Vehicle Co., Ltd., Suzhou 215200;
3.Suzhou Automobile Research Institute, Tsinghua University, Suzhou 215200

Received:2018-11-16 Online:2020-02-25 Published:2020-02-25

摘要/Abstract

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。

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

Abstract: 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

Key words: in-wheel motor electric vehicle, speed and gradient estimation, extended state observer, recursive least squares method, information fusion

陈浩, 袁良信, 孙涛, 郑四发, 连小珉. 电动轮汽车车速与道路坡度估计^*[J]. 汽车工程, 2020, 42(2): 199-205.

Chen Hao, Yuan Liangxin, Sun Tao, Zheng Sifa, Lian Xiaomin. Estimation of In-wheel Motor Driven Electric Vehicle Speed and Road Gradient[J]. Automotive Engineering, 2020, 42(2): 199-205.

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电动轮汽车车速与道路坡度估计^*

Estimation of In-wheel Motor Driven Electric Vehicle Speed and Road Gradient

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