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

被引:0
|
作者
Chen H. [1 ]
Yuan L. [1 ]
Sun T. [2 ]
Zheng S. [1 ,3 ]
Lian X. [1 ]
机构
[1] Department of Automotive Engineering, Tsinghua University, Beijing
[2] Suzhou TS-Sky-Blue Electric Vehicle Co., Ltd., Suzhou
[3] Suzhou Automobile Research Institute, Tsinghua University, Suzhou
来源
关键词
Extended state observer; In-wheel motor electric vehicle; Information fusion; Recursive least squares method; Speed and gradient estimation;
D O I
10.19562/j.chinasae.qcgc.2020.02.009
中图分类号
学科分类号
摘要
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. © 2020, Society of Automotive Engineers of China. All right reserved.
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页码:199 / 205and256
相关论文
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