Abstract
The tire-road friction coefficient is an important input parameter of the vehicle active control system,the estimation accuracy of which directly affects the performance of the vehicle dynamics system control. The estimation method should meet the requirements of timeliness,reliability and high accuracy. Firstly,a 3DOF model and tire model of the vehicle are established. Secondly,a method of expansion state observer is used to estimate and identify the utilization of tire-road friction coefficient,and an adaptive Kalman filtering method is used to estimate and identify the slip rate. Finally,a segmented method for estimating the tire-road friction coefficient is proposed, which can effectively identify the tire-road friction coefficient. By introducing in the evaluation indicators in the estimation process,the computational complexity of the method is reduced and the efficiency is improved. The simulation and experimental results show that the estimation error of the tire-road friction coefficient is within 0.05,after introducing in the evaluation indicators,the operating efficiency of the algorithm is increased by 21.1%,which can meet the requirements of the control system.
| Translated title of the contribution | Segmented Identification Method of Tire-Road Friction Coefficient for Intelligent Vehicles |
|---|---|
| Original language | Chinese (Traditional) |
| Pages (from-to) | 1923-1932 |
| Number of pages | 10 |
| Journal | Qiche Gongcheng/Automotive Engineering |
| Volume | 45 |
| Issue number | 10 |
| DOIs | |
| Publication status | Published - 25 Oct 2023 |
| Externally published | Yes |