Vehicle speed decoupling road identification method based on least squares

Aiming at the problem that the road recognition method requires a large number of training sets or high computational power support is not conducive to the realization of ride sensation improvement. In this paper，an improved least squares estimation method is proposed，which does not require a training set and directly collects vehicle responses to identify road excitation and road grade changes. On the basis of the variable parameter model of road grade coefficient and vehicle speed，the sampling processing rules of road excitation data are discussed，and the real-time road roughness coefficient is obtained by decoupling the influence of driving speed. The simulation results show that the comprehensive estimation accuracy of the A-E road grade is above 97%，the response time to the sudden change of road surface grade is less than 0.15 s，and the following performance to the road surface input is good. The dynamic parameters of the real vehicle at different speeds of different road sections are collected for identification. The test results show that the accuracy of the estimated value under this working condition is 98.2%，which is consistent with the actual road surface grade obtained by the three-meter-foot detection method. The feasibility and accuracy of this vehicle speed decoupling road identification method are verified. © 2024 Editorial Board of Jilin University. All rights reserved.