Citation

Wu G, Lyu Z, Wang C. SAE Int. J. Veh. Dyn. Stab. NVH 2022; 7(1): 10-07-01-0001.

Copyright

(Copyright © 2022, Society of Automotive Engineers)

DOI

10.4271/10-07-01-0001

PMID

unavailable

Abstract

In order to improve the safety of vehicles driving in mountainous areas and other curve roads, a DCT shift strategy for different drivers is designed in this article. First, the test road is digitized and an electronic map model is built based on particle filtering (PF) to achieve the optimal prediction of road conditions. Then, a driver's intention recognition model is constructed based on principle component analysis (PCA) and Kohonen neural network (KohonenNN) to accommodate different driving intentions, and the appropriate downshift schedules are designed for different driver's intentions. In addition, we propose the concept of the curve safety factor, and the current safety level is determined by vehicle speed and distance. By combining the earlier discussed concepts, the predictive curve shift strategy is presented. To determine the appropriate downshift schedule and make full use of the auxiliary engine brake to improve the vehicle's braking efficiency, the strategy utilizes the driver's intention as well as the vehicle's current safety level. The simulation and real vehicle test results show that the predictive curve shift strategy can effectively reduce the braking distance and time compared with the traditional one.

Language: en