Paper Info
Title
Design and Experimental Verification of Real-Time Nonlinear Predictive Controller for Improving the Stability of Production Vehicles
Abstract
Vehicle stability control under extreme conditions is influenced by the coupled nonlinear characteristics of vehicle dynamics, corresponding safety constraints, and rapid response requirements. To address these problems, this brief proposes a real-time nonlinear predictive controller for a distributed drive electric vehicle. First, nonlinear lateral dynamics of the vehicle are applied to develop the stability controller on low friction coefficient surfaces. Second, the requirement for suppressing the sideslip angle is integrated into the objective function to prevent the vehicle from destabilizing due to excessive sideslip angles. Finally, a fast solution algorithm is proposed by solving the transformed two-point boundary value problem, making it possible to apply nonlinear predictive controller to experimental road tests. The experiments with a production vehicle are conducted on the snow-covered dynamic roads of the DongFeng's winter test center. The test results on low friction coefficient roads show that the overall passing speed can be improved from 50-55 to 60-70 km/h with the proposed controller.
Year
DOI
Venue
2021
10.1109/TCST.2020.3015832
IEEE Transactions on Control Systems Technology
Keywords
DocType
Volume
Experimental verification,low friction coefficient,nonlinear model of predictive control (NMPC),Pontryagin’s minimum principle (PMP),vehicle stability control
Journal
29
Issue
ISSN
Citations 
5
1063-6536
0
PageRank 
References 
Authors
0.34
2
6
Name
Order
Citations
PageRank
Ping Wang121.73
Hanghang Liu200.68
Lulu Guo3257.45
Lin Zhang410451.47
haitao ding5184.45
Hong Chen628056.04