Paper Info
Title
Human-Centered Torque Vectoring Control for Distributed Drive Electric Vehicle Considering Driving Characteristics
Abstract
Most of the existing torque vectoring control (TVC) strategies are “vehicle-centered,” hence, fail to consider how driving characteristics affect the vehicle's motion. To address this issue, we propose a hierarchically structured human-<;bold/>centered TVC (HCTVC) for distributed drive electric vehicles (EVs). To do this we design the experiment to characterize the drivers' behavior with different skills. Then a global objective function is formulated considering the driver's physical and mental workload, as well as the agility and stability of the vehicle, to optimize the overall performance of the driver-vehicle system. Next, an adaptive second-order sliding mode controller (ASOSM) based on the backstepping method is designed as the upper-level controller to improve system robustness. Finally, a multi-objective optimization algorithm based on the weight self-tuning strategy is developed as the lower-level controller to solve the torque distribution problem. We further obtain the analytical solution to this optimization problem. Experimental results on the asphalt and icy roads confirm that the proposed HCTVC significantly enhances the vehicle transient response and reduces the driver's workload.
Year
DOI
Venue
2021
10.1109/TVT.2021.3087476
IEEE Transactions on Vehicular Technology
Keywords
DocType
Volume
Human-centered torque vectoring control,driving characteristics,driver workload,distributed drive electric vehicles,real-world experiment
Journal
70
Issue
ISSN
Citations 
8
0018-9545
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Lin Zhang110451.47
Hong Chen228056.04
Yanjun Huang37910.54
Ping Wang400.34
Konghui Guo500.34