Design of an Integrated Vehicle Chassis Control System with Driver Behavior Identification
作者： Bing Zhu , Yizhou Chen , Jian Zhao , Yunfu Su
DOI: 10.1155/2015/954514
关键词: Artificial neural network 、 Automobile handling 、 DSPACE 、 Model predictive control 、 Engineering 、 Chassis 、 Automotive engineering 、 CarSim 、 Control system 、 Simulation 、 MATLAB
摘要: An integrated vehicle chassis control strategy with driver behavior identification is introduced in this paper. In order to identify the different types of characteristics, a signals acquisition system was established using dSPACE real-time simulation platform, and inputs 30 test drivers were collected under double lane change condition. Then, characteristics analyzed identified based on preview optimal curvature model through genetic algorithm neural network method. Using it as base, an active front steering (AFS) direct yaw moment (DYC) considering by predictive (MPC) Finally, simulations carried out verify CarSim MATLAB/Simulink. The results show that proposed method enables adjust its parameters according handling stability performance are significantly improved.
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