Journal of Jilin University(Engineering and Technology Edition) ›› 2023, Vol. 53 ›› Issue (5): 1257-1263.doi: 10.13229/j.cnki.jdxbgxb.20210886

   

A vehicle agility control strategy based on steering intent

Lei CHEN1(),Yang WANG2(),Zhi-sheng DONG2,Ya-qi SONG1,2   

  1. 1.State Key Laboratory of Integrated Technology of Automotive Vibration and Noise and Safety Control,Changchun 130011,China
    2.KH Automotive Technologies (Huzhou) Co. ,Ltd. ,Huzhou 313002,China
  • Received:2021-09-08 Online:2023-05-01 Published:2023-05-25
  • Contact: Yang WANG E-mail:chenlei2@faw.com.cn;wangyang@khat.com.cn

Abstract:

In order to improve the agility and safety of emergency steering, a steering intention-based agility control strategy based on active lateral stabilizer bar system was proposed. The rolling dynamics mechanism of wheel load transfer during steering is analyzed and an improved driver steering intention recognition method is developed. According to the steering intention and the vehicle roll dynamics mechanism, the left and right wheel loads on the front and rear axles were dynamically distributed, and the stability control method was introduced to improve the agility control strategy during vehicle driving. Simulink-CarSim vehicle model was built for simulation and verification. The simulation results show that compared with traditional vehicles, the use of steering wheel angle decreases by about 9%, the peak angle of centroid side angle decreases by about 22%, and the yaw angle speed increases by 4%. Emergency steering control is achieved by using smaller steering wheel angle to improve the yaw steering response, and the agility and stability of the vehicle are enhanced. Finally, the simulation algorithm is verified on the ECU in-the-loop test bench and laid the foundation for the subsequent development of stabilizer rod prototypes.

Key words: vehicle engineering, agility control, driver intention identification, simulation verification

CLC Number: 

  • U461.6

Fig.1

Analysis of cornering operations by professional drivers"

Fig.2

Driver intent recognition based on lateral acceleration"

Fig.3

Control methods during a single turn"

Fig.4

Fuzzy algorithm membership function diagram"

Table 1

Control rule table for the parameter"

NBNMNSZOPSPMPB
NBPBPBPMPMPSZOZO
NMPBPBPMPSZOZONS
NSPMPMPMPSZONSNS
ZOPMPMPSZONSNSNM
PSPSPSZONSNSNMNM
PMPSZONSNMNMNMNB
PBZOZONMNMNMNBNB

Table 2

Control rule table for the parameter"

NBNMNSZOPSPMPB
NBNBNBNMNMNSZOZO
NMNBNBNMNSZOZOPS
NSNMNMNMNSZOPSPS
ZONMNMNSZOPSPSPM
PSNSNSZOPSPSPMPM
PMNSZOPSPMPMPMPB
PBZOZOPMPMPMPBPB

Table 3

Control rule table for the parameter"

NBNMNSZOPSPMPB
NBPMPMPSPSZOZOZO
NMPMPMPSPSZONONS
NSPMPSPSZOZONSNS
ZOPMPSZOZONSNSNS
PSPSPSZOZONSNSNM
PMPSZOZONSNSNSNM
PBPSZONSNSNSNMNM

Table 4

Vehicle basic parameter table"

参 数数 值
整车质量/kg2825
簧上质量/kg2515
簧下质量/kg310
轴距/mm3110
前、后轴距/mm1702/1684
轮胎型号275/65 R18

Fig.5

Co-simulation comparison results"

Fig.6

Controller code is written to the model"

Fig.7

Results of the in-the-loop test and simulation"

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