吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (5): 1405-1413.doi: 10.13229/j.cnki.jdxbgxb201605004

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Self-adaptive composite ABS of dual-motor four-wheel drive electric vehicle

SUN Da-xu1,2, LAN Feng-chong1,3, HE Xing-fu1,3, CHEN Ji-qing1,3   

  1. 1.School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510640,China;
    2.Guangdong Mechanical & Electrical Polytechnic, Guangzhou 510515,China;
    3.Guangdong Key Laboratory of Vehicle Engineering, South China University of Technology, Guangzhou 510640, China
  • Received:2014-06-17 Online:2016-09-20 Published:2016-09-20

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Abstract: On the basis of electro-hydraulic varying parameters PID control, to further improve the response rate and accuracy of anti-lock breaking system of a dual-motor four-wheel drive electric vehicle, the neural network system based on radial basis function is introduced to realize online identification of electro-hydraulic braking system. The sensitivity of the wheel slip ratio to motor braking torque is used to achieve scroll optimal adjustment of parameters of PID control, and to increase the response rate and accuracy. The off-line simulation and hardware in loop real time simulation are carried out to test the control algorithm. Results show that the improve control algorithm can increase the accuracy and regulating rate of the system, and meet the real time requirements of the control system.

Key words: vehicle engineering, radial basis function, neural network, anti-lock braking system(ABS), electric vehicle

CLC Number: 

  • U461.3
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