Welcome to Journal of Kunming Metallurgy College! Today is Share:

Journal of Kunming Metallurgy College ›› 2021, Vol. 37 ›› Issue (1): 55-58.DOI: 10.3969/j.issn.1009-0479.2021.01.010

Previous Articles     Next Articles

Research on Prediction of SOC State of Accumulator of Hydraulic Hybrid Vehicle Based on Neural Network#br#

ZHOU Peng,WU Xiangji2   

  1. 1.Faculty of Electrical and Mechanical Engineering,Kunming Metallurgy College Kunming 650033,China;
    2.Faculty of Transportation Engineering,Kunming University of Science and Technology,Kunming 650500,China
  • Received:2020-09-04 Online:2021-04-29 Published:2021-08-23

Abstract: The hydraulic accumulator ( SOC) load model of hydraulic hybrid vehicles based on neural network control is established. By selecting a certain heavy-duty hydraulic hybrid vehicle , the simulation model under Matlab / Simulink platform is built. In the FUDS simulation cycle ,the actual vehicle speed and expected speed, vchicle speed error parameters,the SOC predict state parameters,etc. are analyzed. lt is concluded that when the opening value of hydraulic accumulator ACC is 0.2 and the closing value is 0. 5 ,the coordination between engine and accumulator is the best. 'The response of SOC valuc is good,and the expected effect is achieved.

Key words: hydraulic hybrid power, FUDS, neural network control hydraulic accumulator, state of charge, speed error

CLC Number: