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Simulation and Analysis of Sintering Furnace Temperature Based on Fuzzy Neural Network Control

Chaoxin Zou, Rong Li, Zhiping Xie, Ming Su, Jingshi Zeng, Xu Ji, Xiaoli Ye, Ye Wang

Archives of Foundry Engineering

2021

Vol. 21, iss. 1

23--30

Aiming at the problems of delay and couple in the sintering temperature control system of lithium batteries, a fuzzy neural network controller that can solve complex nonlinear temperature control is designed in this paper. The influence of heating voltage, air inlet speed and air inlet volume on the control of temperature of lithium battery sintering is analyzed, and a fuzzy control system by using MATLAB toolbox is established. And on this basis, a fuzzy neural network controller is designed, and then a PID control system and a fuzzy neural network control system are established through SIMULINK. The simulation shows that the response time of the fuzzy neural network control system compared with the PID control system is shortened by 24s, the system stability adjustment time is shortened by 160s, and the maximum overshoot is reduced by 6.1%. The research results show that the fuzzy neural network control system can not only realize the adjustment of lithium battery sintering temperature control faster, but also has strong adaptability, fault tolerance and anti-interference ability.