Study on Estimation of Gasoline Engine Oil Film Dynamic Parameter Based on Chaos-RS-RBF#br# Algorithm

Abstract

Abstract: In view of the highly complex nonlinear characteristics of the gasoline engine dynamics system, the Chaos-RS-RBF

algorithm is proposed to identify the dynamic parameters of the oil film. On the basis of judging the chaos characteristics of the engine

dynamics system, the inherently complex nonlinear characteristics are restored through the phase space reconstruction technology to

obtain a multi-dimensional state space time series, and a large number of redundancies are removed using rough sets（RS）. Finally, the

RBF algorithm is used to identify the multi-dimensional state space time series to obtain the oil film dynamic parameter identification

value. The simulation results show that compared with the least square method and RBF neural network, the Chaos-RS-RBF model has

higher accuracy and has a good reference for practical engineering applications.

Key words: gasoline engine, phase space reconstruction, chaos, RS, RBF, predict

CLC Number:

Xu Donghui, Xu Xiangyang, Xu Xinren. Study on Estimation of Gasoline Engine Oil Film Dynamic Parameter Based on Chaos-RS-RBF#br# Algorithm[J]. Journal of Dali University.

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