复合材料板簧迟滞特性线性辨识方法

Abstract

Abstract:

Aiming at the identification of hysteresis characteristic parameter of composite leaf springs， a linear algorithm was proposed based on the stochastic gradient decent method and the recursive formular was deduced. From the two dimensions of identification accuracy and calculation time， the linear identification method and the improved firefly algorithm in the existing work are compared and verified. On this basis， a momentum term is introduced to improve the linear identification method. The results show that the improved algorithm accelerates the convergence time and reduces the convergence error. Finally， the improved algorithm was applicated to identify the hysteresis characteristics of a certain composite leaf spring and good results were obtained. The results show that the linear algorithm， which can get results in 2.5 ms， is more suitable for hysteresis characteristic parameter identification of composite leaf springs than nonlinear algorithm and can be used in online parameter identification and digital twin simulation.

Key words: vehicle engineering, composite material, leaf springs, parameter identification, linear algorithm, online parameter identification

CLC Number:

U467.3

Wei LI,Hai-sheng SONG,Hao-yu LU,Wen-ku SHI,Qiang WANG,Xiao-jun WANG. Linear identification method of hysteresis characteristic of composite leaf springs[J].Journal of Jilin University(Engineering and Technology Edition), 2022, 52(4): 829-836.

Figures/Tables 15

Fig.1

Table 1

Comparison of results between linear method and MFA method"

方法	对比结果		计算时间/s
方法	$w 1$ /（N·mm^-1）	RMSE^［17］ /%	计算时间/s
MFA^［17］	125.554	0.709	22.4014
本文方法	128.744	0.851	0.003
比较标准	131.052	0	-

Table 1

Fig.2

Fig.3

Table 2

Comparison of influence of momentum term on algorithm"

方法	对比结果		计算时间/s
方法	$w 1$ /（N·mm^-1）	RMSE^［17］ /%	计算时间/s
无动量	128.744	0.851	0.003
有动量	131.199	0.762	0.0024
比较标准	131.052	0	-

Table 2

Fig.4

Fig.5

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