基于轮胎内嵌传感器阵列的智能轮胎磨损检测方法

doi:10.19562/j.chinasae.qcgc.2025.06.019

Abstract

Abstract:

In order to fully utilize the advantages of embedded integrated sensor arrays in smart tires for collecting multi-modal information of the tire-ground contact state， and to enhance the accuracy of tire wear detection， a smart tire wear detection method based on the embedded sensor array is proposed in this paper. Firstly， a sensor array composed of accelerometers and PVDF piezoelectric film sensors is constructed， and an embedded data acquisition system for the smart tire is designed to collect sensor array data from tires with various degrees of wear under different operating conditions. Next， the waveform data from the sensor array is processed using Butterworth filtering， and multidimensional time-domain features are extracted. The variations in the time-domain characteristics of the sensor array data are analyzed under changing vehicle operating conditions， revealing significant differences in the time-domain feature variations （length features and area features） of the accelerometer and PVDF piezoelectric film sensors with the change of vehicle speed and vertical load. Finally， a joint feature set that integrates the time-domain feature information from both types of sensors is established， and a machine learning model for tire wear detection is constructed. The test results show that the average absolute error of tire wear detection based on the sensor array is 0.13 mm， a reduction of 67.67% and 56.81%， respectively， compared to using only the accelerometer or only the PVDF piezoelectric film sensor. The detection accuracy of tire wear within a 0.3 mm error reaches 88.81%， while the accuracy within a 0.5 mm error reaches 96.42， which proves the effectiveness and accuracy of the machine learning model for tire wear detection based on the sensor array.

Key words: intelligent tire, sensor array, wear detection, machine learning

Lisheng Jin,Xin Zhao,Xianyi Xie,Hao Yang,Bo Lu,Mingliang Song,Baicang Guo,Yaoguang Cao. Intelligent Tire Wear Detection Method Based on an Embedded Sensor Array Within the Tire[J].Automotive Engineering, 2025, 47(6): 1207-1218.

Figures/Tables 37

类型	符号	表达
长度特征	H_Z₁	$L C y - m e a n f$
长度特征	H_Z₂	$R C y - m e a n f$
长度特征	S_Z	$R C x - L C x$
长度特征	H_Z	$m a x m e a n f - f$
面积特征	A_Z₁	$∫ L C x L I f n - m e a n f n d n$
面积特征	A_Z₂	$∫ R I R C x f n - m e a n f n d n$
面积特征	A_Z	$∫ L I R I m e a n f n - f n d n$

References 29

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工况	范围
轮胎花纹磨损程度/mm	0/1/2/3/4/5
车速/（km·h^-1）	20/40/60
载荷/kN	4/5/6
胎压/bar	2.3/2.5/2.7

速度/（km·h^-1）	20	40	60
H_Z₁	2.880	14.809	38.164
H_Z₂	3.422	18.269	45.108
S_Z	318	167	113
H_Z	9.630	47.748	112.356
A_Z₁	97.993	311.674	580.975
A_Z₂	597.458	1 585.483	2 480.233
A_Z	1 145.998	2 958.727	4 745.111

载荷/kN	4	5	6
H_Z₁	3.648	4.094	4.235
H_Z₂	4.080	4.512	4.635
S_Z	318	334	356
H_Z	10.520	11.534	11.714
A_Z₁	130.364	151.305	160.366
A_Z₂	618.168	756.688	906.023
A_Z	1 206.742	1 436.353	1 627.966

胎压/bar	2.3	2.5	2.7
H_Z₁	2.357	2.214	2.125
H_Z₂	3.180	3.009	2.898
S_Z	314	313	307
H_Z	8.845	8.718	8.453
A_Z₁	77.299	71.050	66.200
A_Z₂	518.592	496.864	467.449
A_Z	1 020.595	997.187	948.706

工况	车速	载荷	胎压
H_Z₁	↑↑↑↑	↑↑	↓
H_Z₂	↑↑↑↑	↑↑	↓
S_Z	↓↓↓	↑↑	↓
H_Z	↑↑↑↑	↑↑	↓
A_Z₁	↑↑↑↑	↑↑	↓↓
A_Z₂	↑↑↑↑	↑↑	↓
A_Z	↑↑↑↑	↑↑	↓

Intelligent Tire Wear Detection Method Based on an Embedded Sensor Array Within the Tire

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Figures/Tables 37

References 29

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速度/（km·h^-1）	20	40	60
H_Z₁	441.551	459.966	482.228
H_Z₂	558.606	583.954	620.658
S_Z	362	184	123
H_Z	1 355.772	1 418.732	1 396.541
A_Z₁	24 759.970	13 340.559	9 359.872
A_Z₂	88 592.821	47 701.338	31 174.607
A_Z	170 935.799	92 236.902	61 026.540

载荷/kN	4	5	6
H_Z₁	621.462	709.260	785.909
H_Z₂	847.733	971.042	1 060.970
S_Z	377	386	403
H_Z	2 066.289	2 239.152	2 357.636
A_Z₁	39 783.561	42 054.107	45 546.640
A_Z₂	137 345.932	163 150.427	190 423.241
A_Z	264 434.755	309 844.789	360 638.633

胎压/bar	2.3	2.5	2.7
H_Z₁	499.839	474.681	449.944
H_Z₂	650.484	631.369	598.343
S_Z	362	361	357
H_Z	1 558.841	1 520.906	1 475.908
A_Z₁	29 376.038	28 401.918	27 327.799
A_Z₂	99 316.974	95 794.804	89 684.084
A_Z	192 478.747	184 705.444	175 152.252

学习率	数据集	MAE/mm
0.01	测试集	0.413
0.01	训练集	0.363
0.005	测试集	0.402
0.005	训练集	0.348
0.001	测试集	0.438
0.001	训练集	0.404

学习率	数据集	MAE/mm
0.01	测试集	0.352
0.01	训练集	0.267
0.005	测试集	0.301
0.005	训练集	0.212
0.001	测试集	0.382
0.001	训练集	0.297

学习率	数据集	MAE/mm
0.01	测试集	0.172
0.01	训练集	0.143
0.005	测试集	0.130
0.005	训练集	0.098
0.001	测试集	0.181
0.001	训练集	0.134

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