基于卷积神经网络的汽车操纵稳定性试验类型识别方法

doi:10.19562/j.chinasae.qcgc.2023.09.024

Abstract

Abstract:

To meet the need of automatic identification of test types， which is aimed at automatic processing of vehicle handling and stability test evaluation indicators， this paper proposes a vehicle handling and stability test type recognition method based on convolutional neural network. On the basis of analyzing the image characteristics of the test type data， a vehicle handling and stability test type recognition model based on convolution neural network is established， which consists of 1 input layer， 3 convolution layers， 3 batch normalization layers， 2 Max-pooling layers， 5 linear rectification function （ReLU） layers， 3 full connection layers， 2 Dropout layers， 1 Softmax layer and 1 classification layer. The model is trained and verified using 2 250 groups of data collected from the tests. The accuracy of type recognition is 99.33%， and the average recognition time is 0.05 s. The results show that the vehicle handling and stability test type recognition method based on convolutional neural network proposed in this paper can effectively distinguish different test types， which can be used for automatic processing of vehicle handling and stability test results， and can significantly improve the automatic processing level of vehicle handling and stability test.

Key words: automobile test, type recognition, convolution neural network, vehicle handling and stability

Xin Guan,Zhaohui Zhong,Jun Zhan,Tenglong Xi,Hao Ye,Shenzhen Gao,Jian Cheng,Shihui Liao,Jun Cai. Vehicle Handling and Stability Test Type Recognition Method Based on Convolutional Neural Network[J].Automotive Engineering, 2023, 45(9): 1765-1771.

Figures/Tables 7

References 20

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编号	试验类型	编号	试验类型
1	中心区-斜坡试验	9	角脉冲试验（右）
2	中心区-穿行试验	10	角脉冲试验（左）
3	单正弦试验（右）	11	蛇行试验
4	单正弦试验（左）	12	转向释放开环试验（右）
5	双移线试验	13	转向释放开环试验（左）
6	扫频试验	14	角阶跃试验（右）
7	稳态圆周-定半径（右）	15	角阶跃试验（左）
8	稳态圆周-定半径（左）

编号	试验类型	编号	试验类型
1	中心区-斜坡试验	9	角脉冲试验（右）
2	中心区-穿行试验	10	角脉冲试验（左）
3	单正弦试验（右）	11	蛇行试验
4	单正弦试验（左）	12	转向释放开环试验（右）
5	双移线试验	13	转向释放开环试验（左）
6	扫频试验	14	角阶跃试验（右）
7	稳态圆周-定半径（右）	15	角阶跃试验（左）
8	稳态圆周-定半径（左）

名称	参数
处理器	Intel Core（TM）i9-9900K CPU（3.6 GHz）
GPU	NVIDIA GeForce RTX 2080 Ti
操作系统	Windows 10
内存	32.00 GB
MATLAB	2022a

识别方法	识别准确率/%	平均识别时间/s
文献［14］	98.461 5	0.302 4
文献［16］	93.33
本文	99.33	0.05

Vehicle Handling and Stability Test Type Recognition Method Based on Convolutional Neural Network

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References 20

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