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Investigation of Urban Ramp Driving Cycle Based on Principal Component Analysis and Neural Network Clustering
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Yuzhen Song1, Zhimin Wu1, Xiaofeng Yin1, Yulong Lei2, Yiming Liang1
Automobile Technology | 2025, (5) : 47 - 54
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Automobile Technology | 2025, (5): 47-54
Investigation of Urban Ramp Driving Cycle Based on Principal Component Analysis and Neural Network Clustering
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Yuzhen Song1, Zhimin Wu1, Xiaofeng Yin1, Yulong Lei2, Yiming Liang1
Affiliations
  • 1 Stitute of Automotive Engineering, Xihua University, Chengdu 610039
  • 2 National Key Laboratory of Automobile Chassis Integration and Bionics, Jilin University, Changchun 130021
Published: 2025-05-24 doi: 10.19620/j.cnki.1000-3703.20240906
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Aiming at the issue of lacking slope information in urban driving cycles used for vehicle performance evaluation, this paper proposes a method for Urban Ramp Driving Cycle (URDC) construction based on Self-Organizing Map (SOM) neural network. Typical road driving data with urban ramp characteristics is collected using the average traffic flow method. After pre-processing, the data is segmented into short trips, and 20 parameters representing road operation characteristics are selected as the feature parameters of the short trips. The dimensionality of these feature parameters is then reduced via principal component analysis, followed by clustering the short trips analysis using a SOM neural network. According to the principle of smooth ramp connection, short trips with high correlation are selected to construct an urban ramp driving cycle that includes both speed and slope information. The results of automatic transmission operated in slope performance test indicate that the constructed driving cycle can reflect the driving characteristics of vehicles on road with urban ramp features, which can be used as the benchmark driving cycle for performance test of vehicle driving on urban ramps.

Ramp driving cycle  /  Principal component analysis  /  SOM neural network  /  Cluster analysis  /  Performance test
Yuzhen Song, Zhimin Wu, Xiaofeng Yin, Yulong Lei, Yiming Liang. Investigation of Urban Ramp Driving Cycle Based on Principal Component Analysis and Neural Network Clustering[J]. Automobile Technology, 2025 , (5) : 47 -54 . DOI: 10.19620/j.cnki.1000-3703.20240906
Year 2025 volume Issue 5
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doi: 10.19620/j.cnki.1000-3703.20240906
  • Online Date:2025-11-14
  • Published:2025-05-24
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  • Revised:2025-03-06
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    1 Stitute of Automotive Engineering, Xihua University, Chengdu 610039
    2 National Key Laboratory of Automobile Chassis Integration and Bionics, Jilin University, Changchun 130021
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表12种不同金属材料的力学参数

Family
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Number of
genus
种数
Number of
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占总种数比例
Percentage of
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种数
Number of
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Percentage of total
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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