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Research on Vehicle Planning Driving Cycle Construction Method Based on Markov Chain
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Wei Wang1, Fufan Qu1, Fang Yang2, Wenbo Li1
Automobile Technology | 2023, (4) : 1 - 7
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Automobile Technology | 2023, (4): 1-7
Research on Vehicle Planning Driving Cycle Construction Method Based on Markov Chain
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Wei Wang1, Fufan Qu1, Fang Yang2, Wenbo Li1
Affiliations
  • 1 CATARC Automotive Test Center (Tianjin) Co., Ltd., Tianjin 300300
  • 2 Global R&D Center, China FAW Corporation Limited, Changchun 130013
Published: 2023-04-24 doi: 10.19620/j.cnki.1000-3703.20220277
Outline
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In order to accurately reflect the driving motion characteristics of vehicles on the real road, this paper proposes a vehicle driving cycle construction method based on Markov fusion online map information. In this paper, the actual collected vehicle driving data were cleaned and segmented that were clustered and analyzed by Principal Component Analysis (PCA) method and K-Means clustering method, and a typical working condition fragment library based on Markov was established. The road information of the planned path on the online map was integrated in the fragment database, and the road driving condition of the vehicle was constructed. An electric vehicle was taken as the research object for simulation and analysis, the results show that the energy consumption of online map planning driving condition based on Markov fragment library is closer to the actual road condition than that of online map basic planning condition. The error of characteristic parameters is only 4.29%, and the error of energy consumption is only 4.09%.

Working condition construction  /  Cluster analysis  /  Markov Chain  /  Online map
Wei Wang, Fufan Qu, Fang Yang, Wenbo Li. Research on Vehicle Planning Driving Cycle Construction Method Based on Markov Chain[J]. Automobile Technology, 2023 , (4) : 1 -7 . DOI: 10.19620/j.cnki.1000-3703.20220277
Year 2023 volume Issue 4
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doi: 10.19620/j.cnki.1000-3703.20220277
  • Online Date:2025-12-07
  • Published:2023-04-24
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  • Revised:2022-07-06
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    1 CATARC Automotive Test Center (Tianjin) Co., Ltd., Tianjin 300300
    2 Global R&D Center, China FAW Corporation Limited, Changchun 130013
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表12种不同金属材料的力学参数

Family
属数
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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