A Study on the Driving Style Recognition of Hybrid Electric Vehicle

被引：0
|
作者：
Hao J. [1 ,2 ]
Yu Z. [1 ]
Zhao Z. [1 ]
Zhan X. [1 ]
Shen P. [1 ]
机构：
[1] Clean Energy Automotive Engineering Center, Tongji University, Shanghai
[2] SAIC MAXUS Co., Ltd., Shanghai
来源：
Zhao, Zhiguo (zhiguozhao@tongji.edu.cn) | 1600年 / SAE-China卷 / 39期
关键词：
Driving style recognition; K-means clustering; Principal component analysis; Support vector machine;
D O I：
10.19562/j.chinasae.qcgc.2017.12.014
中图分类号：
学科分类号：
摘要：
In view of the significant effects of driver's driving style on fuel economy and emission performance of hybrid electric vehicles, this paper aims to enhance the adaptability of vehicle control strategy to driver's driving style through the classification and identification of drivers' driving styles for improving the fuel economy of vehicle. Firstly, with a hybrid electric vehicle as object, a real vehicle test with data acquisition is conducted by different drivers with different driving styles. Then principal component analysis is adopted to extract the comprehensive characteristic parameters of driving styles, and K-means clustering is applied to the cluster analysis of driving styles. Finally, on these bases, support vector machine algorithm is used to identify driving styles. The results show that the recognition accuracy of driving styles reaches more than 90%, laying a solid foundation for the subsequent adaptive optimization of energy management strategy for hybrid electric vehicles. © 2017, Society of Automotive Engineers of China. All right reserved.
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页码：1444 / 1450
页数：6
相关论文
共 10 条
  • [1] Elander J., West R., French D., Behavioral correlates of individual differences in road-traffic crash risk: an examination method and findings, Psychological Bulletin, 113, 2, pp. 279-294, (1993)
  • [2] Son J., Park M., Won K., Et al., Comparative study between Korea and UK: relationship between driving style and real-world fuel consumption, International Journal of Automotive Technology, 17, 1, pp. 175-181, (2016)
  • [3] Fonseca G.N., Casanova K.J., Espinosa Z.F., Influence of driving style on fuel consumption and emissions in diesel-powered passenger car, Proceedings 18thInternational Symposium Transport and Air Pollution, (2010)
  • [4] Zorrofi S., Filizadeh S., Zanetel P., A simulation study of the impact of driving patterns and driver behavior on fuel economy of hybrid transit buses, Vehicle Power and Propulsion Conference, 2009, pp. 572-577, (2009)
  • [5] Malikopoulos A., Aguilar P., Optimization of driving styles for fuel economy improvement, International IEEE Conference on Intelligent Transportation Systems, pp. 194-199, (2012)
  • [6] Wang R., Lukic M., Review of driving conditions prediction and driving style recognition based control algorithms for hybrid electric vehicles, Vehicle Power and Propulsion Conference, pp. 1-7, (2011)
  • [7] Augustynowicz A., Preliminary classification of driving style with objective rank method, International Journal of Automotive Technology, 10, 5, pp. 607-610, (2009)
  • [8] Murphey L., Milton R., Kiliaris L., Driver's style classification using jerk analysis, Computational Intelligence in Vehicles and Vehicular Systems, 2009. CIVVS '09, pp. 23-28, (2009)
  • [9] Karginova N., Byttner S., Svensson M., Data-driven methods for classification of driving styles in buses, SAE World Congress, (2012)
  • [10] Javier M., Carlos C., Juan C., Et al., Characterizing the driving style behavior using artificial intelligence techniques, (2011)
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