This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Construction and Simulation Analysis of Driving Cycle of Urban Electric Logistic Vehicles
Technical Paper
2020-01-1042
ISSN: 0148-7191, e-ISSN: 2688-3627
This content contains downloadable datasets
Annotation ability available
Sector:
Language:
English
Abstract
In order to reflect the actual power consumption of logistics electric vehicles in a city, sample real vehicle road data. After preprocessing, the short-stroke analysis method is used to divide it into working blocks of no less than 20 seconds. Based on principal component analysis, three of the 12 characteristic parameters were selected as the most expressive. K-means clustering algorithm is adopted to obtain the proportions of various short strokes, according to the proportion, select the short stroke with small deviation degree to combine, and construct the driving cycle, it has the characteristics of low average speed, high idle speed ratio and short driving distance. AVL-cruise software builds the vehicle model and runs the driving cycle of urban logistic EV. Compared with WLTC, the difference in power consumption is 34.3%, which is closer to the actual power consumption, the areas with the highest motor speed utilization are concentrated only in the idle area. Therefore, the driving cycle is consistent with the actual use conditions of low average speed and high idle speed of urban logistics vehicles, which can provide theoretical basis for power matching, economic analysis and control strategy optimization of urban logistic EV, so as to achieve the purpose of saving energy and enhancing endurance.
Authors
Topic
Citation
Qian, C., Wang, L., Zou, X., and Yuan, L., "Construction and Simulation Analysis of Driving Cycle of Urban Electric Logistic Vehicles," SAE Technical Paper 2020-01-1042, 2020, https://doi.org/10.4271/2020-01-1042.Data Sets - Support Documents
Title | Description | Download |
---|---|---|
Unnamed Dataset 1 | ||
Unnamed Dataset 2 | ||
Unnamed Dataset 3 | ||
Unnamed Dataset 4 | ||
Unnamed Dataset 5 | ||
Unnamed Dataset 6 |
Also In
References
- Zhu , J. , Shi , Q. , and Zhou , J. The City Bus Driving Cycle Construction Technology & Economy in Areas of Communications 2687 2690 2011
- Chen , Q. et al. Advanced Electric Vehicle Technology Beijing Chemical Industry Press 2013
- Qiang , S. , Shuzhan , B. , and Erliang , H. Construction of Instantaneous Driving Conditions Based on Test Measurement Journal of Jilin University: Engineering Edition 364 370 2015
- Youwen , L. , Qin , S. , and Ping , J. Data Processing and Analysis in the Construction of Driving Conditions Based on Markov Process Journal of Hefei University of Technology (Natural Science Edition) 491 494 2010
- Yao-hua , L. , Qi-zhi , G. , Yan-yuan , R. et al. A Study on the Construction of Modal Driving Conditions of Urban Bus Lines -- A Case Study of Xi 'An Bus Lines Traffic Information and Safety 36 3 2018
- Yuhui , P. , Huibao , Y. , Mengliang , L. et al. Study on Construction Method of Urban Road Vehicle Driving Conditions Based on K-Means Clustering Analysis Automotive Technology 17 22 2017
- Peng , L. 2017
- Jolliffe , I.T. Principal Component Analysis Journal of Marketing Research 513 2002
- Huang , X. and Su , W. 2016
- Guofei , L. , Yi , L. , Hongwen , H. et al. Regenerative Braking Control Strategy for Electric Vehicle Transactions of Beijing Institute of Technology 520 524 2009