Yiming Ye

Dr. Yiming Ye

orcid

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 April 2020 in Transportation Research Part D: Transport and Environment
Verified
Journal Article
Closed access
XZXuan Zhao
Xuan Zhao
XZXiangmo Zhao
Xiangmo Zhao
QYQiang Yu
Qiang Yu
YYYiming Ye
Yiming Ye
MYMan Yu
Man Yu

11 May 2020 in Environmental Science and Pollution Research
Verified
Journal Article
Closed access
PDF file
XZXuan Zhao
Xuan Zhao
YYYiming Ye
Yiming Ye
JMJian Ma
Jian Ma
PSPeilong Shi
Peilong Shi
HCHao Chen
Hao Chen

7 November 2018 in Environmental Science and Pollution Research
Verified
Journal Article
Closed access
PDF file
Xuan ZhaoXuan Zhao
Xuan Zhao
JMJian Ma
Jian Ma
SWShu Wang
Shu Wang
YYYiming Ye
Yiming Ye
YWYan Wu
Yan Wu
MYMan Yu
Man Yu

10 October 2024 in Energy
Verified
Journal Article
Closed access
YYYiming Ye
Yiming Ye
BXBin Xu
Bin Xu
HWHanchen Wang
Hanchen Wang
JZJiangfeng Zhang
Jiangfeng Zhang
Benjamin LawlerBenjamin Lawler
Benjamin Lawler
BABeshah Ayalew
Beshah Ayalew

5 November 2018 in Journal of Advanced Transportation
Verified
Journal Article
Open access
PDF file
Xuan ZhaoXuan Zhao
Xuan Zhao
QYQiang Yu
Qiang Yu
JMJian Ma
Jian Ma
YWYan Wu
Yan Wu
MYMan Yu
Man Yu
YYYiming Ye
Yiming Ye
This paper proposes a scientific and systematic methodology for the development of a representative electric vehicle (EV) urban driving cycle. The methodology mainly includes three tasks: test route selection and data collection, data processing, and driving cycle construction. A test route is designed according to the overall topological structure of the urban roads and traffic flow survey results. The driving pattern data are collected using a hybrid method of on-board measurement method and chase car method. Principal component analysis (PCA) is used to reduce the dimensionality of the characteristic parameters. The driving segments are classified using a hybrid k-means and support vector machine (SVM) clustering algorithm. Scientific assessment criteria are studied to select the most representative driving cycle from multiple candidate driving cycles. Finally, the characteristic parameters of the Xi’an EV urban driving cycle, international standard driving cycles, and other city driving cycles are compared and analyzed. The results indicate that the Xi’an EV urban driving cycle reflects more aggressive driving characteristics than the other cycles.

16 February 2018 in Cluster Computing
Verified
Journal Article
Closed access
PDF file
Xuan ZhaoXuan Zhao
Xuan Zhao
SXShiwei Xu
Shiwei Xu
YYYiming Ye
Yiming Ye
MYMan Yu
Man Yu
GWGuiping Wang
Guiping Wang