Proceedings of the 2017 7th International Conference on Applied Science, Engineering and Technology (ICASET 2017)

Analysis and Modeling of New Energy Automobile's Data Acquisition and Processing System

Authors
Yanning Wang, Xia Yu
Corresponding Author
Yanning Wang
Available Online May 2017.
DOI
10.2991/icaset-17.2017.26How to use a DOI?
Keywords
New energy automobile, Data acquisition and processing system, Modeling
Abstract

The data acquisition and processing system of new energy automobile is to design a complete experimental system that can realize the automation of the experiment; which can collect the effective data efficiently, accurately. Tt can also help the automotive engineers to learn the related performance of the automobile. Through the analysis of the business needs of the system, on the basis of it to combine with practice, the system function can be designed, making it module, through designing each module, they can be integrated, and finally realize the data acquisition and processing system.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 7th International Conference on Applied Science, Engineering and Technology (ICASET 2017)
Series
Advances in Engineering Research
Publication Date
May 2017
ISBN
10.2991/icaset-17.2017.26
ISSN
2352-5401
DOI
10.2991/icaset-17.2017.26How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yanning Wang
AU  - Xia Yu
PY  - 2017/05
DA  - 2017/05
TI  - Analysis and Modeling of New Energy Automobile's Data Acquisition and Processing System
BT  - Proceedings of the 2017 7th International Conference on Applied Science, Engineering and Technology (ICASET 2017)
PB  - Atlantis Press
SP  - 138
EP  - 142
SN  - 2352-5401
UR  - https://doi.org/10.2991/icaset-17.2017.26
DO  - 10.2991/icaset-17.2017.26
ID  - Wang2017/05
ER  -