Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology

The Driving Control Strategy of Pure Electric Vehicle Based on Fuzzy Self-adaptive PID

Authors
Shi-wei Xu, Jing Lu, Xuan Zhao
Corresponding Author
Shi-wei Xu
Available Online March 2016.
DOI
10.2991/icmmct-16.2016.187How to use a DOI?
Keywords
Automotive engineering, drive control, fuzzy self-adaptive PID, double closed loop control.
Abstract

For the problem of pure electric vehicle drive control, a speed-current double closed loop control strategywasproposed by using the fuzzy self-adaptive PID theory, and thevehicle simulation model was established in Matlab/Simscape.The performance of the drive control strategy was verified bystarting operation condition and NEDC cycle in the simulation model. Simulation results show that the pure electric vehicle drive control strategy based on the fuzzy adaptive PID can execute the driving instructionsquickly and accurately, and the vehiclecan operate stably without static speed error, so the control strategy can improve the vehicle driving performanceeffectively.

Copyright
© 2016, 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/).

Download article (PDF)

Volume Title
Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
Series
Advances in Engineering Research
Publication Date
March 2016
ISBN
10.2991/icmmct-16.2016.187
ISSN
2352-5401
DOI
10.2991/icmmct-16.2016.187How to use a DOI?
Copyright
© 2016, 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  - Shi-wei Xu
AU  - Jing Lu
AU  - Xuan Zhao
PY  - 2016/03
DA  - 2016/03
TI  - The Driving Control Strategy of Pure Electric Vehicle Based on Fuzzy Self-adaptive PID
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
PB  - Atlantis Press
SP  - 940
EP  - 946
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-16.2016.187
DO  - 10.2991/icmmct-16.2016.187
ID  - Xu2016/03
ER  -