Study on Strategy of Automatic Shift Based on ANFIS for Intelligent Pure Electric Vehicle

DOI

10.2991/msota-16.2016.95How to use a DOI?

Keywords

fuzzy system; ANFIS; shifting strategy; intelligent pure electric vehicle; vehicle simulation

Abstract

In intelligent pure electric vehicle, different shift strategies has a great influence in energy consumption, The paper established the ANFIS shifting strategy based on the fuzzy neural network control theory and the traditional two parameters shift rules, training the ANFIS shifting strategy by the Sample data, and then built the vehicle model in the Cruise as a simulation environment, and substituting the parameters of the simulation, obtained the simulation results, then compared with the single fuzzy shift strategy, the results show that ANFIS shift strategy can effectively improve the efficiency of the vehicle, and the energy consumption has been optimized in the energy.

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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TY  - CONF
AU  - Bingli Zhang
AU  - Jiaoyu Xing
AU  - Yunsheng Ye
AU  - Zhihao Bai
PY  - 2016/12
DA  - 2016/12
TI  - Study on Strategy of Automatic Shift Based on ANFIS for Intelligent Pure Electric Vehicle
BT  - Proceedings of 2016 International Conference on Modeling, Simulation and Optimization Technologies and Applications (MSOTA2016)
PB  - Atlantis Press
SP  - 428
EP  - 430
SN  - 2352-538X
UR  - https://doi.org/10.2991/msota-16.2016.95
DO  - 10.2991/msota-16.2016.95
ID  - Zhang2016/12
ER  -