Research on Double Energy Fuzzy Controller of Electric Vehicle Based on Particle Swarm Optimization of Multimedia Big Data
The pure electric vehicles have the problems of short driving range, poor acceleration performance and battery performance, this paper presents a novel double - energy fuzzy control algorithm for battery-supercapacitor based on particle swarm optimization (PSO). The proposed algorithm can avoid falling into local optimum and being over reliance on prior knowledge by using the swarm intelligence global optimization and evolutionary operation. The simulation results show that this method can improve the vehicle performances in the large extent and verify the effectiveness of the control strategy. It is very important for improving the development and research level and promoting industrialization process of pure electric vehicles.
Year of publication: |
2017
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Authors: | Wang, Xiaokan |
Published in: |
International Journal of Mobile Computing and Multimedia Communications (IJMCMC). - IGI Global, ISSN 1937-9404, ZDB-ID 2703549-9. - Vol. 8.2017, 3 (01.07.), p. 32-43
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Publisher: |
IGI Global |
Subject: | Double Energy Source Mode | Multimedia Big Data | Particle Swarm Optimization | Pure Electric Vehicle Fuzzy Control |
Saved in:
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