Real-Time Control Strategy of Elman Neural Network for the Parallel Hybrid Electric Vehicle
Joint Authors
Source
Journal of Applied Mathematics
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-08-26
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Through researching the instantaneous control strategy and Elman neural network, the paper established equivalent fuel consumption functions under the charging and discharging conditions of power batteries, deduced the optimal control objective function of instantaneous equivalent consumption, established the instantaneous optimal control model, and designs the Elman neural network controller.
Based on the ADVISOR 2002 platform, the instantaneous optimal control strategy and the Elman neural network control strategy were simulated on a parallel HEV.
The simulation results were analyzed in the end.
The contribution of the paper is that the trained Elman neural network control strategy can reduce the simulation time by 96% and improve the real-time performance of energy control, which also ensures the good performance of power and fuel economy.
American Psychological Association (APA)
Liu, Ruijun& Shi, Dapai& Ma, Chao. 2014. Real-Time Control Strategy of Elman Neural Network for the Parallel Hybrid Electric Vehicle. Journal of Applied Mathematics،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1039746
Modern Language Association (MLA)
Liu, Ruijun…[et al.]. Real-Time Control Strategy of Elman Neural Network for the Parallel Hybrid Electric Vehicle. Journal of Applied Mathematics No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-1039746
American Medical Association (AMA)
Liu, Ruijun& Shi, Dapai& Ma, Chao. Real-Time Control Strategy of Elman Neural Network for the Parallel Hybrid Electric Vehicle. Journal of Applied Mathematics. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1039746
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1039746