Fuzzy energy management strategy for tram with supercapacitors

2015 ◽  
Author(s):  
Jakub Talla ◽  
Lubos Streit ◽  
Zdenek Peroutka ◽  
Pavel Drabek ◽  
Vojtech Blahnik
Keyword(s):  
Energy Management ◽  
Management Strategy ◽  
Energy Management Strategy ◽  
Fuzzy Energy

scholarly journals A Neural Network Fuzzy Energy Management Strategy for Hybrid Electric Vehicles Based on Driving Cycle Recognition

2020 ◽  
Vol 10 (2) ◽  
pp. 696
Author(s):  
Qi Zhang ◽  
Xiaoling Fu
Keyword(s):  
Neural Network ◽  
Energy Management ◽  
Membership Function ◽  
Electric Vehicles ◽  
Management Strategy ◽  
Hybrid Electric Vehicles ◽  
Driving Cycle ◽  
Energy Management Strategy ◽  
Driving Cycles ◽  
Fuzzy Energy

Aiming at the problems inherent in the traditional fuzzy energy management strategy (F-EMS), such as poor adaptive ability and lack of self-learning, a neural network fuzzy energy management strategy (NNF-EMS) for hybrid electric vehicles (HEVs) based on driving cycle recognition (DCR) is designed. The DCR was realized by the method of neural network sample learning and characteristic parameter analysis, and the recognition results were considered as the reference input of the fuzzy controller with further optimization of the membership function, resulting in improvement in the poor pertinence of F-EMS driving cycles. The research results show that the proposed NNF-EMS can realize the adaptive optimization of fuzzy membership function and fuzzy rules under different driving cycles. Therefore, the proposed NNF-EMS has strong robustness and practicability under different driving cycles.

Sign in / Sign up

Export Citation Format

Share Document