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.

LVQ Neural Network Based Driving Cycles Recognition for Hybrid Electric Vehicles

2012 ◽  
Vol 253-255 ◽  
pp. 2113-2116
Author(s):  
Shi Jing Xu
Keyword(s):  
Neural Network ◽  
Management Strategy ◽  
Hybrid Electric Vehicle ◽  
Hybrid Electric Vehicles ◽  
Driving Cycle ◽  
Characteristic Parameters ◽  
Energy Management Strategy ◽  
Driving Cycles ◽  
Recognition Result ◽  
Hybrid Electric

In order to establish a real-time hybrid electric vehicle energy management strategy, a LVQ neural network based driving cycles recognizer is established. Selecting 6 typical driving cycles, and the characteristic parameters of the typical driving cycles are extracted and is used to train the LVＱ neural network by LVQ2 algorithm. The trained LVＱ neural network is employed to recognize the other driving cycle. The result shows that the recognition result reflects the character of the real driving cycle very well.

scholarly journals Online Energy Management of Plug-In Hybrid Electric Vehicles for Prolongation of All-Electric Range Based on Dynamic Programming

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Zeyu Chen ◽  
Weiguo Liu ◽  
Ying Yang ◽  
Weiqiang Chen
Keyword(s):  
Dynamic Programming ◽  
Energy Saving ◽  
Energy Management ◽  
Electric Vehicles ◽  
Management Strategy ◽  
Hybrid Electric Vehicles ◽  
Driving Cycle ◽  
Energy Management Strategy ◽  
Driving Range ◽  
Hybrid Electric

The employed energy management strategy plays an important role in energy saving performance and exhausted emission reduction of plug-in hybrid electric vehicles (HEVs). An application of dynamic programming for optimization of power allocation is implemented in this paper with certain driving cycle and a limited driving range. Considering the DP algorithm can barely be used in real-time control because of its huge computational task and the dependence ona prioridriving cycle, several online useful control rules are established based on the offline optimization results of DP. With the above efforts, an online energy management strategy is proposed finally. The presented energy management strategy concerns the prolongation of all-electric driving range as well as the energy saving performance. A simulation study is deployed to evaluate the control performance of the proposed energy management approach. All-electric range of the plug-in HEV can be prolonged by up to 2.86% for a certain driving condition. The energy saving performance is relative to the driving distance. The presented energy management strategy brings a little higher energy cost when driving distance is short, but for a long driving distance, it can reduce the energy consumption by up to 5.77% compared to the traditional CD-CS strategy.

Energy Management Strategy for Ultracapacitors in Hybrid Electric Vehicles

2020 ◽  
Author(s):  
Carlos Villarreal-Hernandez ◽  
Javier Loranca-Coutino ◽  
Omar F. Ruiz-Martinez ◽  
Jonathan C. Mayo-Maldonado ◽  
Jesus E. Valdez-Resendiz ◽  
...  
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Management Strategy ◽  
Hybrid Electric Vehicles ◽  
Energy Management Strategy ◽  
Hybrid Electric
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