LVQ Neural Network Based Driving Cycles Recognition for Hybrid Electric Vehicles

Shi Jing Xu

doi:10.4028/www.scientific.net/AMM.253-255.2113

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 253-255LVQ Neural Network Based Driving Cycles...

LVQ Neural Network Based Driving Cycles Recognition for Hybrid Electric Vehicles

Abstract:

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.

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Periodical:

Applied Mechanics and Materials (Volumes 253-255)

Pages:

2113-2116

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.253-255.2113

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Online since:

December 2012

Authors:

Shi Jing Xu

Keywords:

Driving Cycles Recognition, Hybrid Electric Vehicle (HEV), Learning Vector Quantization

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References

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