An invalid idling start-stop prediction method based on BP neural network

XueJun Li; JiYu Wang; YanLi Yang; Ting Zhao

doi:10.1117/12.2671738

28 April 2023 An invalid idling start-stop prediction method based on BP neural network

XueJun Li, JiYu Wang, YanLi Yang, Ting Zhao

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 126104Y (2023) https://doi.org/10.1117/12.2671738
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

Idling start-stop is a fuel prudent and emission reductive technology at motor vehicle idling condition. Irrespective of the fuel consumption associated with useless idling condition and the characteristics of actual road conditions, the idling start-stop system not only cannot be fuel-prudence or emission -reduction, but also aggravate the starter abrasion. The method based on BP Neural Network is proposed to predict idling condition in this paper for avoiding useless idle situations. A predictor based on BP Neural Network which has 4 signal-input channels and 1 signal-output channel, is used to predict the speed and idling stop temporal information which is useful in the idling start-stop control policy. The simulation experiment results show that the method based on BP Neural Network can effectively avoid useless idle situations, sequentially reduce fuel consumption and harmful gases discharge and improve comfort.

Citation Download Citation

XueJun Li, JiYu Wang, YanLi Yang, and Ting Zhao "An invalid idling start-stop prediction method based on BP neural network", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 126104Y (28 April 2023); https://doi.org/10.1117/12.2671738

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KEYWORDS

Neural networks

Mathematical optimization

Neurons

MATLAB

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