The Ignition Advance Angle Control of CNG Automobile Based on BP Neural Network

Abstract:

Compressed natural gas (CNG) automobile is an emerging new energy car. How to optimally control the ignition advance angle of engine is the key technology of CNG electronic control system. At present, the control based on the MAP graph is used usually, but this control method has some shortages, for example larger data, poor adaptive capacity and difficulties in data updating. BP neural network control has adaptive and self-learning, nonlinear processing ability and high generalization, and faults tolerant ability in processing information. In this paper, BP neural network is used to control natural the ignition advance of engine in order to solve the shortages of the MAP picture control. Simulations experiment shows the feasibility and advantage of this method.

• Periodical: Applied Mechanics and Materials (Volume 391)
• Pages: 453-456
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.391.453
• Online since: September 2013
• Authors: De Hai Chen, Wei Feng Chao
• Keywords: BP Neural Network (BPNN), Compressed Natural Gas (CNG) Automobile, Ignition Advance Angle of Engine, MATLAB Simulation

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