A new approach in improvement of mean value models for spark ignition engines using neural networks

作者：

Highlights：

• We present a highly accurate, real-time control-oriented model for SI engines.

• Incorporating neural nets into mean value models, we achieve a grey-box extension.

• Neuro-MVM is much more accurate than MVM, and is also more reliable than a mere NN.

• The model precisely predicts transient conditions, in a wide range of reliability.

• This study reaches high levels of accuracy in designing neural networks.

摘要

•We present a highly accurate, real-time control-oriented model for SI engines.•Incorporating neural nets into mean value models, we achieve a grey-box extension.•Neuro-MVM is much more accurate than MVM, and is also more reliable than a mere NN.•The model precisely predicts transient conditions, in a wide range of reliability.•This study reaches high levels of accuracy in designing neural networks.

论文关键词：Spark ignition engines,Control oriented modeling,Mean value models,Artificial neural networks

论文评审过程：Available online 27 February 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.02.031