Neural Network Control of Air-to-Fuel Ratio in a Bi-Fuel Engine  

Oleh:

Gnanam, Gnanaprakash ; Habibi, Saedi R. ; Burton, Richard T. ; Sulatisky, Michael T.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Systems, Man, and Cybernetics: Part C Applications and Reviews vol. 36 no. 5 (Sep. 2006), page 656-667.
Topik: Artificial Neural Networks; Bi-Fuel Engines; Compressed Natural Gas (CNG); Fuel Injection Control

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II69.2 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

Lihat Detail Induk

Isi artikel

In this paper, a neural network-based control system is proposed for fine control of the intake air/fuel ratio in a bi-fuel engine. This control system is an add-on module for an existing vehicle manufacturer's electronic control units (ECUs). Typically the ECU is calibrated for gasoline and provides a good control of the intake air/fuel ratio with gasoline. The neural network-based control system is developed to allow the conversion of a gasoline ECU to a bi-fuel form with compressed natural gas at minimal cost. The effectiveness of the neural control system is demonstrated by using a simulation of a Dodge four-stroke bi-fuel engine.

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