A Virtual Residual Gas Sensor to Enable Modeling of the Air Charge BMW AG

Format:

Conference/Event

Author/Creator:

Raidt, Raidt, author.

Conference Name:

SAE 2016 World Congress and Exhibition (2016-04-12 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2016

Summary:

AbstractAir charge calibration of turbocharged SI gasoline engines with both variable inlet valve lift and variable inlet and exhaust valve opening angle has to be very accurate and needs a high number of measurements. In particular, the modeling of the transition area from unthrottled, inlet valve controlled resp. throttled mode to turbocharged mode, suffers from small number of measurements (e.g. when applying Design of Experiments (DoE)). This is due to the strong impact of residual gas respectively scavenging dominating locally in this area. In this article, a virtual residual gas sensor in order to enable black-box-modeling of the air charge is presented. The sensor is a multilayer perceptron artificial neural network. Amongst others, the physically calculated air mass is used as training data for the artificial neural network. The air mass calculation is performed by taking into account valve timing, effective valve cross-sectional area and low-pressure indication at intake and exhaust manifold. It can be shown that by applying the virtual sensor, a global black-box-model of the air charge can be built. Furthermore, the sensor enables to reduce the required number of measurements by DoE and at the same time to maintain good modeling results. The global air charge model can be used to derive virtual measurements for the air charge calibration

Notes:

Vendor supplied data

Publisher Number:

2016-01-0626

Access Restriction:

Restricted for use by site license