Abstract
Recently, model-based control applicable for diesel engines is attracting attention as an engine control methodology. Discrete combustion models have been developed as control-oriented models expressing diesel combustion, where these models can predict the combustion state, however, NOx emission is not considered. In this paper, the NOx emission model for the discrete model is proposed, and its accuracy was evaluated by comparing with the experiment. In this model, the NOx formation period is defined as the period from the ignition timing to the timing defined by the temperature after combustion. The local reaction temperature of the previous model is modified to consider the effect of the amount of injected fuel. The gas concentrations used in the NOx model are obtained from the discrete combustion model and the amount of NOx emission is calculated by using the Arrhenius equation. In the model, the local reaction temperature under the multiple fuel injection is calculated considering spread of heat released by pre combustion and increment of lean mixture. Then, the prediction accuracy of the NOx model was evaluated by comparison with the experimental result showing that the proposed model can predict NOx emissions within 10% error. Moreover, from the viewpoint of the calculation time, this model can predict both engine output and NOx emission within the period of one cycle of the engine, therefore, it can be applicable to real-time engine control applications.
Original language | English |
---|---|
Publication status | Published - 2017 Jan 1 |
Event | 9th International Conference on Modeling and Diagnostics for Advanved Engine Systems, COMODIA 2017 - Okayama, Japan Duration: 2017 Jul 25 → 2017 Jul 28 |
Other
Other | 9th International Conference on Modeling and Diagnostics for Advanved Engine Systems, COMODIA 2017 |
---|---|
Country/Territory | Japan |
City | Okayama |
Period | 17/7/25 → 17/7/28 |
Keywords
- Control-oriented model
- Diesel engine
- Multiple fuel injection
- NOx
ASJC Scopus subject areas
- Control and Systems Engineering
- Electrical and Electronic Engineering
- Mechanical Engineering