To cope with more stringent emissions standarts, diesel engines have been equipped with increasing number of airpath actuators and sensors. The goals of using these devices are, on one hand, to control the chemical content of the emissions by 7dynamically controlling the pressure and oxigen content of the gas entering the motor; on the other hand, to satisfy expected power requirements. New emission standarts imply dynamic calibration tests, and especially in heavy duty vehicles, emissions are assessed by road tests to see if they are within the legal limits. Such requirements necessitate dynamic control of the combustion.
In a current project funded by Ford Otosan, airpath related dynamically controllable combustion variables are dealt with. Using results of the System Identification project, appropriate control architectures for airpath channels inside the Electronic Control Unit (ECU) are investigated. As the outcome of the project, a new control architecture compatible with current needs and that can work harmoniously with other functions and available sensors will be developed.
Diesel engines are widely used in both light-duty and highduty automobile industry. Due to the hazardous emissions of diesel engines such as NOx gases and soot, governmental institutions regulates the maximum acceptable emission values which are exponentially declining. Therefore engine and vehicle manufacturers require a diesel engine combustion model to determine the best engine operating conditions that provides minimum emission values with maximum power. However, combustion process in a diesel engine is a highly nonlinear dynamic system and physical modeling of this process is very challenging. Even a physical model is achieved, it will be only applicable for one specific diesel engine. As a consequence, a data-driven model is sought to optimize the parameters of the engine operating conditions.
In a recent project funded by Ford Otosan, a novel input design framework in terms of multi-sweep chirp signals was developed and input channels (both airpath and fuel) were excited by these chirp signals. Linear and nonlinear system identification methods were utilized to model NOx emissions with airpath input channels. In the first year (Phase-I), the focus was on developing nonlinear NARX and Hammerstein-Wiener models for NOx, Torque and Temperature representation. In the second year (Phase-II) of the project, obtained models were robustified against data perturbations and possible parameter variations.
