Mean Value Engine Models Applied to Control System Design and Validation

Abstract

The importance of simulation in power train and combustion engine development is undisputed today, but the search for the most efficient use of simulation in the development cycle is still ongoing. In parallel available computing power and the number of tools are increasing. The choice of the right tool has significant impact on the development process. In this chapter some insight will be given into a process relying on the mean value model approach for control strategy development and validation regarding the development of a 1.6-litres 4-cylindre direct injection diesel engine respecting Euro 5 legislation. To reach the performance and emission targets in a cost effective way, simulation was used early in the project to study different concepts of air loop control architecture and then was employed for the control function development of the air loop control. The present study addresses the main components of the mean value model, the air loop, the degree of refinement in regards to combustion and the actuator dynamics. Two variants of a new control concept have been studied with considerable refinement. To position the predicted performance they were compared to the conventional Euro 4 approach. To obtain significant simulation results the work was concentrated on specific engine life situations. The comparatively fast execution of mean value models has been exploited to realize statistical computations on the robustness of the controlled system. The main targets of control development are a high degree of precision but also a robust behavior in real life. To asses the performance of the control approaches under study, the main sources of disturbances du to series production were identified and than this knowledge was used to build a mean engine model that allowed to represent their impact on the engine. This allowed distinguishing the control approaches not only on their capacity to perform well on a nominal engine but their ability to cope with the large spectrum of engine behavior to be expected in series production. The obtained results allowed for an intelligent choice of the control strategy, choice which has been confirmed by experimental work.