One of the main challenges during the development of operating strategies for modern diesel engines is the reduction of the CO 2 emissions, while complying with ever more stringent limits for the pollutant emissions. The inherent trade-off between the emissions of CO 2 and pollutants renders a simultaneous reduction difficult. Therefore, an optimal operating strategy is sought that yields minimal CO 2 emissions, while holding the cumulative pollutant emissions at the allowed level. Such an operating strategy can be obtained offline by solving a constrained optimal control problem. However, the final-value constraint on the cumulated pollutant emissions prevents this approach from being adopted for causal control. This paper proposes a framework for causal optimal control of diesel engines. The optimization problem can be solved online when the constrained minimization of the CO 2 emissions is reformulated as an unconstrained minimization of the CO 2 emissions and the weighted pollutant emissions (i.e., equivalent emissions). However, the weighting factors are not known a priori. A method for the online calculation of these weighting factors is proposed. It is based on the Hamilton-Jacobi-Bellman (HJB) equation and a physically motivated approximation of the optimal cost-to-go. A case study shows that the causal control strategy defined by the online calculation of the equivalence factor and the minimization of the equivalent emissions is only slightly inferior to the non-causal offline optimization, while being applicable to online control.Energies 2014, 7 1231
In order to comply with increasingly stringent diesel-engine emission legislation, fast and precise control of the turbochargers and exhaust-gas recirculation are necessary. The difficulties lie in certain disadvantageous plant properties such as cross-couplings and non-linearities, the disturbance of the air path by fast operating-point changes and the multitude of air-path configurations that are available. In this paper, a novel model-based approach for air-path control based on cascaded control is proposed. The resulting multi-variable controller has a low sensitivity to the non-linearity of the plant and the disturbances caused by sudden changes in the operating point. Furthermore, the controller is applicable to various types of air-path configuration. This flexibility is demonstrated by a system analysis of the models of two engines which span a broad range of air-path configurations. The performance of the proposed controller is compared experimentally with that of a conventional model-based multi-variable controller, by implementing both on an engine test bench. This comparison confirms that the cascaded controller presented herein can handle the cross-couplings of the system and that it exhibits a lower sensitivity to the non-linearity and the disturbances than the conventional controller does.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.