An Equivalent Emission Minimization Strategy for Causal Optimal Control of Diesel Engines

Stephan Zentner, Jonas Asprion, Christopher Onder and Lino Guzzella
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Stephan Zentner: Institute for Dynamic Systems and Control, Department of Mechanical and Process Engineering, ETH Zurich, Sonneggstrasse 3, 8092 Zurich, Switzerland
Jonas Asprion: Institute for Dynamic Systems and Control, Department of Mechanical and Process Engineering, ETH Zurich, Sonneggstrasse 3, 8092 Zurich, Switzerland
Christopher Onder: Institute for Dynamic Systems and Control, Department of Mechanical and Process Engineering, ETH Zurich, Sonneggstrasse 3, 8092 Zurich, Switzerland
Lino Guzzella: Institute for Dynamic Systems and Control, Department of Mechanical and Process Engineering, ETH Zurich, Sonneggstrasse 3, 8092 Zurich, Switzerland

Energies, 2014, vol. 7, issue 3, 1-21

Abstract: 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 CO2 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.

Keywords: optimization; fuel consumption; NOx; soot; particulate matter; pollutant; trade-off; driving cycle; operating strategy; model-predictive control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2014
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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