Predictive Engine and Aftertreatment Control Concepts for a Heavy-Duty Long-Haul Truck

Autoren

Giovanni Vagnoni, MSc., Dipl.-Ing. Sebastian Petri, Ferenc Aubeck, MSc., Institut für Verbrennungskraftmaschinen (VKA), RWTH Aachen University, Aachen;
Johan Lindberg, MSc. E.E., Dr. Esteban R. Gelso, Volvo Group, Göteborg;
Prof. Dr. Nikolce Mugovski, Mohammed R. Karim, Chalmers University, Göteborg;
Dr.-Ing. Joschka Schaub, Andrea Pantaleo, FEV Europe GmbH, Aachen

Zusammenfassung

This paper considers the modular control framework for energy and emissions management developed within the IMPERIUM project. The framework is proposed for a long haul truck equipped with a 13 L Volvo Diesel engine and it aims to improve the
operating system efficiency. The focus of the paper is the development and the evaluation of three key functions of the control framework: the "Integrated Engine and Aftertreatment System (EATS) Supervisory Controller" and two local controllers, for
the engine and the aftertreatment system. Whilst for the last two only a brief introduction is given, for the "Integrated Engine and EATS Supervisory Controller" a detailed description of the Optimal Control Problem (OCP) formulation and its solution strategies is provided. A controller is proposed based on a moving horizon Nonlinear Model Predictive Control (NMPC), which is tested in a simulation environment and benchmarked against Dynamic Programming (DP) strategies.

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