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Lampe, Bernhard
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A Post-Catalyst Control Strategy Based on Oxygen Storage Dynamics

IAV-Michael Tomforde, Matthias Schultalbers
University of Rostock-Wolfgang Drewelow, Bernhard Lampe
Published 2013-04-08 by SAE International in United States
For compliance with future more stringent emission standards exhaust emissions must be reduced. One possibility is to improve air-fuel ratio control quality. The approach presented in this paper uses virtual sensors to get a rough picture of the spatial distribution of lambda and oxygen storage states across the catalyst. This additional process information is gathered by means of a novel model for three-way catalysts. A state-space controller is used to maintain oxygen storage states predicted by the model at desired levels. The proposed control strategy has been implemented on a turbocharged, direct injection engine and successfully validated by means of emission measurements. A comparison with a commonly used air-fuel ratio control strategy is presented.
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Solutions of Hybrid Energy-Optimal Control for Model-based Calibrations of HEV Powertrains

IAV Automotive Engineering-Thomas Juergen Boehme, Benjamin Frank, Matthias Schultalbers
University of Rostock-Markus Schori, Bernhard Lampe
Published 2013-04-08 by SAE International in United States
In this paper optimal control problems for hybrid powertrain vehicles with different drive-modes are considered and solved using numerical techniques. This leads to the formulation of hybrid optimal control problems. The aim is to find optimal controls and optimal switchings between the drive-modes to minimize a cost function resembling fuel consumption. The problem is nonlinear and subject to constraints concerning both controls and state. The techniques include indirect methods as well as direct optimization methods. Efficiency and accuracy are evaluated for all methods using simulation studies. An experimental test on a near mass-production vehicle confirms the usability of the direct optimization approach.
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Application of an Optimal Control Problem to a Trip-Based Energy Management for Electric Vehicles

SAE International Journal of Alternative Powertrains

IAV Automotive Engineering-Thomas Juergen Boehme, Florian Held, Christoph Rollinger, Heiko Rabba, Matthias Schultalbers
University of Rostock-Bernhard Lampe
  • Journal Article
  • 2013-01-1465
Published 2013-04-08 by SAE International in United States
A trip-based energy management strategy for electric vehicles (EVs) is proposed. It can use deterministic routing information obtained from, nowadays, available navigation systems and determines stochastic descriptions of process uncertainties such as stop events as unpredictable disturbances. A dynamic programming algorithm is used to calculate the optimal control trajectories required to reach the target destination safely and to suggest the driver an optimal driving style to maximize the battery range. The algorithm is implemented on a rapid prototyping platform using MATLAB/Simulink. Simulations and experimental results obtained from an EV prototype car are presented.
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