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This paper investigates how recently endorsed methods in distributed optimization can be exploited in the energy-management problem for heavy trucks, with focus on improved control of ancillary systems. The justification for investigating this is because it may offer higher modularity and integrity to the development process of vehicle models.
This submission deals with energy management of automotive ancillary systems, and how to find suitable control actions that can improve fuel economy compared to control laws that do not exploit the storage potential of energy buffers. The main focus lies on how to model components to fit within the framework of convex optimization. The resulting convex models allow the energy-management problem to...
The degree of importance of prediction in the control of ancillary systems for conventional heavy-duty trucks is investigated, with focus on fuel economy. An optimal control law that utilizes prediction is compared with a suboptimal causal control law. The incentive for this investigation is that the suboptimal control law is less complex to develop and implement for the considered system. The results...
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