Browsing by Subject "Supervisory controllers"

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Open Access
Concurrent design of energy management and vehicle traction supervisory control algorithms for parallel hybrid electric vehicles
(Institute of Electrical and Electronics Engineers Inc., 2016) Dokuyucu, H. I.; Cakmakci, M.
In this paper, concurrent design of energy management (EM) and traction control algorithms for a vehicle equipped with a parallel hybrid powertrain is studied. This paper focuses on designing the two control algorithms together as one control design problem, which are traditionally considered separately. First, optimal control actions and operating points are obtained by applying dynamic programming (DP). Then, this information is used for developing a rule-based supervisory controller. Our objective is to minimize the fuel consumption and the wheel slip simultaneously. Two control problems are also solved separately and compared with the concurrent solution. Results show that promising benefits can be obtained by using the concurrent design approach rather than considering two control problems separately. Under the same conditions, the vehicle with the concurrent supervisory controller is 16% more efficient in fuel consumption and experiences 12% less wheel slip, assuming slippery road friction conditions. © 1967-2012 IEEE.
Open Access
Development of a supervisory controller for residential energy management problems
(AACC, 2012-06) Akgün, Emre; Çakmakçı, Melih
In recent years, the infrastructure that supplies energy to residential areas has started to evolve into a multi-source system, just like in automotive industry in which hybrid electric vehicles (HEVs) have been replacing conventional gasoline vehicles. Multi energy source systems considered as a potential solution for carbon emission problems despite their challenges in their operation due to increased complexity. In this paper, a control design approach successfully applied in the automotive industry is used to solve a residential energy management problem. First, a dynamic programming method is applied to obtain optimal control actions for the representative demand profiles and then by using these results, a causal supervisory controller is developed. It is found that the developed baseline controller performs 1-2% better daily in its initial form in terms of operational costs, compared to available heuristic strategies. © 2012 AACC American Automatic Control Council).