Optimal Energy Management for Parallel Hybrid Electric Vehicles using Dynamic Programming
Abstract: In this thesis, two optimal control problems for the control of hybrid electric vehicles are formulated. The first is general formulation where both velocity and state of charge can vary. The second is a formulation where the velocity is prespecified and therefore only the state of charge can vary. The first formulation takes significantly more time to solve with dynamic programming than the second formulation. For the most hilly drive cycle that was evaluated, 4:45 % fuel savings were obtained by using the general formulation over the formulation with prespecified velocity. For the least hilly cycle, this number dropped to 1:75%. When the lowest admissible velocity was lowered from 75 to 70 km/h, fuel savings of 0:52 % were obtained. From 80 to 70 km/h, the number increased to 1:92 %. In conclusion, if dynamic programming is to be implemented in real time on a hybrid electric vehicle the fuel savings for hilly roads where a low minimal velocity is allowed are potentially much greater than when using prespecifued velocity. However, for less hilly roads and where the velocity is not allowed to vary as much, it might be more beneficial in terms of fuel consumption to use the formulation with prespecified velocity and include abilities such as gear shifting or switching the engine on or off.
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