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R. Huertas Vizcaíno:
"Development of Control Strategies for a Parallel Hybrid Electric Vehicle by Means of a Simulation Model";
Supervisor: B. Geringer, B. Schneeweiss; E315 Institut für Fahrzeugantriebe und Automobiltechnik, 2010.

The future of transport is extremely linked to the future of the raw materials used to provide energy. The existing energetic demand and the future of such demand strongly related to petroleum makes that it is necessary to improve technology in order to develop more efficient systems to reach the goal of sustainability, even more when the predictions about the oil reserves estimate that they will run out within some decades.
Hybrid electric vehicles have the goal of reducing fuel consumption as well as pollutant emissions, through increasing the overall vehicle efficiency. They capability that this kind of vehicles have to decide which torque distribution is necessary at each time instant is the key to achieve these goals. This decision making process is carried out by the power controller.
On this work, various vehicle simulation models are developed with MATLAB. The quasistatic approach, which simulates the vehicle from the wheels to the power sources, is used to develop these models with the high advantage of the low computational effort, working out reliable calculations of the system parameters.
At first a conventional vehicle model is developed, as a reference to compare with the different hybrid electric vehicle models developed. Then, the hybrid electric vehicle models are developed. The chosen configuration corresponds to a parallel hybrid and three models have been designed according to three different control strategies. Two of them have a previously defined torque distribution, so they are called fixed strategies that show the system´s behaviour when the vehicle tries to enhance at first fuel efficiency, and later fuel economy.
The aim of this work is to develop an on line deciding control strategy that determines on each time instant the accurate torque distribution according to different factors such as fuel consumption, emissions, battery state of charge and so on; and looking after the driver´s choice, as well.
One of the advantages of this control strategy is that several influence factors may be added responding to any criterion whenever they are related in some way to one of the system parameters.
Eventually, the results show that fuel consumption and NOx emissions have been significantly reduced, with an overall efficiency increase.