New requirements and guidelines for fuel saving, decreasing emissions and the customer requirements for more driving performance are reasons for the development of hybrid electric vehicles. The choice of certain control strategies of these drive trains has a big influence on the energy efficiency of those vehicles. In this academic paper some approaches for control strategies are discussed. A simple proposal to describe a control strategy for a hybrid vehicle is the usage of defined basic system states, which are linked to the according combination of drive train components. A parameter set with specific limiting values decides the mode switching strategy. Using constant characteristics of these parameters is then called a static control strategy. Advantages arise from the high drive train performance reproducibility for the driver as well as the easy way of implementation on the control unit. For increasing the energy efficiency depending of the driving situation the integration of further parameter data sets is one possibility for a next step. One disadvantage here might be the higher memory requirements to the control unit. These data sets can be optimized in a first step during an offline-optimization, executed on commercial computer simulation tools. The inexactness of the implemented hybrid vehicle drive train models in those tools can be beared down by using a hardware-in-the-loop test bench. Then the final implementation on a real vehicle might lead to further fuel savings. The biggest potentials are given by the so called predictive control strategies. But low-precision prediction data may cause increased fuel consumption. Hence one great challenge consists in the correction of these data by use of several integrated systems. The first step can be seen by comparison of different environment information systems, GPS, car-2-x and historic driving data. After this the usage of stochastic methods is one way to fuse these information systems. In the next step a calculation method for online optimization is presented, the so called model predictive control. Finally it can be concluded that there are a number of other methods to optimize the control strategy, however the advantages of this method described here rely on the usage of many different information with a defined dynamic weighting. Furthermore the application of a prediction quality measure system could also include aspects like aging of sensor systems or different driving behaviours.
Concept study for an efficient operating control of hybrid vehicles based on environment information
Konzeptstudie für eine effiziente Betriebsführung von Hybridfahrzeugen durch Fahrzeugumfeldinformationen
2008
11 Seiten, 5 Bilder, 1 Tabelle, 8 Quellen
Aufsatz (Konferenz)
Datenträger
Englisch
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