This paper is a first step towards optimization of driving style to obtain an extended driving range for future electric vehicles. The main advantage is that no drastic changes need to be done in battery packs or drive trains. However, the model is limited because no real life traffic situations are taken into account, such as traffic jam, speed limits, slipstreams, etc. Further investigation in optimizing the follow up distance between vehicles and consideration of the instantaneous energy consumption needs to be done, to make the algorithm suitable for daily traffic situations. Also constraints on maximum speed need to be implemented to resemble speed limits. Secondly the weight parameter needs to be optimized. It would be interesting to use a formula instead of the weight, with parameters dependent on mass, aerodynamics of the vehicle ana relief of the trajectory. By improving calculation time, the algorithm can be used for on line calculation. This way it can be integrated in a commercial GPS-system, where trajectories are calculated by using start point and destination. A simplified algorithm of this model can be used for efficient train transportation, since diverting from the route can be disregarded and only one motor needs to be controlled. Future research can be done to extend this model so it can be used for driving agricultural vehicles through a hilly landscape.
Optimal dynamic predictive cruise control for differential driven electric vehicles
EVS, Electric Vehicle Symposium, 26 ; 1292-1302
2012
11 Seiten, 13 Bilder, 1 Tabelle, 8 Quellen
Conference paper
English
Predictive cruise control in hybrid electric vehicles
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