Driving segment simulation for determination of the most effective driving features for HEV intelligent control
Driving segment simulation for determination of the most effective driving features for HEV intelligent control
- New search for: Montazeri, Morteza
- New search for: Fotouhi, Abbas
- New search for: Naderpour, Akbar
- New search for: Montazeri, Morteza
- New search for: Fotouhi, Abbas
- New search for: Naderpour, Akbar
This paper presents a methodological approach for determination of the most effective driving features for hybrid electric vehicle intelligent control, using the driving segment simulation. In this approach, driving data gathering is first performed in real traffic conditions using Advanced Vehicle Locator systems. The vehicle's speed time series are then divided into small segments. Subsequently, 19 driving features are defined for each driving segment, and the influence of the driving features on the vehicle's fuel consumption (FC) and exhaust emissions is investigated, using the driving segment simulation. The simulation approach is also verified by experimental test. Finally, the driving features are ranked by a new approach based on the definition of an effectiveness index and a correlation analysis. The results demonstrate that the velocity-dependent driving features such as 'energy', 'mean of velocity', 'displacement' and 'maximum velocity' are more effective on vehicle's FC and exhaust emissions. However, because of high dependency between these features, this study suggests independent driving features among the most effective driving features.
Document information
Driving segment simulation for determination of the most effective driving features for HEV intelligent control
Fahrsegmentsimulation zur Bestimmung der wirksamsten Fahrcharakteristika für intelligente Regelungen von Hybridfahrzeugen
Vehicle System Dynamics ; 50 , 1-3 ; 229-246
2012
18 Seiten, 11 Bilder, 8 Tabellen, 20 Quellen
Article (Journal)
English
Similar titles
| Taylor & Francis Verlag | 2012
| Automotive engineering | 2012