Škugor, Branimir and Deur, Joško (2017) Synthetic driving cycles-based modelling of extended range electric vehicle fleet energy demand. = Synthetic driving cycles-based modelling of extended range electric vehicle fleet energy demand. In: 30th International Electric Vehicle Symposium & Exhibition (EVS30), 09-11.10.2018., Stuttgart.
Full text not available from this repository.Abstract
The paper deals with modelling of transport energy demand related to an electric vehicle (EV) fleet. The main aim of the paper is to provide a proper methodology of deriving a simple transport energy demand model aimed to be used within: (i) real-time control of EV fleet charging, (ii) planning of EV fleet routes, and (iii) various EV fleet-related techno-economic analysis studies. The model is represented by maps also known as response surfaces, which are obtained by simulating the considered EV model over synthetic driving cycles. The synthetic driving cycles are introduced to replace a high number of recorded driving cycles in a statistically representative way, thus reducing the number of time-consuming EV simulations. The final transport energy demand model is validated against the more precise energy consumption data obtained by simulating EREV model over the full set of recorded driving cycle.
| Item Type: | Conference or Workshop Item (Poster) |
|---|---|
| Keywords (Croatian): | Energy consumption, modelling, EREV (extended range electric vehicle) |
| Subjects: | TECHNICAL SCIENCE > Mechanical Engineering |
| Divisions: | 900 Department of Robotics and Production System Automation > 910 Chair of Engineering Automation |
| Indexed in Web of Science: | No |
| Indexed in Current Contents: | No |
| Date Deposited: | 11 Sep 2018 10:56 |
| Last Modified: | 18 Oct 2018 14:12 |
| URI: | http://repozitorij.fsb.hr/id/eprint/8704 |
Actions (login required)
 |
View Item |
Citations:
Citations: