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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Koehler, S. Viehl, A. Bringmann, O. Rosenstiel, W. |
| Copyright Year | 2014 |
| Description | Author affiliation: FZI Karlsruhe, Karlsruhe, Germany (Koehler, S.; Viehl, A.; Bringmann, O.; Rosenstiel, W.) |
| Abstract | We propose a novel operation strategy for electric vehicles with axle-individual electric machines to improve their energy efficiency in typical driving situations. The developed algorithm is allocating a total torque requested by a velocity controlling system or the driver to the electric machines such that the energy loss is reduced compared to an equal distribution. By taking near-future forecasts into account, the predictive nature of the algorithm leads to a minimized number of clutching processes compared to previous work and thereby contributes to increased comfort and minimized component wear. Overall, an average reduction of up to 25% in the electric machine losses can be achieved for the ARTEMIS driving cycles. At the same time, a reduction of the clutching operations by 70% is possible due to the forecast, compared to algorithms only considering the momentary state. |
| Sponsorship | IEEE Intell. Transp. Syst. Soc. |
| Starting Page | 1109 |
| Ending Page | 1114 |
| File Size | 495489 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781479936380 |
| DOI | 10.1109/IVS.2014.6856499 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-06-08 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Torque Vehicles Optimization Switches Energy management Prediction algorithms Batteries |
| Content Type | Text |
| Resource Type | Article |
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