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ATZelectronics worldwide
Published in: ATZelectronics worldwide 2/2014

01-04-2014 | Development

Electrified vehicle powertrains Optimisation of efficiency by predictive energy management

Authors: Dr.-Ing. Armin Engstle, M. Sc. Andreas Zinkl, Dipl.-Ing. Anton Angermaier, Dr. Wolfgang Schelter

Published in: ATZelectronics worldwide | Issue 2/2014

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Excerpt

The AVL software package “upgrade-E” enables the predictive calculation of the expected speed, elevation and tractive power requirements of an unknown driving route. The development platform mainly accesses freely available data formats such as Open Street Map (OSM) and SRTM altitude profiles. The predicted driving route provides a plethora of optimisation possibilities for classical vehicle and powertrain functions. The prototype version of the software is implemented in AVL’s electric vehicle Coup-e 800 and runs on a conventional 7-inch tablet PC with appropriate data gateways to the vehicle’s CAN bus. …
previous article Algorithms for Recuperation and Traction in Electric Vehicles
next article Reduced Validation Effort for Dynamic Light Functions

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Literature
[1]
Wilde, A.: Eine modulare Funktionsarchitektur für adaptives und vorausschauendes Energiemanagement in Hybridfahrzeugen. Dissertation TU München. 10/2009. pp. 52 ff.
[2]
Kriesten, R.; Traub, M.: Predictive Coupling of routing and energy management systems for pure electric vehicles. In: ATZelektronik 8 (2013), No. 6, pp. 26 ff.CrossRef
[3]
Wietschel, M. et al: Kaufpotenzial für Elektrofahrzeuge bei sogenannten “Early Adoptern”. Studie im Auftrag des Bundesministeriums für Wirtschaft und Technologie (BMWi). p. 10, Karlsruhe, Juni 2012
[4]
Engstle, A.; Deiml, M.; Angermaier, A.; Schelter, W.: 800 Volt für Elektrofahrzeuge, eine applikationsgerechte Spannungslage. In: ATZ 115 (2013), No. 11, pp. 66
[5]
Hoffmann, J.; Walter, D.: How Complementary are SRTM-X and -C Band Digital Elevation Models? Photogrammatic Engineering & Remote Sensing. März 2006. pp. 261–268
Metadata
Title
Electrified vehicle powertrains Optimisation of efficiency by predictive energy management
Authors
Dr.-Ing. Armin Engstle
M. Sc. Andreas Zinkl
Dipl.-Ing. Anton Angermaier
Dr. Wolfgang Schelter
Publication date
01-04-2014
Publisher
Springer Fachmedien Wiesbaden
Published in
ATZelectronics worldwide / Issue 2/2014
Electronic ISSN: 2524-8804
DOI
https://doi.org/10.1365/s38314-014-0232-z

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