Zobrazeno 1 - 10
of 57
pro vyhledávání: '"electrified powertrains"'
Publikováno v:
Vehicles, Vol 4, Iss 3, Pp 808-824 (2022)
In order to improve the efficiency of electrified vehicle drives, various predictive energy management strategies (driving strategies) have been developed. This article presents the extension of a generic prediction approach already proposed in a pre
Externí odkaz:
https://doaj.org/article/3d0cb35731b84114a46e43b8a77fb140
Publikováno v:
Vehicles, Vol 4, Iss 2, Pp 464-481 (2022)
Various energy management systems (driving strategies) have been developed to improve the efficiency of electrified vehicle drives. These include strategies from the field of offline optimization to determine the theoretical optimum for a given syste
Externí odkaz:
https://doaj.org/article/bfedefe75ac9496794a381b5b79c6879
Publikováno v:
World Electric Vehicle Journal, Vol 14, Iss 12, p 353 (2023)
To increase the efficiency of electrified vehicles, many energy management strategies (driving strategies) have been proposed. These include both offline optimization techniques to identify a system’s theoretical optimum and online optimization tec
Externí odkaz:
https://doaj.org/article/20389659a3e14860b47168cc7fcae59d
Publikováno v:
Vehicles, Vol 4, Iss 1, Pp 182-198 (2022)
In order to further increase the efficiency of electrified vehicle drives, various predictive energy management strategies (driving strategies) have been developed. Therefore, a generic prediction approach is worked out in this paper, which enables a
Externí odkaz:
https://doaj.org/article/504bfeceaa7940799759f65029fd0744
Autor:
Karim Hamza, Kang-Ching Chu, Matthew Favetti, Peter Keene Benoliel, Vaishnavi Karanam, Kenneth P. Laberteaux, Gil Tal
Publikováno v:
World Electric Vehicle Journal, Vol 12, Iss 4, p 161 (2021)
Software tools for fuel economy simulations play an important role during design stages of advanced powertrains. However, calibration of vehicle models versus real-world driving data faces challenges owing to inherent variations in vehicle energy eff
Externí odkaz:
https://doaj.org/article/0d51c1e1d68b40b494a5b79505f3460b
Akademický článek
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Publikováno v:
Publications of the Ray W. Herrick Laboratories
Machine learning classification is a common method for vehicle noise and vibration (N&V) fault diagnosis which helps improve vehicle safety, comfort, and reduce maintenance cost. To improve the accuracy of classification, the model requires sufficien
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______540::9b7bfd59a7b61e66b1a2773223bb3fad
https://docs.lib.purdue.edu/herrick/272
https://docs.lib.purdue.edu/herrick/272
Akademický článek
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Publikováno v:
Vehicles; Volume 4; Issue 3; Pages: 808-824
In order to improve the efficiency of electrified vehicle drives, various predictive energy management strategies (driving strategies) have been developed. This article presents the extension of a generic prediction approach already proposed in a pre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::4306e69410dcbcb05fba957816586345
Publikováno v:
Energies, Vol 12, Iss 11, p 2058 (2019)
This study presents an integrated energy and thermal management system to identify the fuel-saving potential caused by cold-starting an electrified powertrain. In addition, it quantifies the benefit of adopting waste heat recovery (WHR) technologies
Externí odkaz:
https://doaj.org/article/ead07f506d494d109019728365e8367a