Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Ahad Hamednia"'
Publikováno v:
ICT Express, Vol 8, Iss 1, Pp 37-43 (2022)
To enable optical interconnect fluidity in next-generation data centers, we propose adaptive transmission based on machine learning in a wavelength-routing network. We consider programmable transmitters that can apply N possible code rates to connect
Externí odkaz:
https://doaj.org/article/5300325fbf984443a5ad13ccae6271f0
Autor:
Ahad Hamednia, Nikolce Murgovski, Jonas Fredriksson, Jimmy Forsman, Mitra Pourabdollah, Viktor Larsson
Publikováno v:
IEEE Transactions on Vehicular Technology. :1-14
This paper addresses optimal battery thermal management (BTM), charging, and eco-driving of a battery electric vehicle (BEV) with the goal of improving its grid-to-meter energy efficiency. Thus, an optimisation problem is formulated, aiming at findin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5e3f131a489f57c7d24932a7ecf59552
https://doi.org/10.1109/tvt.2023.3240279
https://doi.org/10.1109/tvt.2023.3240279
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 23:6556-6570
This paper presents a computationally efficient algorithm for eco-driving along horizons of over 100km. The eco-driving problem is formulated as a bi-level program, where the bottom level is solved offline, pre-optimising gear as a function of longit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::35ef136a630da156c0837cd55e8af271
https://doi.org/10.1109/tits.2021.3058418
https://doi.org/10.1109/tits.2021.3058418
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 22:7792-7803
We propose an eco-driving technique for a heavy-duty ego vehicle that drives behind a leading heavy-duty vehicle. By observing a decrease in speed of the leading vehicle when driving uphill, its power capability is estimated and its future speed is p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e91d1f2b88a930a2e634bd14fd919f1b
https://doi.org/10.1109/tits.2020.3009288
https://doi.org/10.1109/tits.2020.3009288
Publikováno v:
ITSC
This paper addresses eco-driving of an electric vehicle driving in a hilly terrain under stochastic wind speed uncertainty. The eco-driving problem has been formulated as an optimisation problem, subject to road and traffic information. To enhance th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::234d750b00065180a16006aa632ba3bc
https://doi.org/10.1109/itsc48978.2021.9564621
https://doi.org/10.1109/itsc48978.2021.9564621
Publikováno v:
ITSC
This paper addresses optimising a trans-port mission by controlling the mission start time and velocity profile of an electric vehicle (EV) driving in a hilly terrain, subject to legal and dynamic speed limits imposed by traffic congestion. To this e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::138cf0efac59905ff7b615ea6f2ea1d0
https://doi.org/10.1109/itsc45102.2020.9294341
https://doi.org/10.1109/itsc45102.2020.9294341
Publikováno v:
IFAC-PapersOnLine. 51:485-492
This paper presents a computationally efficient velocity control of vehicles driving in a possibly hilly terrain and over long look-ahead horizons that may stretch to hundreds of kilometers. The controller decouples gear scheduling into an online opt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2a61d9eb0f540ea6848704c007ffa684
https://doi.org/10.1016/j.ifacol.2018.10.107
https://doi.org/10.1016/j.ifacol.2018.10.107
Autor:
Nalin Kumar Sharma, Sten Elling Tingstad Jacobsen, Sachin Madhusudhana, Nikolce Murgovski, Ahad Hamednia, Nam Vu, Anton Gustafsson
Publikováno v:
IV
This paper presents an energy-efficient velocity control technique for a truck driving behind a slow moving truck. An observer is designed to estimate the acceleration capability of the leading vehicle, which is then used to predict the velocity and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5293648c533a9404145968995afb27f0
https://doi.org/10.1109/ivs.2019.8814014
https://doi.org/10.1109/ivs.2019.8814014