[HTML][HTML] Electric vehicle routing, arc routing, and team orienteering problems in sustainable transportation

LC Martins, RD Tordecilla, J Castaneda, AA Juan… - Energies, 2021 - mdpi.com
The increasing use of electric vehicles in road and air transportation, especially in last-mile
delivery and city mobility, raises new operational challenges due to the limited capacity of …

HCP: Heterogeneous computing platform for federated learning based collaborative content caching towards 6G networks

ZM Fadlullah, N Kato - IEEE Transactions on Emerging Topics …, 2020 - ieeexplore.ieee.org
A heterogeneous computing architecture is essential to facilitate intelligent network traffic
control for a joint computation, communication, and collaborative caching optimization in 6G …

[HTML][HTML] Research on micro-mobility with a focus on electric scooters within smart cities

J Vanus, P Bilik - World Electric Vehicle Journal, 2022 - mdpi.com
In the context of the COVID-19 pandemic, an increasing number of people prefer individual
single-track vehicles for urban transport. Long-range super-lightweight small electric …

Scheduling drone charging for multi-drone network based on consensus time-stamp and game theory

V Hassija, V Saxena, V Chamola - Computer Communications, 2020 - Elsevier
Abstract Drones or Unmanned Aerial Vehicles (UAVs) can be highly efficient in various
applications like hidden area exploration, delivery, or surveillance and can enhance the …

Online estimation of driving range for battery electric vehicles based on SOC-segmented actual driving cycle

H Wei, C He, J Li, L Zhao - Journal of Energy Storage, 2022 - Elsevier
The transport sector is one of the most polluting sectors globally, battery electric vehicles
(BEVs) are deemed as one alternative to improve the environmental efficiency for the …

Validation of EKF based SoC estimation using vehicle dynamic modelling for range prediction

EP Sangeetha, N Subashini, TK Santhosh… - Electric Power Systems …, 2024 - Elsevier
Demand for Li-ion batteries is soaring daily in the global Electric Vehicle (EV) market.
Therefore, develo** an accurate, efficient and low-cost Battery Management System …

Predicting electric vehicle energy consumption from field data using machine learning

Q Zhu, Y Huang, CF Lee, P Liu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
This study addresses the challenge of accurately forecasting the energy consumption of
electric vehicles (EVs), which is crucial for reducing range anxiety and advancing strategies …

UAV-aided information diffusion for vehicle-to-vehicle (V2V) in disaster scenarios

Y Kawamoto, T Mitsuhashi… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
To support safe driving and automatic operation, collecting and providing information are
important in intelligent transport systems (ITSs). Information and communication technology …

Least-energy path planning with building accurate power consumption model of rotary unmanned aerial vehicle

D Hong, S Lee, YH Cho, D Baek, J Kim… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Rotary unmanned aerial vehicles (UAVs), also known as drones, have various advantages,
yet their actual applications are limited owing to their flight range. However, increasing the …

[HTML][HTML] A data-driven learning method for online prediction of drone battery discharge

C Conte, G Rufino, G De Alteriis, V Bottino… - Aerospace Science and …, 2022 - Elsevier
This paper describes an adaptive method to predict the battery discharge of a multirotor
drone over a generic path. A proper assessment of battery state of discharge trend is critical …