Hierarchical predictive energy management of hybrid electric buses based on driver information
To improve the energy efficiency of hybrid electric city buses, a hierarchical predictive
energy management strategy (HP-EMS) based on driver behavior and type is proposed in …
energy management strategy (HP-EMS) based on driver behavior and type is proposed in …
Ensemble machine learning based driving range estimation for real‐world electric city buses by considering battery degradation levels
Battery electric buses (BEBs) have been regarded as effective options to address the
congestion and pollution problems in the field of urban transportation. However, since the …
congestion and pollution problems in the field of urban transportation. However, since the …
Estimation of the energy demand of electric buses based on real-world data for large-scale public transport networks
An increasing number of cities are transitioning from fossil fuel-powered buses for public
transport to battery electric buses. Evaluating the energy demand of buses has become an …
transport to battery electric buses. Evaluating the energy demand of buses has become an …
Fine-grained RNN with transfer learning for energy consumption estimation on EVs
Electric vehicles (EVs) are increasingly becoming an environmental-friendly option in
current transportation systems, thanks to reduced fossil fuel consumption and carbon …
current transportation systems, thanks to reduced fossil fuel consumption and carbon …
Analysis of energy consumption for electric buses based on low-frequency real-world data
Z Xu, J Wang, PD Lund, Y Zhang - Transportation Research Part D …, 2023 - Elsevier
Energy consumption management is a referential approach to alleviate range anxiety. In this
paper, the data-driven modeling and analysis of energy consumption based on low …
paper, the data-driven modeling and analysis of energy consumption based on low …
Trip-level energy consumption prediction model for electric bus combining Markov-based speed profile generation and Gaussian processing regression
J Jiang, Y Yu, H Min, Q Cao, W Sun, Z Zhang, C Luo - Energy, 2023 - Elsevier
Electric bus energy consumption prediction is conducive to bus route scheduling and
charging optimization management. However, existing prediction models do not …
charging optimization management. However, existing prediction models do not …
Energy consumption estimation for electric buses based on a physical and data-driven fusion model
X Li, T Wang, J Li, Y Tian, J Tian - Energies, 2022 - mdpi.com
The energy consumption of electric vehicles is closely related to the problems of charging
station planning and vehicle route optimization. However, due to various factors, such as …
station planning and vehicle route optimization. However, due to various factors, such as …
Toward safe and smart mobility: Energy-aware deep learning for driving behavior analysis and prediction of connected vehicles
Connected automated driving technologies have shown tremendous improvement in recent
years. However, it is still not clear how driving behaviors and energy consumption correlate …
years. However, it is still not clear how driving behaviors and energy consumption correlate …
DeepFEC: Energy consumption prediction under real-world driving conditions for smart cities
S Elmi, KL Tan - Proceedings of the Web Conference 2021, 2021 - dl.acm.org
The status of air pollution is serious all over the world. Analysing and predicting vehicle
energy consumption becomes a major concern. Vehicle energy consumption depends not …
energy consumption becomes a major concern. Vehicle energy consumption depends not …
Online Learning Models for Vehicle Usage Prediction During COVID-19
T Lindroth, A Svensson, N Åkerblom… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Today, there is an ongoing transition to more sustainable transportation, for which an
essential part is the switch from combustion engine vehicles to battery electric vehicles …
essential part is the switch from combustion engine vehicles to battery electric vehicles …