Electric vehicles' energy consumption estimation with real driving condition data
R Zhang, E Yao - Transportation Research Part D: Transport and …, 2015 - Elsevier
The use of electric vehicles (EVs) is viewed as an attractive option to reduce CO 2 emissions
and fuel consumption resulted from transport sector, but the popularization of EVs has been …
and fuel consumption resulted from transport sector, but the popularization of EVs has been …
Prediction of electric vehicles charging demand: A transformer-based deep learning approach
Electric vehicles have been gaining attention as a cleaner means of transportation that is
low-carbon and environmentally friendly and can reduce greenhouse gas emissions and air …
low-carbon and environmentally friendly and can reduce greenhouse gas emissions and air …
Comparison of machine learning algorithms for the power consumption prediction:-case study of tetouan city–
A Salam, A El Hibaoui - 2018 6th International Renewable and …, 2018 - ieeexplore.ieee.org
Predicting electricity power consumption is an important task which provides intelligence to
utilities and helps them to improve their systems' performance in terms of productivity and …
utilities and helps them to improve their systems' performance in terms of productivity and …
Electric vehicle charging demand forecasting using deep learning model
Greenhouse gas (GHG) emission and excessive fuel consumption have become a pressing
issue nowadays. Particularly, CO2 emissions from transportation account for approximately …
issue nowadays. Particularly, CO2 emissions from transportation account for approximately …
Velocity prediction using Markov Chain combined with driving pattern recognition and applied to Dual-Motor Electric Vehicle energy consumption evaluation
X Lin, G Zhang, S Wei - Applied Soft Computing, 2021 - Elsevier
Vehicle velocity prediction is of great significance in electric vehicle (EV) energy
consumption evaluation. However, vehicle velocity prediction is complicated due to the …
consumption evaluation. However, vehicle velocity prediction is complicated due to the …
Charging demand of plug-in electric vehicles: Forecasting travel behavior based on a novel rough artificial neural network approach
The market penetration of Plug-in Electric Vehicles (PEVs) is escalating due to their energy
saving and environmental benefits. In order to address PEVs impact on the electric …
saving and environmental benefits. In order to address PEVs impact on the electric …
Aggregated electric vehicle fast-charging power demand analysis and forecast based on LSTM neural network
M Chang, S Bae, G Cha, J Yoo - Sustainability, 2021 - mdpi.com
With the widespread use of electric vehicles, their charging power demand has increased
and become a significant burden on power grids. The uncoordinated deployment of electric …
and become a significant burden on power grids. The uncoordinated deployment of electric …
An advanced framework for net electricity consumption prediction: Incorporating novel machine learning models and optimization algorithms
X Li, Z Wang, C Yang, A Bozkurt - Energy, 2024 - Elsevier
In recent years, the escalating demand for electric energy has underscored the need for
robust prediction models capable of accurately anticipating consumption patterns. The …
robust prediction models capable of accurately anticipating consumption patterns. The …
A machine-learning ensemble model for predicting energy consumption in smart homes
Smart homes incorporate several devices that automate tasks and make our lives easy.
These devices can be useful for many things, like security access, lighting, temperature, etc …
These devices can be useful for many things, like security access, lighting, temperature, etc …
A hybrid method for power demand prediction of electric vehicles based on SARIMA and deep learning with integration of periodic features
F Ren, C Tian, G Zhang, C Li, Y Zhai - Energy, 2022 - Elsevier
Accurate power demand prediction of electrical vehicles (EVs) is crucial to power grid
operation. To fully utilize the existing knowledge of EVs' power demand and further improve …
operation. To fully utilize the existing knowledge of EVs' power demand and further improve …