Research graph
References from Decomposed kinetics of electric vehicle energy consumption rate: A multi-method approach. Local targets link to admitted publications; unresolved targets remain external evidence.
Global drive toward net-zero emissions and sustainability via electric vehicles: an integrative critical review
10.1007/s40974-024-00351-7 · 2025 · External reference
10.2139/ssrn.5069182
10.2139/ssrn.5069182 · External reference
Electric vehicle adoption: a comprehensive systematic review of technological, environmental, organizational and policy impacts
10.3390/wevj15080375 · 2024 · External reference
A comprehensive study on the expansion of electric vehicles in Europe
10.3390/app122211656 · 2022 · External reference
Accurate range estimation for an electric vehicle including changing environmental conditions and traction system efficiency
10.1049/iet-est.2015.0052 · 2017 · External reference
Energy consumption analysis and prediction of electric vehicles based on real-world driving data
10.1016/j.apenergy.2020.115408 · 2020 · External reference
Artificial intelligence innovation and the global energy trilemma: a cross-country panel analysis of conditional associations
2026 · External reference
Artificial intelligence and energy resilience: dynamic evolution, developmental heterogeneity, and the moderating roles of geopolitical risk and clean energy
2026 · External reference
Mathematical modeling of driving forces of an electric vehicle for sustainable operation
10.1109/access.2023.3309728 · 2023 · External reference
Unresolved reference
2021 · External reference
Energy modeling for electric vehicles based on real driving cycles: an artificial intelligence approach for microscale analyses
10.3390/en17051148 · 2024 · External reference
Driver alerting system using range estimation of electric vehicles in real time under dynamically varying environmental conditions
10.1049/iet-est.2014.0067 · 2016 · External reference
A novel data-driven framework for driving range prognostics in electric vehicles
10.1016/j.engappai.2024.109925 · 2025 · External reference
Predicting electric vehicle energy consumption from field data using machine learning
10.1109/tte.2024.3416532 · 2025 · External reference
Evaluating the energy consumption of an electric vehicle under real-world driving conditions
10.4271/2022-01-1127 · 2022 · External reference
Influence of driving style, infrastructure, weather and traffic on electric vehicle performance
10.1016/j.trd.2020.102569 · 2020 · External reference
Electric vehicle energy consumption modelling and prediction based on road information
10.3390/wevj7030447 · 2015 · External reference
Energy consumption effects of speed and acceleration in electric vehicles: laboratory case studies and implications for drivers and policymakers
10.1016/j.trd.2017.04.020 · 2017 · External reference
Vehicle acceleration and speed as factors determining energy consumption in electric vehicles
10.3390/en17164051 · 2024 · External reference
Holistic sensitivity analysis for long-term energy demand prediction of battery electric vehicles
10.1007/s42154-024-00292-1 · 2024 · External reference
Development of hybrid vehicle energy consumption model for transportation applications—Part II: traction force-speed based energy consumption modeling
10.3390/wevj10020022 · 2019 · External reference
EV-PINN: a physics-informed neural network for predicting electric vehicle
2024 · External reference
Unresolved reference
2013 · External reference
Review of state-of-charge estimation methods for electric vehicle applications
10.3390/wevj16020087 · 2025 · External reference
A hybrid machine learning model for range estimation of electric vehicles
2016 · External reference
Electric vehicle range estimation using regression techniques
10.3390/wevj13060105 · 2022 · External reference
Remaining driving range prediction for electric vehicles: key challenges and outlook
10.1049/cth2.12486 · 2023 · External reference
Analysis of the electric bus autonomy depending on the atmospheric conditions
10.3390/en12234535 · 2019 · External reference
Unresolved reference
External reference
Unresolved reference
External reference
City buses’ future velocity prediction for multiple driving cycle: a meta supervised learning solution
10.1049/itr2.12019 · 2021 · External reference
Are we testing vehicles the right way? Challenges of electrified and connected vehicles for standard drive cycles and on-road testing
10.3390/wevj16020094 · 2025 · External reference
Risk-averse real driving emissions optimization considering stochastic influences
10.1080/0305215x.2019.1569646 · 2020 · External reference
Physics-Informed Loss Function for Robust Electric Truck Range Estimation
2025 · External reference
KY. Physics-Informed Deep Learning for Electric Vehicle Energy Consumption Prediction: A Multi-Head Neural Network Approach
2026 · External reference
A feature prediction-based method for energy consumption prediction of electric buses
10.1016/j.energy.2024.134345 · 2025 · External reference
A knowledge-enhanced modular method for predicting electric vehicle remaining driving range under cold conditions utilizing cloud-based big data
10.1007/s42154-025-00392-6 · 2025 · External reference
A review on recent advances on improving fuel economy and performance of a fuel cell hybrid electric vehicle
10.1016/j.ijhydene.2024.09.298 · 2024 · External reference
Fuel cell electric vehicles: innovations, challenges, and the path to sustainable mobility
10.1016/j.icheatmasstransfer.2026.110520 · 2026 · External reference
A critical review on the efficient cooling strategy of batteries of electric vehicles: advances, challenges, future perspectives
10.1016/j.rser.2024.114732 · 2024 · External reference
Unresolved reference
2021 · External reference
Electric vehicle air conditioning system and its optimization for extended range—a review
10.3390/wevj13110204 · 2022 · External reference
The influence factor analysis of energy consumption on all electric range of electric city bus in China
2013 · External reference
Physics-informed Transformer for end-to-end energy prediction of integrated electric vehicle thermal management under extreme ambient temperature conditions
10.1016/j.applthermaleng.2026.130776 · 2026 · External reference
Experimental and physics-informed machine learning analysis of an adaptive thermoelectric-assisted cooling system for electric and hybrid vehicle battery thermal management
10.1177/09544062261452315 · 2026 · External reference
Artificial intelligence and sustainable development: a global nonlinear analysis of the moderating roles of human capital and renewable energy
10.1016/j.rser.2025.116574 · 2026 · External reference
10.2139/ssrn.5991679
10.2139/ssrn.5991679 · External reference
Full-scene energy consumption prediction for electric vehicles: a knowledge-enhanced hybrid-driven framework
10.1016/j.energy.2025.137136 · 2025 · External reference
Energy consumption prediction for electric buses based on traction modeling and LightGBM
10.3390/wevj16030159 · 2025 · External reference
Reliable Energy Consumption Modeling for an Electric Vehicle Fleet
2022 · External reference
A data-driven framework for estimating remaining driving range in cargo electric vehicles
10.1186/s42162-026-00618-9 · 2026 · External reference
Longitudinal modeling and velocity control of autonomous electric vehicles with energy optimization using non-linear autoregressive model with exogenous inputs (NLARX) system identification method
2026 · External reference
Energy consumption prediction and analysis for electric vehicles: a hybrid approach
10.3390/en15176490 · 2022 · External reference
Electric vehicle velocity and energy consumption predictions using transformer and Markov-Chain Monte carlo
10.1109/tte.2022.3157652 · 2022 · External reference
Power-based electric vehicle energy consumption model: model development and validation
10.1016/j.apenergy.2016.01.097 · 2016 · External reference
Predicting electric vehicle energy consumption using machine learning: a comparative study of regression and neural network approaches on large-scale real-world data
2026 · External reference
Energy consumption prediction for an electric vehicle using machine learning: a comparative study of regression, ensemble, and LSTM-based models
10.3390/vehicles8050099 · 2026 · External reference
Energy management of a dual battery energy storage system for electric vehicular application
10.1016/j.compeleceng.2024.109099 · 2024 · External reference
Energy consumption prediction strategy for electric vehicle based on LSTM-transformer framework
10.1016/j.energy.2024.131780 · 2024 · External reference
Electric vehicles’ energy consumption estimation with real driving condition data
10.1016/j.trd.2015.10.010 · 2015 · External reference
Convolutional neural network–bagged decision tree: a hybrid approach to reduce electric vehicle’s driver’s range anxiety by estimating energy consumption in real-time
10.1007/s00500-020-05310-y · 2021 · External reference
Future automotive architecture and the impact of IT trends
10.1109/ms.2017.69 · 2017 · External reference
Robustifying the deployment of tinyML models for autonomous mini-vehicles
10.3390/s21041339 · 2021 · External reference
Real-time performance-focused localization techniques for autonomous vehicle: a review
10.1109/tits.2021.3077800 · 2022 · External reference
Reliability challenges for electric vehicles: from devices to architecture and systems software
2013 · External reference
A comprehensive review of model compression techniques in machine learning
10.1007/s10489-024-05747-w · 2024 · External reference
Performance and robustness of tree-based models, neural networks, and ordinal regression in learning-to-rank systems
2026 · External reference
Enable deep learning on mobile devices: methods, systems, and applications
10.1145/3486618 · 2022 · External reference
Unresolved reference
2001 · External reference
Unresolved reference
2012 · External reference
Unresolved reference
2024 · External reference
Statistical comparisons of classifiers over multiple data sets
2006 · External reference
Convolutional neural network–bagged decision tree: a hybrid approach to reduce electric vehicle’s driver’s range anxiety by estimating energy consumption in real-time
10.1007/s00500-020-05310-y · ExternalCitation · doi-reference
A comprehensive review of model compression techniques in machine learning
10.1007/s10489-024-05747-w · ExternalCitation · doi-reference
Global drive toward net-zero emissions and sustainability via electric vehicles: an integrative critical review
10.1007/s40974-024-00351-7 · ExternalCitation · doi-reference
Holistic sensitivity analysis for long-term energy demand prediction of battery electric vehicles
10.1007/s42154-024-00292-1 · ExternalCitation · doi-reference
A knowledge-enhanced modular method for predicting electric vehicle remaining driving range under cold conditions utilizing cloud-based big data
10.1007/s42154-025-00392-6 · ExternalCitation · doi-reference
Power-based electric vehicle energy consumption model: model development and validation
10.1016/j.apenergy.2016.01.097 · ExternalCitation · doi-reference
Energy consumption analysis and prediction of electric vehicles based on real-world driving data
10.1016/j.apenergy.2020.115408 · ExternalCitation · doi-reference
Physics-informed Transformer for end-to-end energy prediction of integrated electric vehicle thermal management under extreme ambient temperature conditions
10.1016/j.applthermaleng.2026.130776 · ExternalCitation · doi-reference
Energy management of a dual battery energy storage system for electric vehicular application
10.1016/j.compeleceng.2024.109099 · ExternalCitation · doi-reference
Energy consumption prediction strategy for electric vehicle based on LSTM-transformer framework
10.1016/j.energy.2024.131780 · ExternalCitation · doi-reference
A feature prediction-based method for energy consumption prediction of electric buses
10.1016/j.energy.2024.134345 · ExternalCitation · doi-reference
Full-scene energy consumption prediction for electric vehicles: a knowledge-enhanced hybrid-driven framework
10.1016/j.energy.2025.137136 · ExternalCitation · doi-reference
A novel data-driven framework for driving range prognostics in electric vehicles
10.1016/j.engappai.2024.109925 · ExternalCitation · doi-reference
Fuel cell electric vehicles: innovations, challenges, and the path to sustainable mobility
10.1016/j.icheatmasstransfer.2026.110520 · ExternalCitation · doi-reference
A review on recent advances on improving fuel economy and performance of a fuel cell hybrid electric vehicle
10.1016/j.ijhydene.2024.09.298 · ExternalCitation · doi-reference
A critical review on the efficient cooling strategy of batteries of electric vehicles: advances, challenges, future perspectives
10.1016/j.rser.2024.114732 · ExternalCitation · doi-reference
Artificial intelligence and sustainable development: a global nonlinear analysis of the moderating roles of human capital and renewable energy
10.1016/j.rser.2025.116574 · ExternalCitation · doi-reference
Electric vehicles’ energy consumption estimation with real driving condition data
10.1016/j.trd.2015.10.010 · ExternalCitation · doi-reference
Energy consumption effects of speed and acceleration in electric vehicles: laboratory case studies and implications for drivers and policymakers
10.1016/j.trd.2017.04.020 · ExternalCitation · doi-reference
Influence of driving style, infrastructure, weather and traffic on electric vehicle performance
10.1016/j.trd.2020.102569 · ExternalCitation · doi-reference
Remaining driving range prediction for electric vehicles: key challenges and outlook
10.1049/cth2.12486 · ExternalCitation · doi-reference
Driver alerting system using range estimation of electric vehicles in real time under dynamically varying environmental conditions
10.1049/iet-est.2014.0067 · ExternalCitation · doi-reference
Accurate range estimation for an electric vehicle including changing environmental conditions and traction system efficiency
10.1049/iet-est.2015.0052 · ExternalCitation · doi-reference
City buses’ future velocity prediction for multiple driving cycle: a meta supervised learning solution
10.1049/itr2.12019 · ExternalCitation · doi-reference
Risk-averse real driving emissions optimization considering stochastic influences
10.1080/0305215x.2019.1569646 · ExternalCitation · doi-reference
Mathematical modeling of driving forces of an electric vehicle for sustainable operation
10.1109/access.2023.3309728 · ExternalCitation · doi-reference
Future automotive architecture and the impact of IT trends
10.1109/ms.2017.69 · ExternalCitation · doi-reference
Real-time performance-focused localization techniques for autonomous vehicle: a review
10.1109/tits.2021.3077800 · ExternalCitation · doi-reference
Electric vehicle velocity and energy consumption predictions using transformer and Markov-Chain Monte carlo
10.1109/tte.2022.3157652 · ExternalCitation · doi-reference
Predicting electric vehicle energy consumption from field data using machine learning
10.1109/tte.2024.3416532 · ExternalCitation · doi-reference
Enable deep learning on mobile devices: methods, systems, and applications
10.1145/3486618 · ExternalCitation · doi-reference
Experimental and physics-informed machine learning analysis of an adaptive thermoelectric-assisted cooling system for electric and hybrid vehicle battery thermal management
10.1177/09544062261452315 · ExternalCitation · doi-reference
A data-driven framework for estimating remaining driving range in cargo electric vehicles
10.1186/s42162-026-00618-9 · ExternalCitation · doi-reference
10.2139/ssrn.5069182
10.2139/ssrn.5069182 · ExternalCitation · doi-reference
10.2139/ssrn.5991679
10.2139/ssrn.5991679 · ExternalCitation · doi-reference
A comprehensive study on the expansion of electric vehicles in Europe
10.3390/app122211656 · ExternalCitation · doi-reference
Analysis of the electric bus autonomy depending on the atmospheric conditions
10.3390/en12234535 · ExternalCitation · doi-reference
Energy consumption prediction and analysis for electric vehicles: a hybrid approach
10.3390/en15176490 · ExternalCitation · doi-reference
Energy modeling for electric vehicles based on real driving cycles: an artificial intelligence approach for microscale analyses
10.3390/en17051148 · ExternalCitation · doi-reference
Vehicle acceleration and speed as factors determining energy consumption in electric vehicles
10.3390/en17164051 · ExternalCitation · doi-reference
Robustifying the deployment of tinyML models for autonomous mini-vehicles
10.3390/s21041339 · ExternalCitation · doi-reference
Energy consumption prediction for an electric vehicle using machine learning: a comparative study of regression, ensemble, and LSTM-based models
10.3390/vehicles8050099 · ExternalCitation · doi-reference
Development of hybrid vehicle energy consumption model for transportation applications—Part II: traction force-speed based energy consumption modeling
10.3390/wevj10020022 · ExternalCitation · doi-reference
Electric vehicle range estimation using regression techniques
10.3390/wevj13060105 · ExternalCitation · doi-reference
Electric vehicle air conditioning system and its optimization for extended range—a review
10.3390/wevj13110204 · ExternalCitation · doi-reference
Electric vehicle adoption: a comprehensive systematic review of technological, environmental, organizational and policy impacts
10.3390/wevj15080375 · ExternalCitation · doi-reference
Review of state-of-charge estimation methods for electric vehicle applications
10.3390/wevj16020087 · ExternalCitation · doi-reference
Are we testing vehicles the right way? Challenges of electrified and connected vehicles for standard drive cycles and on-road testing
10.3390/wevj16020094 · ExternalCitation · doi-reference
Energy consumption prediction for electric buses based on traction modeling and LightGBM
10.3390/wevj16030159 · ExternalCitation · doi-reference
Electric vehicle energy consumption modelling and prediction based on road information
10.3390/wevj7030447 · ExternalCitation · doi-reference
Evaluating the energy consumption of an electric vehicle under real-world driving conditions
10.4271/2022-01-1127 · ExternalCitation · doi-reference
