A review of reinforcement learning based energy management systems for electrified powertrains: Progress, challenge, and potential solution

AH Ganesh, B Xu - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
The impact of internal combustion engine-powered automobiles on climate change due to
emissions and the depletion of fossil fuels has contributed to the progress of electrified …

[HTML][HTML] Review of optimal sizing and power management strategies for fuel cell/battery/super capacitor hybrid electric vehicles

AS Mohammed, SM Atnaw, AO Salau, JN Eneh - Energy Reports, 2023 - Elsevier
Energy management strategies and optimal power source sizing for fuel cell/battery/super
capacitor hybrid electric vehicles (HEVs) are critical for power splitting and cost-effective …

[HTML][HTML] A comprehensive review on energy storage in hybrid electric vehicle

S Verma, S Mishra, A Gaur, S Chowdhury… - Journal of Traffic and …, 2021 - Elsevier
The sharp inclination in the emissions from conventional vehicles contribute to a significant
increase in environmental issues, besides the energy crises and low conversion efficiency …

[HTML][HTML] Digital twin of electric vehicle battery systems: Comprehensive review of the use cases, requirements, and platforms

F Naseri, S Gil, C Barbu, E Çetkin, G Yarimca… - … and Sustainable Energy …, 2023 - Elsevier
Transportation electrification has been fueled by recent advancements in the technology
and manufacturing of battery systems, but the industry yet is facing serious challenges that …

[HTML][HTML] One-shot battery degradation trajectory prediction with deep learning

W Li, N Sengupta, P Dechent, D Howey… - Journal of Power …, 2021 - Elsevier
The degradation of batteries is complex and dependent on several internal mechanisms.
Variations arising from manufacturing uncertainties and real-world operating conditions …

[HTML][HTML] Data-driven systematic parameter identification of an electrochemical model for lithium-ion batteries with artificial intelligence

W Li, I Demir, D Cao, D Jöst, F Ringbeck… - Energy Storage …, 2022 - Elsevier
Electrochemical models are more and more widely applied in battery diagnostics,
prognostics and fast charging control, considering their high fidelity, high extrapolability and …

Deep reinforcement learning based energy management strategies for electrified vehicles: Recent advances and perspectives

H He, X Meng, Y Wang, A Khajepour, X An… - … and Sustainable Energy …, 2024 - Elsevier
Electrified vehicles provide an effective solution to address the unfavorable impacts of fossil
fuel use in the transportation sector. Energy management strategy (EMS) is the core …

Optimization of energy management strategy for extended range electric vehicles using multi-island genetic algorithm

Y Xu, H Zhang, Y Yang, J Zhang, F Yang, D Yan… - Journal of Energy …, 2023 - Elsevier
This study aims to improve the fuel economy of extended range electric vehicles (EREVs)
and reduce the cumulative battery workload. Energy management strategy (EMS) of EREVs …

Physics-informed neural networks for electrode-level state estimation in lithium-ion batteries

W Li, J Zhang, F Ringbeck, D Jöst, L Zhang, Z Wei… - Journal of Power …, 2021 - Elsevier
An accurate estimation of the internal states of lithium-ion batteries is critical to improving the
reliability and durability of battery systems. Data-driven methods have exhibited enormous …

Critical review of intelligent battery systems: Challenges, implementation, and potential for electric vehicles

L Komsiyska, T Buchberger, S Diehl, M Ehrensberger… - Energies, 2021 - mdpi.com
This review provides an overview of new strategies to address the current challenges of
automotive battery systems: Intelligent Battery Systems. They have the potential to make …