Transferable representation modelling for real-time energy management of the plug-in hybrid vehicle based on k-fold fuzzy learning and Gaussian process regression

Q Zhou, Y Li, D Zhao, J Li, H Williams, H Xu, F Yan - Applied energy, 2022 - Elsevier
Electric vehicles, including plug-in hybrids, are important for achieving net-zero emission
and will dominate road transportation in the future. Energy management, which optimizes …
被引用次数：68 相关文章

Transferable representation modelling for real-time energy management of the plug-in hybrid vehicle based on K fold fuzzy learning and Gaussian process regression

Q Zhou, Y Li, D Zhao, J Li, H Williams, H Xu… - Applied Energy, 2022 - eprints.gla.ac.uk
Electric vehicles, including plug-in hybrids, are important for achieving net-zero emission
and will dominate road transportation in the future. Energy management, which optimizes …
[PDF] bham.ac.uk

[PDF][PDF] Transferable representation modelling for real-time energy management of the plug-in hybrid vehicle based on k-fold fuzzy learning and Gaussian process …

Q Zhou, Y Li, D Zhao, J Li, H Williams, H Xu, F Yan - pure-oai.bham.ac.uk
The hybrid electric vehicle (HEV), as a mainstream ultra-low emission solution, will account
for more than 60% of the world passenger market share by 2030 according to predictions of …

Transferable representation modelling for real-time energy management of the plug-in hybrid vehicle based on k-fold fuzzy learning and Gaussian process regression

Q Zhou, Y Li, D Zhao, J Li, H Williams, H Xu, F Yan - Applied Energy, 2022 - ideas.repec.org
Electric vehicles, including plug-in hybrids, are important for achieving net-zero emission
and will dominate road transportation in the future. Energy management, which optimizes …
[PDF] birmingham.ac.uk

[PDF][PDF] Transferable representation modelling for real-time energy management of the plug-in hybrid vehicle based on k-fold fuzzy learning and Gaussian process …

Q Zhou, Y Li, D Zhao, J Li, H Williams, H Xu, F Yan - research.birmingham.ac.uk
The hybrid electric vehicle (HEV), as a mainstream ultra-low emission solution, will account
for more than 60% of the world passenger market share by 2030 according to predictions of …

Transferable representation modelling for real-time energy management of the plug-in hybrid vehicle based on k-fold fuzzy learning and Gaussian process regression

Q Zhou, Y Li, D Zhao, J Li, H Williams, H Xu… - Applied …, 2022 - ui.adsabs.harvard.edu
Electric vehicles, including plug-in hybrids, are important for achieving net-zero emission
and will dominate road transportation in the future. Energy management, which optimizes …

Transferable representation modelling for real-time energy management of the plug-in hybrid vehicle based on k-fold fuzzy learning and Gaussian process regression

Q Zhou, Y Li, D Zhao, J Li, H Williams, H Xu… - Applied …, 2022 - econpapers.repec.org
Electric vehicles, including plug-in hybrids, are important for achieving net-zero emission
and will dominate road transportation in the future. Energy management, which optimizes …
[PDF] bham.ac.uk

[PDF][PDF] Transferable representation modelling for real-time energy management of the plug-in hybrid vehicle based on k-fold fuzzy learning and Gaussian process …

Q Zhou, Y Li, D Zhao, J Li, H Williams, H Xu, F Yan - pure-oai.bham.ac.uk
The hybrid electric vehicle (HEV), as a mainstream ultra-low emission solution, will account
for more than 60% of the world passenger market share by 2030 according to predictions of …

Transferable representation modelling for real-time energy management of the plug-in hybrid vehicle based on k-fold fuzzy learning and Gaussian process regression

Q Zhou, Y Li, D Zhao, J Li, H Williams… - Applied …, 2022 - research.birmingham.ac.uk
Electric vehicles, including plug-in hybrids, are important for achieving net-zero emission
and will dominate road transportation in the future. Energy management, which optimizes …

[引用][C] Transferable representation modelling for real-time energy management of the plug-in hybrid vehicle based on k-fold fuzzy learning and Gaussian process …

Q Zhou, Y Li, D Zhao, J Li, H Williams, H Xu, F Yan - 2022