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Refinado por: assunto: Physical Sciences remover Base de dados/Biblioteca: ANTE: Abstracts in New Technology & Engineering remover
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1
Performance investigation of a thermoelectric generator system applied in automobile exhaust waste heat recovery
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Performance investigation of a thermoelectric generator system applied in automobile exhaust waste heat recovery

Luo, Ding ; Sun, Zeyu ; Wang, Ruochen

Energy (Oxford), 2022-01, Vol.238, p.121816, Article 121816 [Periódico revisado por pares]

Oxford: Elsevier Ltd

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2
Experimental and numerical study of energy and thermal management system for a hydrogen fuel cell-battery hybrid electric vehicle
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Experimental and numerical study of energy and thermal management system for a hydrogen fuel cell-battery hybrid electric vehicle

Şefkat, Gürsel ; Özel, Mert Ali

Energy (Oxford), 2022-01, Vol.238, p.121794, Article 121794 [Periódico revisado por pares]

Oxford: Elsevier Ltd

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3
Design and Flux-Weakening Control of an Interior Permanent Magnet Synchronous Motor for Electric Vehicles
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Design and Flux-Weakening Control of an Interior Permanent Magnet Synchronous Motor for Electric Vehicles

Yue Zhang ; Wenping Cao ; McLoone, Sean ; Morrow, John

IEEE transactions on applied superconductivity, 2016-10, Vol.26 (7), p.1-6 [Periódico revisado por pares]

New York: IEEE

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4
Hybrid electric vehicle electric motors for optimum energy efficiency: A computationally efficient design
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Hybrid electric vehicle electric motors for optimum energy efficiency: A computationally efficient design

Wei, Dong ; He, Hongwen ; Cao, Jianfei

Energy (Oxford), 2020-07, Vol.203, p.117779, Article 117779 [Periódico revisado por pares]

Oxford: Elsevier Ltd

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5
A combinatorial optimisation approach to energy management strategy for a hybrid fuel cell vehicle
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A combinatorial optimisation approach to energy management strategy for a hybrid fuel cell vehicle

Caux, Stéphane ; Gaoua, Yacine ; Lopez, Pierre

Energy (Oxford), 2017-08, Vol.133, p.219-230 [Periódico revisado por pares]

Oxford: Elsevier Ltd

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6
Fuel saving and lower pollutants emissions using an ethanol-fueled engine in a hydraulic hybrid passengers vehicle
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Fuel saving and lower pollutants emissions using an ethanol-fueled engine in a hydraulic hybrid passengers vehicle

Barbosa, Társis Prado ; Eckert, Jony Javorski ; Roso, Vinícius Rückert ; Pujatti, Fabrício José Pacheco ; da Silva, Leonardo Adolpho Rodrigues ; Horta Gutiérrez, Juan Carlos

Energy (Oxford), 2021-11, Vol.235, p.121361, Article 121361 [Periódico revisado por pares]

Oxford: Elsevier Ltd

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7
Markov velocity predictor and radial basis function neural network-based real-time energy management strategy for plug-in hybrid electric vehicles
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Markov velocity predictor and radial basis function neural network-based real-time energy management strategy for plug-in hybrid electric vehicles

Liu, Hui ; Li, Xunming ; Wang, Weida ; Han, Lijin ; Xiang, Changle

Energy (Oxford), 2018-06, Vol.152, p.427-444 [Periódico revisado por pares]

Oxford: Elsevier Ltd

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8
Fuel consumption model optimization based on transient correction
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Fuel consumption model optimization based on transient correction

Guang, Hao ; Jin, Hui

Energy (Oxford), 2019-02, Vol.169, p.508-514 [Periódico revisado por pares]

Oxford: Elsevier Ltd

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9
Influence of tumble and TKE on combustion, fuel economy, and emissions of a single cylinder motorcycle engine
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Influence of tumble and TKE on combustion, fuel economy, and emissions of a single cylinder motorcycle engine

Lee, Cho-Yu ; Tu, Lih-Fu

International journal of engine research, 2023-04, Vol.24 (4), p.1400-1413 [Periódico revisado por pares]

London, England: SAGE Publications

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10
Energy harvesting approach to utilize the dissipated energy during hydraulic active suspension operation with comfort oriented control scheme
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Energy harvesting approach to utilize the dissipated energy during hydraulic active suspension operation with comfort oriented control scheme

Sathishkumar, P. ; Wang, Ruochen ; Yang, Lin ; Thiyagarajan, J.

Energy (Oxford), 2021-06, Vol.224, p.120124, Article 120124 [Periódico revisado por pares]

Oxford: Elsevier Ltd

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