المؤلفون: Qiang, Song, Ping, Zhao

المصدر: 2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), 2017 IEEE 2nd. :2256-2260 Mar, 2017

Relation: 2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

المؤلفون: Huijun Yue, Jinyu Lin, Peng Dong, Zhinan Chen, Xiangyang Xu

المصدر: Energies, Vol 16, Iss 2, p 725 (2023)

مصطلحات موضوعية: HEV, hybrid powertrain system, configuration comparison and optimization, energy management strategy, dynamic coordinated control strategy, Technology

وصف الملف: electronic resource

Relation: https://www.mdpi.com/1996-1073/16/2/725; https://doaj.org/toc/1996-1073

URL الوصول: https://doaj.org/article/9d1346a4c782401081e1ff0a549912bf

المؤلفون: Peng Hao, Hongyu Zhu, Chen Wang, Huijun Cheng, Haisheng Yu

المصدر: Jixie chuandong, Vol 44, Pp 118-124 (2020)

مصطلحات موضوعية: Power-split, Hybrid powertrain system, Constraint matrix, Acceleration performance, Mechanical engineering and machinery, TJ1-1570

وصف الملف: electronic resource

Relation: http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2020.12.019; https://doaj.org/toc/1004-2539

URL الوصول: https://doaj.org/article/fa340c352376490c894118048ea8ba29

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المؤلفون: Zou, Yuan^Aff5, Li, Junqiu^Aff6, Hu, Xiaosong^Aff7, Chamaillard, Yann^Aff8

المساهمون: Zou, Yuan^Aff1, Li, Junqiu^Aff2, Hu, Xiaosong^Aff3, Chamaillard, Yann^Aff4

المصدر: Modeling and Control of Hybrid Propulsion System for Ground Vehicles. :53-97

المؤلفون: Lihua Wang, Yahui Cui, Fengqi Zhang, Guanglei Li

المصدر: Energies, Vol 13, Iss 2, p 329 (2020)

مصطلحات موضوعية: hybrid electric vehicle, planetary hybrid powertrain system, configuration, classification, comparison, Technology

وصف الملف: electronic resource

Relation: https://www.mdpi.com/1996-1073/13/2/329; https://doaj.org/toc/1996-1073

URL الوصول: https://doaj.org/article/9970870e2a014dc3800e0e57568ced0b

المؤلفون: Kitanović, Marko

المساهمون: Popović, Slobodan, Miljić, Nenad, Knežević, Dragan, Mrđa, Predrag, Dorić, Jovan

المصدر: Универзитет у Београду

مصطلحات موضوعية: hybrid powertrain systems, dynamic programming, optimization, control, energy efficfficciency, Great scientific and engineering effoorts are being invested in improving the fuel economy and emission performance standards of powertrain systems amid ever-increasing legislative pressure. Hybrid powertrain systems, comprising a conventional internal combustion engine and an additional prime mover and its corresponding energy storage system, offeffoer great opportunities for fuel economy improvements. However, functional and control parameters optimization is of crucial importance in order to achieve the full extent of potential improvements. The subject of this dissertation is experimental and theoretical investigation into the ficeld of optimization of a hydraulic hybrid powertrain system intended for the propulsion of a transit bus. TheTheese hybrid propulsion solutions employ hydro-pneumatic accumulators for energy storage, which are characterized by low specific energy values. Because of this, it is of crucial importance to carefully choose the accumulator parameters in order to harness the maximum amount of regenerative braking energy during the deceleration phases that will yield the greatest fuel economy improvement. A comprehensive simulation model of a hydraulic hybrid powertrain system has been devised, which has allowed for the determination of the influfluuence of elastomeric foam mass, preload pressure and accumulator capacity on the resulting powertrain system efficfficciency and the potential fuel savings. For maximizing the achievable fuel savings, a neural network-based control algorithm trained using the optimal control trajectories derived using Dynamic Programming has been investigated. By applying the functional and optimal control optimizations presented in this dissertation, average fuel savings of 23.9% have been achieved in direction 1 of the transit bus driving cycle and 25.5% in direction 2. TheTheese ficgures represent 83.7% and 79.8% of the fuel economy improvements obtained using the unimplementable Dynamic Programming algorithm, respectively

وصف الملف: application/pdf

URL الوصول: https://explore.openaire.eu/search/publication?articleId=nardusnacion::9f7c0995b82bf76e40ed5b562d18e160
https://nardus.mpn.gov.rs/handle/123456789/18616

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