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Fuel consumption potential of different external combustion gas- turbine thermodynamic configurations for extended range electric vehicles

机译:扩展范围电动汽车的不同外燃式燃气轮机热力学配置的油耗潜力

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摘要

External combustion gas-turbine (ECGT) systems are among potential multi-fuel energy converters to substitute the internal combustion engine (ICE) as auxiliary power unit (APU) in future extended range hybrid electric vehicle (EREV) powertrains. Fuel consumption of these APUs in EREV strongly relies on the energy converter efficiency and power to weight ratio as well as on the energy management strategy deployed on-board. This paper presents a technological analysis and investigates the potential of fuel consumption savings of an EREV using different ECGT-system thermodynamic configurations. These include a simple ECGT (S-ECGT), a downstream simple ECGT (DS-ECGT), a downstream intercooled ECGT (DS-ECGT) and a downstream intercooled reheat ECGT (DIRe-ECGT). An energetic and technological analysis is conducted to identify the systems' efficiency and power to weight ratio for different operating temperatures. An EREV model is developed and the different ECGT-system configurations are integrated as APUs. A bi-level optimization method is proposed to optimize the powertrain. It consists of coupling the non-dominated sorting genetic algorithm (NSGA) to the dynamic programing (DP) in order to minimize the fuel consumption and the number of switching On/Off of the APU, which impacts its durability. Fuel consumption simulations are performed on the worldwide-harmonized light vehicles test cycle (WLTC). Results show that the DIRe-ECGT-APU presents an improved fuel consumption compared to the other investigated ECGT-systems and a good potential for implementation in EREVs. (C) 2019 Elsevier Ltd. All rights reserved.
机译:外部燃气轮机(ECGT)系统属于潜在的多燃料能源转换器,可在未来的扩展范围混合动力电动汽车(EREV)动力总成中替代内燃机(ICE)作为辅助动力装置(APU)。 EREV中这些APU的燃料消耗在很大程度上取决于能量转换器的效率和功率重量比,以及船上部署的能量管理策略。本文介绍了一项技术分析,并研究了使用不同ECGT系统热力学配置的EREV节省燃油的潜力。这些包括简单的ECGT(S-ECGT),下游的简单ECGT(DS-ECGT),下游的中冷ECGT(DS-ECGT)和下游的中冷再热ECGT(DIRe-ECGT)。进行了一次充满活力的技术分析,以识别系统在不同工作温度下的效率和功率重量比。开发了EREV模型,并将不同的ECGT系统配置集成为APU。提出了一种双层优化方法来优化动力总成。它包括将非控制性排序遗传算法(NSGA)与动态编程(DP)耦合在一起,以最大程度地减少燃料消耗和APU的开/关次数,从而影响其耐用性。油耗模拟是在全球范围内协调的轻型车辆测试周期(WLTC)上进行的。结果表明,与其他研究过的ECGT系统相比,DIRe-ECGT-APU的燃油消耗有所改善,并且在EREV中具有良好的实施潜力。 (C)2019 Elsevier Ltd.保留所有权利。

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