Parametric study of a turbocompound diesel engine based on an analytical model
Parametric study of a turbocompound diesel engine based on an analytical model
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基于解析模型的涡轮复合柴油机参数研究
DOI：
10.1016/j.energy.2016.09.029
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发表时间：
2016-11
期刊：
影响因子：
9
通讯作者：
Zhen Chen
中科院分区：
文献类型：
--
作者：
Rongchao Zhao;Weilin Zhuge;Yangjun Zhang;Yong Yin;Yanting Zhao;Zhen Chen
涡轮复合是回收发动机尾气余热、减少二氧化碳排放的重要技术。本文提出了一种基于解析模型的涡轮复合柴油机参数化研究方法。建立了分析模型，研究了系统参数对发动机燃油消耗的影响。该模型基于热力学知识和经验模型，可以独立考虑各参数的影响。研究了涡轮效率、背压、排气温度、压比和发动机转速对回收能量、泵送损失和发动机燃油减量的影响。结果表明，涡轮效率、排气温度和背压对燃油减量和最佳动力涡轮（PT）膨胀比有较大影响。然而，发动机转速对涡轮复合的节油效果影响不大。本文介绍了PT回收功率与发动机抽油损失的相互作用机理。由于涡轮功率的非线性特性，为了获得最大的功率增益，存在一个PT膨胀比的最优值。最后，提出了高性能涡轮复合发动机的节油潜力和节油要求。
Turbocompounding is an important technique to recover waste heat from engine exhaust and reduce CO2emission. This paper presents a parametric study of turbocompound diesel engine based on analytical model.An analytical model was developed to investigate the influence of system parameters on the engine fuel consumption. The model is based on thermodynamics knowledge and empirical models, which can consider the impacts of each parameter independently. The effects of turbine efficiency, back pressure, exhaust temperature, pressure ratio and engine speed on the recovery energy, pumping loss and engine fuel reductions were studied. Results show that turbine efficiency, exhaust temperature and back pressure has great influence on the fuel reduction and optimal power turbine (PT) expansion ratio. However, engine operation speed has little impact on the fuel savings obtained by turbocompounding.The interaction mechanism between the PT recovery power and engine pumping loss is presented in the paper. Due to the nonlinear characteristic of turbine power, there is an optimum value of PT expansion ratio to achieve largest power gain. At the end, the fuel saving potential of high performance turbocompound engine and the requirements for it are proposed in the paper.
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DOI：
10.4271/2003-01-2294
发表时间：
2003-06
期刊：
--
影响因子：
--
作者：
Ulrich Hopmann;M. Algrain
通讯作者：
Ulrich Hopmann;M. Algrain
影响因子：
6.4
作者：
Rongchao Zhao;W. Zhuge;Yangjun Zhang;Yong Yin;Zhen Chen;Zhigang Li
通讯作者：
Rongchao Zhao;W. Zhuge;Yangjun Zhang;Yong Yin;Zhen Chen;Zhigang Li
影响因子：
11.2
作者：
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通讯作者：
G. Pasini;G. Lutzemberger;S. Frigo;S. Marelli;M. Ceraolo;R. Gentili;M. Capobianco
DOI：
10.1115/1.4025887
发表时间：
2013-06
影响因子：
1.5
作者：
Nicola Terdich;R. Martinez-Botas;A. Romagnoli;A. Pesiridis
通讯作者：
Nicola Terdich;R. Martinez-Botas;A. Romagnoli;A. Pesiridis
影响因子：
9
作者：
I. Briggs;G. McCullough;S. Spence;R. Douglas
通讯作者：
I. Briggs;G. McCullough;S. Spence;R. Douglas