汽车工程

基于流场偏差分析的燃料电池空压机优化设计

  • 邵高鹏 ,
  • 张扬军
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  • 清华大学 汽车工程系, 北京 100084

收稿日期: 2018-08-15

  网络出版日期: 2019-06-01

基金资助

国家重点研发项目(SQ2018YFB010481)

Optimization design of a fuel cell air compressor based on a flow field deviation analysis

  • SHAO Gaopeng ,
  • ZHANG Yangjun
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  • Department of Automotive Engineering, Tsinghua University, Beijing 100084, China

Received date: 2018-08-15

  Online published: 2019-06-01

摘要

燃料电池汽车是新能源汽车发展的重要方向。离心空压机具有效率高、响应快等优点,是当前车用燃料电池空压机研发的重点。非设计工况性能差是离心空压机设计面临的主要难点。该文提出了流场偏差分析的方法,对比研究了离心空压机在非设计工况和设计工况下内部的三维流动,揭示了在非设计工况下主叶片吸力面上出现大尺度的流动分离导致非设计工况性能下降的重要因素。提出了以非设计工况和设计工况主叶片吸力面上的压力分布偏差作为离心空压机非设计工况性能优化的目标,利用正交试验法设计了不同的方案,对离心空压机的叶片后弯角、前掠角和扩压器长度进行了优化。实验结果表明:优化后的空压机在全工况上有2%的效率提升,在低流量工况下效率提升了5%,证明了流场偏差分析优化方法的有效性。

本文引用格式

邵高鹏 , 张扬军 . 基于流场偏差分析的燃料电池空压机优化设计[J]. 清华大学学报(自然科学版), 2019 , 59(6) : 490 -496 . DOI: 10.16511/j.cnki.qhdxxb.2019.25.001

Abstract

Fuel cell vehicles, an important class of new energy vehicles, use compressors to increase the inlet pressure into the fuel cell. The high efficiency and fast response of centrifugal compressors make them an ideal option for the compressors used in fuel cell vehicles. However, centrifugal air compressors have poor off-design performance. Flow field deviation analyses were used here to study the three-dimensional flow distributions inside a centrifugal air compressor for design and off-design conditions. The flow separation on the suction surface of the main blade for off-design conditions is shown to be the main factor leading to the poor performance. The pressure distribution change on the suction surface of the main blade between the off-design and design conditions is then used as the optimization objective to improve the centrifugal air compressor design. The analyses consider various back sweep angles, forward lean angles and vaneless diffuser lengths. The optimized air compressor efficiency is improved by 2% at the design working condition and 5% at the near-stall working condition. Thus, this optimization method using flow field deviation analyses is proven to be effective.

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