燃料电池离心压缩机叶轮构型的参数优化及性能分析

王艺达; 刘小民; 周逸伦; 樊宏周; 陈玉辉; 张治平

doi:10.7652/xjtuxb202206019

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燃料电池离心压缩机叶轮构型的参数优化及性能分析

—————————————————————— | 更新时间：2025-04-27

- 燃料电池离心压缩机叶轮构型的参数优化及性能分析
- Performance Analysis and Multi-Parameter Optimization of Centrifugal Impeller Configuration for the Centrifugal Compressor Used in Fuel Cells
- 西安交通大学学报 2022年56卷第6期页码：164-174
- 作者机构：
  
  1. 西安交通大学能源与动力工程学院,西安,710049
  2. 珠海格力电器股份有限公司,广东,珠海,519070
- 作者简介：
  
  : 2022-01-10。作者简介: 王艺达(1997—),男,硕士生
  刘小民(通信作者),男,教授,博士生导师。基金项目: 国家重点研发计划资助项目(2019YFB1504601)
- 基金信息：
  
  : 2022-01-10。作者简介: 王艺达(1997—),男,硕士生;刘小民(通信作者),男,教授,博士生导师。基金项目: 国家重点研发计划资助项目(2019YFB1504601)
- DOI：10.7652/xjtuxb202206019
  中图分类号： O354.1
- 网络首发：2022-06-10，
  
  纸质出版：2022
- 稿件说明：
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王艺达, 刘小民, 周逸伦, 等. 燃料电池离心压缩机叶轮构型的参数优化及性能分析[J]. 西安交通大学学报, 2022,56(6):164-174.

WANG Yida, LIU Xiaomin, ZHOU Yilun, et al. Performance Analysis and Multi-Parameter Optimization of Centrifugal Impeller Configuration for the Centrifugal Compressor Used in Fuel Cells[J]. 2022, 56(6): 164-174.
王艺达, 刘小民, 周逸伦, 等. 燃料电池离心压缩机叶轮构型的参数优化及性能分析[J]. 西安交通大学学报, 2022,56(6):164-174. DOI： 10.7652/xjtuxb202206019.

WANG Yida, LIU Xiaomin, ZHOU Yilun, et al. Performance Analysis and Multi-Parameter Optimization of Centrifugal Impeller Configuration for the Centrifugal Compressor Used in Fuel Cells[J]. 2022, 56(6): 164-174. DOI： 10.7652/xjtuxb202206019.

摘要

为提升离心压缩机气动性能以满足燃料电池系统的需求

以某燃料电池离心压缩机叶轮为研究对象

选取叶轮进口倾角、叶片数、子午流道等型线控制点和叶片安装角分布控制点等关键构型参数作为优化变量

采用数值计算方法对离心压缩机叶轮气动性能进行模拟和优化。结合拉丁超立方抽样与BP神经网络拟合叶轮构型参数与气动性能的映射关系

以叶轮等熵效率最大为优化目标、总压比和功率等参数为约束

运用遗传算法对上述叶轮关键构型参数进行多参数寻优

并对优化前后叶轮的气动性能及其内部流动特性进行了对比分析。结果表明:在设计工况下

优化后叶轮等熵效率提高了3.90%

总压比为1.742

功率为8.53 kW

满足设计要求; 叶轮的稳定运行工况范围变宽

并且在整个工况范围内叶轮的等熵效率也均得到提升; 从流场分析可以发现

优化后叶轮轮盖侧高熵值区域缩小

叶片压力面及出口截面速度分布更均匀

低速气体团面积在不同流动方向上减小

叶道内流动分离得到抑制

验证了所提离心叶轮多参数优化设计方法的有效性。

Abstract

In order to improve the aerodynamic performance of the centrifugal compressor to meet the demand of the fuel cell system

this paper takes a fuel cell centrifugal compressor impeller as the study object

selects the key configuration parameters such as the impeller inlet inclination angle

number of blades

radial flow path and other profile control points and blade mounting angle distribution control points as optimization variables

then uses the numerical calculation method to simulate and optimize the aerodynamic performance of the centrifugal impeller. Based on the Latin hypercube sampling and the BP neural network

this paper mapped the relationship between the impeller configuration parameters and the aerodynamic performance

then uses the maximum isentropic efficiency of the impeller as the optimization target

and takes the total pressure ratio and power as constraints. The genetic algorithm was used to optimize the key configuration parameters of the impeller

and the aerodynamic performance and internal flow characteristics of the impeller before and after optimization were compared and analyzed. The results show that the isentropic efficiency of the optimized impeller increases by 3.90%

its total pressure ratio is 1.742

and its power is 8.53 kW under the design conditions

which satisfies the design requirements. At the same time

the range of stable operating conditions of the impeller becomes wider

and the isentropic efficiency of the impeller is also improved in the whole range of operating conditions. The flow field analysis shows that the high entropy area on the cover side of the impeller is reduced after optimization

the velocity distribution in the pressure surface and outlet section of the blade is more uniform

the area of the low-speed gas mass is reduced in multiple directions

and the flow separation in the impeller channel is suppressed. The above verifies the effectiveness of the multi-parameter optimization design method of the centrifugal impeller in this paper.

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