基于QAR数据的航空发动机热力学模型构建方法

马超; 赵树杰; 徐建新; 巴翔

doi:10.13224/j.cnki.jasp.20220101

基于QAR数据的航空发动机热力学模型构建方法

doi: 10.13224/j.cnki.jasp.20220101

马超^1,,
赵树杰^1,*, ,,
徐建新¹,
巴翔²

1.
中国民航大学航空工程学院，天津 300300
2.
中国南方航空股份有限公司河南分公司，郑州 450000

基金项目: 中央高校基本科研业务费项目（3122019085）

详细信息

作者简介:
马超（1985-），男，副教授，博士，主要从事基于数据的民机运行与支持、飞行器空气动力学研究

通讯作者:
赵树杰（1996-），男，硕士，主要从事航空发动机故障诊断研究。E-mail：254202828@qq.com

中图分类号: V231.1⁺1
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- 文章访问数: 209
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- 被引次数: 0
出版历程
- 收稿日期: 2022-03-03
- 网络出版日期: 2023-04-11

Construction method of aero-engine thermodynamic model based on QAR data

MA Chao^1
,,
ZHAO Shujie^{1,*
, ,},
XU Jianxin¹,
BA Xiang²

1.
College of Aeronautical Engineering，Civil Aviation University of China，Tianjin 300300，China
2.
Henan Branch，China Southern Airlines Company Limited，Zhengzhou 450000，China

摘要

摘要:
为了能够建立更加接近真实运行环境的航空发动机热力学模型，提出了一种依据航空发动机运行QAR（quick access recorder）数据的热力学模型构建方法。依据发动机传统设计点热力学方程，利用最小二乘辨识原理，修正25站位压强求解方程，获得干空气热力学模型；根据混合气体熵值的可加性，构建了降雨工况下的湿空气热力学模型；最后结合遗传算法优化的粒子群算法，依据QAR数据进行干空气和湿空气热力学模型参数计算与验证。结果表明该热力学模型计算得到的干空气和湿空气热力学参数与QAR数据间最大误差小于13%，较为接近实际绝热参数。证实了基于QAR数据构建发动机热力学模型的可行性和该热力学模型构建方法求解热力参数的有效性。
- 热力学模型 /
- QAR数据 /
- 最小二乘辨识 /
- 粒子群 /
- 遗传算法
Abstract:
In order to establish a thermodynamic model of aero-engine in an approximate real operating environment, a thermodynamic model construction method based on QAR (quick access recorder) data of aero-engine operation was proposed. According to the thermodynamic equation of the traditional design point of the engine, and using the least square identification principle, the equation for solving the pressure at the 25 station was corrected, and the dry air thermodynamic model was obtained; according to the additivity of the entropy value of the mixed gas, a thermodynamic model of wet air under rainfall conditions was constructed; finally, combined with particle swarm optimization optimized by genetic algorithm, the parameters of dry air and wet air thermodynamic model were calculated and verified according to QAR data. The results showed that the maximum error between the dry air and wet air thermodynamic parameters calculated by the thermodynamic model and the QAR data was less than 13%, which was closer to the actual adiabatic parameters. The feasibility of constructing a thermodynamic model of an engine based on QAR data and the effectiveness of the thermodynamic model construction method for solving thermodynamic parameters were proved.
- thermodynamic model /
- QAR data /
- least square identification /
- particle swarm optimization /
- genetic algorithm

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图 1 涡轮冷却气流流动示意

Figure 1. Schematic diagram of the flow of the turbine cooling airflow

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图 2 低压压气机出口总压和高压压气机进口总压

Figure 2. Total pressure at the outlet of the low pressure compressor and the total pressure at the inlet of the high pressure compressor

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图 3 ${p_{{{{\text{25}}}}^\prime }}$与${p_{{{25}}^{\prime \prime } }}$相关性

Figure 3. Correlation between ${p_{{{{\text{25}}}}^\prime }}$ and ${p_{{{25}}^{\prime \prime } }}$

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图 4 同一台发动机不同航班${p_{{{{\text{25}}}}^{\prime \prime } }}$定熵和辨识计算结果对比

Figure 4. Comparison of ${p_{{{{\text{25}}}}^{\prime \prime }}}$ constant entropy and identification calculation results of different flight on the same engine

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图 5 PSO-GA算法结构流程图

Figure 5. PSO-GA algorithm structure flow chart

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图 6 PSO-GA适应度函数值

Figure 6. PSO-GA fitness function value

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图 7 建模流程图

Figure 7. Modeling flowchart

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表 1 CFM56-7B发动机站位信息

Table 1. CFM56-7B engine station information

站位序号	站位名	站位序号	站位名
0	发动机远前方	12	风扇进口
25′	低压压气机出口	25″	高压压气机进口
30	高压压气机出口	40	燃烧室出口
40′	高压涡轮进口	45	高压涡轮出口
45′	低压涡轮进口	50	低压涡轮出口

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表 2 QAR记录热力参数

Table 2. QAR records thermal parameters

参数	变量符号
风扇进口温度/K	$ {T_{12}} $
风扇进口压强/Pa	${p_{12} }$
高压压气机进口温度/K	$ {T_{25}} $
高压压气机出口温度/K	$ {T_{30}} $
高压压气机出口压强/Pa	${p_{30} }$
燃油流量/（$ {\text{kg}}/{\text{s}} $）	$q_{m,{\rm{f}}}$
尾喷口温度/K	$ {T_{50}} $

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表 3 辨识方程系数

Table 3. Identification equation coefficients

模型阶数	${p_{ {{{\text{25} } } }^{\prime \prime }}}$系数	${p_{ {{{\text{25} } } }^\prime}}$系数
$ k - 1 $	2.8628	0.4244
$ k - 2 $	−4.5039	−0.5258
$ k - 3 $	5.1570	0.1169
$ k - 4 $	−4.4539	0
$ k - 5 $	2.9498	0
$ k - 6 $	−1.3913	0
$ k - 7 $	0.3557	0

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表 4 数据截取条件

Table 4. Data interception conditions

参数名称	截取条件
相对转速/%	>90
燃油流量/$ （{\text{kg} }/{\text{s} } ） $	>0.252
空地状态	AIR
油门杆角度/（°）	>70
油门杆角度稳定时间/s	>10
高度/m	<1500

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表 5 热力参数计算结果与QAR数据对比

Table 5. Comparison of thermal parameter calculation results with QAR data

时刻	热力参数	PSO-GA 计算数据	QAR记录原始数据	相对误差/%
1	T₂₅/K	387.58	398.768	2.81
	T₃₀/K	767.90	811.22	5.34
	p₃₀/Pa	1964952	2247770	12.58
2	T₂₅/K	384.47	397.90	3.38
	T₃₀/K	758.58	813.04	6.70
	p₃₀/Pa	1985821.06	2233980	11.11
3	T₂₅/K	404.98	392.78	3.01
	T₃₀/K	741.20	809.05	8.39
	p₃₀/Pa	1862370	2096080	11.15

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表 6 燃烧室及涡轮部件计算参数

Table 6. Calculation parameters of combustor and turbine components

时刻	热力参数	PSO-GA计算数据
1	T₄₀/K	1709.21
	${T_{{{40} }^\prime}}$/K	1661.44
	p₅₀/Pa	73648.43
	${q_{m,\text{a} } }$/$ （\text{kg}/{\text{s} }） $	28.18
	f	0.0330
2	T₄₀/K	1686.67
	${T_{{{40} }^\prime }}$/K	1639.69
	p₅₀/Pa	65817.25
	${q_{m,\text{a} } }$/$ （\text{kg}/{\text{s} }） $	58.73
	f	0.0247
3	T₄₀/K	1752.18
	${T_{{{40} }^\prime}}$/K	1701.83
	p₅₀/Pa	60030.30
	${q_{m,\text{a} } }$/$ （\text{kg}/{\text{s} }） $	50.82
	f	0.0581

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表 7 湿空气热力学模型热力参数计算结果与QAR数据对比

Table 7. Comparing the calculation results of thermodynamic parameters of wet air thermodynamic model with QAR data

时刻	热力参数/K	PSO-GA 计算数据	QAR记录原始数据	相对误差/%
1	T₂₅	387	379.36	2.01
1	T₃₀	757	773.51	2.13
2	T₂₅	374	374.14	0.03
2	T₃₀	774	767.15	0.89
3	T₂₅	366	387.20	5.47
3	T₃₀	749	803.14	6.74

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表 8 湿空气热力学模型燃烧室及涡轮部件计算参数

Table 8. Calculation parameters of combustor and turbine components of wet air thermodynamic model

时刻	热力参数	PSO-GA计算数据
1	${D_{ { {25} }^{\prime \prime } } }/ （{\text{kg} }/{\text{kg} } ） $	0.0262
	${\varphi _{{{25} }^{\prime \prime }}}$/%	0.3263
	D₃₀/$ （\text{kg}/{\text{kg} }） $	0.3762
	$ {\varphi _{30}} $/%	0.0011
	${p_{ {{{\text{25} } } }^{\prime \prime }}}$/Pa	146895
	T₄₀/K	1667
	${T_{{{40} }^\prime }}$/K	1616
	P₅₀/Pa	68116
	${q_{ {m,\text{wet} } } }/ （\text{kg}/{\text{s} }） $	36
	f	0.0206
2	${D_{{{25} }^{\prime \prime }}}$/$ （\text{kg}/{\text{kg} }） $	0.0472
	${\varphi _{{{25} }^{\prime \prime }}}$/%	0.5363
	D₃₀/$ （\text{kg}/{\text{kg} }） $	0.1044
	$ {\varphi _{30}} $/%	0.1086
	${p_{ {{{\text{25} } } }^{\prime \prime } }}$/Pa	164219
	T₄₀/K	1548
	${T_{{{40} }^\prime }}$/K	1502
	p₅₀/Pa	74369
	${q_{ {m,\text{wet} } } }/ （\text{kg}/{\text{s} }） $	39
	f	0.0321
3	${D_{{{25} }^{\prime \prime } }}$/$ （\text{kg}/{\text{kg} }） $	0.0028
	${\varphi _{{{25} }^{\prime \prime } }}$/%	0.5460
	D₃₀/$ （\text{kg}/{\text{kg} }） $	0.0287
	$ {\varphi _{30}} $/%	0.1590
	${p_{ { { {\text{25} } } }^{\prime \prime } } }$/Pa	144000
	T₄₀/K	1601
	${T_{{{40} }^\prime}}$/K	1557
	p₅₀/Pa	64222
	${q_{ {m,\text{wet} } } }$/$ （\text{kg}/{\text{s} }） $	34
	f	0.0315

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