基于确信可靠性理论的离子电推进可靠性分配、评价与提升方法研究

doi:10.12305/j.issn.1001-506X.2026.07.18

Abstract

Abstract:

To address the issue of improving the reliability of ion electric propulsion in spacecraft ion electric propulsion systems for deep space exploration, a reliability allocation, evaluation, and improvement method based on belief reliability theory for ion electric propulsion is proposed. Firstly, carry out reliability allocation for ion electric propulsion based on technological maturity. Secondly, evaluate the task reliability of each component of ion electric propulsion with the current design. Finally, for component units that do not meet reliability requirements, measures such as increasing the failure threshold, delaying sputtering etching, and reducing electrical parameter uncertainty are taken to improve reliability. The results of the case study indicate that the method based on belief reliability theory can effectively achieve reliability allocation, evaluation, and improvement of 20 cm ion electric propulsion with given reliability requirements. The proposed method overcomes the limitations of traditional data-driven methods in scenarios with small samples, long lifetimes, and dual uncertainties, and its analysis accuracy meets the requirements of deep space exploration tasks.

Key words: ion electric propulsion, belief reliability, reliability allocation, reliability evaluation, reliability improvement

CLC Number:

V 43

Jing LI, Juanjuan CHEN, Xingmin ZHANG, Yanhui JIA. Research on reliability allocation, evaluation, and improvement method based on belief reliability theory for ion electric propulsion[J]. Systems Engineering and Electronics, 2026, 48(7): 2333-2339.

Figures/Tables 6

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Table 1

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Table 2

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References 25

26	ZHANG Q Y, KANG R, WEN M L. Decomposition method for belief reliability analysis of complex uncertain random systems[J]. IEEE Access, 2019, 7, 132711- 132719.
27	ZENG Z G, KANG R, WEN M L, et al. Uncertainty theory as a basis for belief reliability[J]. Information Sciences, 2018, 429 (1): 26- 36.
28	WEN M L, KANG R. Reliability analysis in uncertain random systems[J]. Fuzzy Optimization and Decision Making, 2024, 15 (4): 491- 506.
29	陈志聪, 康锐, 祖天培, 等. 基于技术成熟度的确信可靠性分配方法[J]. 系统工程与电子技术, 2022, 44 (1): 327- 337.
	CHEN Z C, KANG R, ZU T P, et al. Belief reliability allocation method based on technology readiness[J]. Systems Engineering and Electronics, 2022, 44 (1): 327- 337.
30	GJB 7688-2012. 装备技术成熟度等级划分及定义[S]. 北京: 总装备部电子信息基础部, 2012.
31	GB/T 37264-2018. 新材料技术成熟度等级划分及定义[S]. 北京: 国家市场监督管理总局, 2018.
32	张斌峰, 徐永能, 陶赟. 基于确信可靠度的城市轨道交通列车制动系统可靠性分配方法[J]. 兵器装备工程学报, 2022, 43 (9): 115- 120.
	ZHANG B F, XU Y N, TAO Y. Reliability allocation method of urban transit braking system based on belief reliability[J]. Journal of Ordnance Engineering, 2022, 43 (9): 115- 120.
33	ZHANG Q Y, KANG R, WEN M L. Belief reliability for uncertain random systems[J]. IEEE Trans. on Fuzzy Systems, 2018, 26 (6): 3605- 3614. doi: 10.1109/TFUZZ.2018.2838560
34	康锐. 确信可靠性理论与方法[M]. 北京: 国防工业出版社, 2020.
	KANG R. Belief reliability theory and methodology[M]. Beijing: National Defense Industry Press, 2020.
1	GOEBEL D M. Fundamentals of electric propulsion(second edition)[M]. Hoboken: Wiley, 2025.
2	张天平, 陈娟娟, 张雪儿. 离子电推进发展历史回顾与启示（上）[J]. 真空与低温, 2025, 31 (1): 114- 132.
	ZHANG T P, CHEN J J, ZHANG X E. Historical review and insights into the development of ion electric propulsion（I）[J]. Vacuum and Cryogenics, 2025, 31 (1): 114- 132.
3	MARCO C A, FERMIN N M, DANIELE T. Feasibility study of a solar electric propulsion mission to mars[J]. Acta Astronautica, 2024, 216 (1): 129- 142.
4	张天平, 李璇, 张雪儿. 电推进用于深空探测任务的工程经验总结与展望[J]. 推进技术, 2023, 44 (6): 1- 11.
	ZHANG T P, LI X, ZHANG X E. Engineering experience and prospect of applying electric propulsion to deep space missions[J]. Journal of Propulsion Technology, 2023, 44 (6): 1- 11.
5	LI Z L, PENG Z, SONG F, et al. Ion electric propulsion system design considerations for beam sparkle[J]. IEEE Access, 2024, 12, 15572- 15581.
6	SHENG B F, GE S Q, JIANG S, et al. Unexpected electrical breakdown characteristics and protection of PPU in space electric propulsion system[J]. Journal of Physics: Conference Series, 2024, 2784 (1): 012001. doi: 10.1088/1742-6596/2784/1/012001
7	李建鹏, 靳伍银, 赵以德. 多模式离子推力器输入参数设计及工作特性研究[J]. 物理学报, 2022, 71 (7): 265- 273.
	LI J P, JIN W Y, ZHAO Y D. Design of input parameters and operating characteristics for multi-mode ion thruster[J]. Acta Physica Sinica, 2022, 71 (7): 265- 273.
8	LI X Y, LI H, XIONG X Y, et al. Reliability modeling of multi-state phased mission systems with random phase durations and dynamic combined phases[J]. Reliability Engineering & System Safety, 2025, 253 (1): 110524.
9	钟晓芳, 兰红娟, 江文奇. 共识驱动的区间直觉模糊型多准则群体决策信息融合模型[J]. 系统工程与电子技术, 2020, 42 (7): 1558- 1566.
	ZHONG X F, LAN H J, JIANG W Q. Consensus driven information fusion model of interval-valued intuitionistic fuzzy multi-criteria group decision making[J]. Systems Engineering and Electronics, 2020, 42 (7): 1558- 1566.
10	ROY A, GUPTA N. A study on utilization of two cold standby components to increase reliability of a coherent system[J]. Communications in Statistics: Theory and Methods, 2025, 54 (2): 324- 351.
11	YANG S Q, ZENG Y, LI X, et al. Reliability analysis for wireless communication networks via dynamic Bayesian network[J]. Journal of Systems Engineering and Electronics, 2023, 34 (5): 1368- 1374. doi: 10.23919/JSEE.2023.000130
12	YU Q F, XU J. Distribution reconstruction and reliability assessment of complex LSFs via an adaptive Non-parametric Density Estimation Method[J]. Reliability Engineering & System Safety, 2025, 254 (1): 110609.
13	YANG C, LIANG Q W, HAO X Y, et al. Reliability analysis of torpedo loading based on fractional-order optimization model[J]. Journal of Systems Engineering and Electronics, 2023, 34 (3): 798- 803. doi: 10.23919/JSEE.2023.000085
14	CHEN Y, YANG T Y, WANG Y F. Reliability modeling of mutual DCFP considering failure physical dependency[J]. Journal of Systems Engineering and Electronics, 2023, 34 (4): 1063- 1073. doi: 10.23919/JSEE.2023.000108
15	徐建坤, 魏盛兴, 高剑, 等. 基于历史数据修正系数的可靠性分配方法[J]. 兵器装备工程学报, 2023, 44 (9): 254- 263.
	XU J K, WEI S X, GAO J, et al. Reliability allocation method based on correction coefficient and historical data[J]. Journal of Ordnance Equipment Engineering, 2023, 44 (9): 254- 263.
16	李健, 王宏伟, 慕宗燚, 等. 考虑性能稳定性的机械系统可靠性分配方法研究[J]. 中国机械工程, 2024, 35 (5): 821- 828.
	LI J, WANG H W, MU Z Y, et al. Research on reliability allocation method for mechanical systems considering performance stability[J]. China Mechanical Engineering, 2024, 35 (5): 821- 828.
17	HUANG H Z, DENG Z, HUANG S, et al. Application of improved fuzzy comprehensive evaluation method in reliability allocation and prediction of industrial robots[J]. Journal of University of Electronic Science and Technology of China, 2023, 52 (1): 132- 139.
18	ZHANG Q Y, LI X Y, ZU T P, et al. Belief reliability: a scientific exploration of reliability engineering[J]. Journal of Systems Engineering and Electronics, 2024, 35 (3): 619- 643. doi: 10.23919/JSEE.2024.000029
19	METAGUDDA S H, BALU A S. Belief reliability of structures with hybrid uncertainties[J]. Meccanica, 2024, 59 (9): 1593- 1606. doi: 10.1007/s11012-024-01832-z
20	ZENG Z G, WEN M L, KANG R. Belief reliability: a new metrics for products’ reliability[J]. Fuzzy Optimization and Decision Making, 2023, 12 (1): 15- 27.
21	于格, 康锐, 林焱辉, 等. 基于确信可靠度的齿轮可靠性建模与分析[J]. 系统工程与电子技术, 2019, 41 (10): 2385- 2391.
35	张清源, 文美林, 康锐, 等. 基于确信可靠性的功能、性能与裕量分析方法[J]. 系统工程与电子技术, 2021, 43 (5): 1413- 1419.
	ZHANG Q Y, WEN M L, KANG R, et al. Function, performance and margin analysis method based on belief reliability[J]. Systems Engineering and Electronics, 2021, 43 (5): 1413- 1419.
36	于倩影, 李娟, 戴洪德, 等. 基于LASSO变量选择的航空发动机相似性剩余寿命预测[J]. 航空动力学报, 2023, 38 (4): 931- 938.
	YU Q Y, LI J, DAI H D. LASSO based variable selection for similarity remaining useful life prediction of aero-engine[J]. Journal of Aerospace Power, 2023, 38 (4): 931- 938.
37	LIU Y H, WEI K C, HUANG C, et al. Quantile adaptive lasso: variable selection for quantile treatment effect estimation[J]. Journal of Statistical Computation and Simulation, 2024, 95 (2): 239- 257.
21	YU G, KANG R, LIN Y H, et al. Reliability modeling and analysis of gear based on belief reliability[J]. Systems Engineering and Electronics, 2019, 41 (10): 2385- 2391.
22	范梦飞, 曾志国, 康锐. 基于确信可靠度的可靠性评价方法[J]. 系统工程与电子技术, 2015, 37(11): 2648−2653.
	FAN M F, ZENG Z G, KANG R. An approach to measure reliability based on belief reliability[J]. Systems Engineering and Electronics, 2015, 37(11): 2648−2653.
23	陈文彬, 李晓阳, 童邦安, 等. 谐波减速器的传动效率确信可靠性建模与分析[J]. 振动工程学报, 2022, 35 (1): 237- 245.
	CHEN W B, LI X Y, TONG A B, et al. Belief reliability modeling and analysis for transmission efficiency of harmonic gear[J]. Journal of Vibration Engineering, 2022, 35 (1): 237- 245.
24	杨晗, 王浩伟, 李清荣, 等. 基于确信可靠性理论的蠕变寿命模型应用研究[J]. 系统工程与电子技术, 2022, 44 (3): 1044- 1051.
	YANG H, WANG H W, LI Q R, et al. Application research of creep life model based on belief reliability theory[J]. Systems Engineering and Electronics, 2022, 44 (3): 1044- 1051.
25	李泊远, 康锐, 余丽. 基于概率测度的确信可靠性建模与分析方法[J]. 系统工程与电子技术, 2021, 43 (7): 1995- 2004.
	LI B Y, KANG R, YU L. Belief reliability modelling and analysis method based on the probability measure[J]. Systems Engineering and Electronics, 2021, 43 (7): 1995- 2004.

关键部件	类别划分结果	可靠性目标变量	极限可靠度	可靠度分配值
阴极	随机单元	$ R_1^P $	0.9912	0.9884
中和器	随机单元	$ R_2^P $	0.9912	0.9883
放电室	不确定单元	$ R_1^U $	0.9792	0.9815
栅极	不确定单元	$ R_2^U $	0.9815	0.9835
阴极气路绝缘器	不确定单元	$ R_3^U $	0.9568	0.9614
阳极气路绝缘器	不确定单元	$ R_4^U $	0.9581	0.9626
中和器气路绝缘器	不确定单元	$ R_5^U $	0.9584	0.9628

t/h	R（t）
15000	1.000
20000	0.9984
25000	0.2977
30000	0.0326
40000	0.0008

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Research on reliability allocation, evaluation, and improvement method based on belief reliability theory for ion electric propulsion

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