###### Abstract  
The aerospace electromagnetic relay (AEMR) is a key electronic component in aerospace and weaponry systems. It usually lacks sufficient test data to conduct an effective storage reliability assessment at its early development stage. Thus, this paper introduces the theory of belief reliability, a new theory in the field of reliability engineering. Under its theoretical framework, firstly, through the analysis of the storage degradation mechanism of AEMR, the performance degradation characterization parameters are selected to build a storage degradation model. Then, the failure criterion conditions of AEMR are analyzed, and the degradation characterization parameters are used as the'smaller the better' performance parameters to build a margin equation. Then, the margin equation is combined with the storage degradation model, and the uncertainties of the model parameters are quantified to complete the belief reliability model of AEMR. Finally, a certain AEMR is used as the object for validation. In solving the belief reliability model, the manufacturing information of the product, the degradation simulation data, and the test data are fully utilized to solve the model parameters by utilizing the uncertainty maximum likelihood estimation (UMLE) method. The results show that the method can obtain more accurate assessment results with small test data samples, and the MAE is reduced, compared to only simulation data, by 29.3%. By analyzing the uncertainty of the model parameters, it is found that the main sensitive factor affecting the storage reliability of batch aerospace relays is the initial release time. It was also found that the accuracy of the calculations could be significantly improved by considering the uncertainty of the threshold values when calculating. a pacs: 12.63. Therefore, modern reliability engineering urgently needs a new mathematical theory to solve the new problems arising from the development. In 2007, the uncertainty theory was proposed by [PERSON] [5; 6], forming a scientific and self-consistent mathematical axiom system with a set of innovative and convenient algorithms, providing a new method to solve the problem of small samples and uncertainty. Furthermore, in response to the issues faced by modern reliability engineering, [PERSON] [7; 8; 9] created the theory of belief reliability by combining traditional probability theory, uncertainty theory, and reliability science. Since it was proposed, many scholars have researched the theory's application, and many successful cases have been produced successively. For example, [PERSON] [10] modeled and estimated the uncertainty of fatigue life with small sample fatigue test data based on uncertainty theory. [PERSON] [11] developed a fatigue crack extension reliable life model based on uncertainty theory and belief reliability theory. It concluded, through analysis, that uncertainty theory could get more stable reliability evaluation results when considering epistemic uncertainty, and it found that material dispersion significantly affects fatigue life. [PERSON] [12] et al. proposed a belief reliability modeling method for the creep-fatigue of radiators, based on uncertainty theory for the tube-and-belt radiator of automobile engine, and gave improvement suggestions by analyzing the uncertainty of model parameters. [PERSON] [13] et al. proposed a belief reliability modeling method, based on assembly accuracy of spaceborne synthetic aperture radar (SAR), when facing the practical engineering problem of how to improve the service performance of SAR. By analyzing the multi-source uncertainty, theoretical guidance is provided to carry out the mechanism assembly, which effectively enhances the assembly accuracy and efficiency and enhances performance. [PERSON] [14] et al. proposed a gear reliability modeling method based on belief reliability, which further improved the accuracy of the evaluation results by considering both inherent uncertainty and cognitive uncertainty. [PERSON] [15] et al.