## 1 Introduction  
For high-reliability, long-life products with the characteristics of long-term storage and single-use, the majority of their lifecycle from manufacturing to deployment is spent in the storage period [1]. During long-term storage, products are subject to various external environmental influences that can lead to changes in performance. These changes may ultimately affect their operational reliability. Therefore, storage reliability has become one of the key performance indicators for products, which is directly related to the maintenance, management, and operational effectiveness of products. A reasonable modeling analysis of the storage reliability of the product helps to ensure that the product plays the expected role at the critical time and achieves the goal of reliable operation [2; 3; 4]. Traditional accelerated life test methods mainly rely on failure life data. However, high-reliability, long-life electromechanical products cannot obtain sufficient life data within a short time for life prediction [5; 6; 7]. At this time, it is difficult to obtain effective assessment results using traditional accelerated life test methods. In fact, product failure is caused by gradual performance degradation, and the process of performance degradation contains a wealth of reliability information. Moreover, the accelerated degradation test (ADT) does not require products to be accelerated to failure, which can significantly shorten the test time. This is particularly beneficial for high-reliability, long-life products that are expensive to manufacture, as it can effectively reduce test costs. Therefore, ADT methods based on performance degradation provide a new approach for assessing the storage life of high-reliability, long-life products [8; 9]. At present, the more popular ADT methodsmainly include the constant-stress accelerated degradation test (CSADT) and the step-stress accelerated degradation test (SSADT) [10]. The CSADT is relatively mature, but it requires a long testing time and a large sample size of test products. Compared to the CSADT, the SSADT can significantly reduce the number of test samples by several times. Moreover, as the stress level gradually increases, the trend of product performance degradation becomes more obvious. However, due to the low initial stress level, the rate of performance decline at the beginning of the test is slow, which greatly reduces the efficiency of the accelerated test. Based on this, [PERSON] et al. proposed a step-down stress accelerated degradation test (SDSADT) method, which suggested that changing the sequence of stress application could significantly enhance test efficiency [11]. Subsequently, [PERSON] et al. proposed step-up-stress ADT and SDSADT for studying the thermal degradation kinetics of light-emitting diode (LED) lamps. The results indicated that the SDSADT could effectively alleviate the initial increase in the optical parameters of LED lamps [12]. Therefore, this article mainly focuses on the SDSADT method, emphasizing performance degradation. Degradation trajectory models are widely used in early performance degradation-based reliability research due to their intuitiveness and ease of understanding. For example, [PERSON] et al. established the degradation trajectory equation for the dual-stress accelerated degradation process to assess the storage life of power switching transistors [13]. The following year, [PERSON] et al. extended the general degradation trajectory equation to the case of varying environmental stress and established a general degradation trajectory equation under varying environmental stress to describe the impact of random stresses [14]. Subsequently, [PERSON] et al. proposed a new random effects model based on reference [14] to deal with degradation data under irregular time-varying environmental stress conditions. This model provided a new theory and method for modeling the degradation path of lithium-ion cells [15]. The degradation trajectory model can be used to establish the life model of the product intuitively.