Abstract: To address the reliability assessment requirements of multi-stage mission systems, this study proposes an optimal design framework for accelerated degradation testing based on the Wiener degradation model. A mission success probability model is established to analyze the joint effects of load heterogeneity and temporal asymmetry across mission stages. Utilizing the large-sample approximation method, the asymptotic variance of parameter estimation is derived as the optimization objective to determine the optimal test plan. Numerical case studies reveal that high-stress stages dominate resource allocation due to their nonlinear degradation characteristics, necessitating increased component allocation to capture rapid degradation patterns. Reduced stage duration amplifies estimation variance, which is mitigated by proportionally enhancing high-stress group resources. Two compromise rules are further proposed, and quantitative analyses using relative efficiency metrics demonstrate a positive correlation between mission complexity and efficiency loss. The resource-prioritization strategy achieves superior balance between estimation accuracy and practical constraints, providing actionable suboptimal solutions for engineering applications.