From Traditional Passive Design to Artificial Intelligence-Based Optimization: A Systematic Review of Passive Design in Residential Buildings

Buildings account for a significant share of global energy consumption and greenhouse gas emissions, highlighting the importance of passive design strategies for improving residential energy efficiency and thermal comfort. This systematic review, conducted and reported in accordance with PRISMA 2020, examines the evolution of passive residential design from bioclimatic principles toward building energy simulation, computational optimization, and artificial intelligence (AI). A total of 191 studies were included in the systematic evidence synthesis. The reviewed evidence identifies orientation, insulation, glazing properties, window-to-wall ratio, shading, thermal mass, and ventilation as recurrent design variables influencing residential energy and thermal performance. The literature also reveals a methodological transition from the evaluation of individual passive strategies toward integrated computational frameworks combining building-performance simulation, predictive modeling, and multi-objective optimization. Validation or verification was explicitly reported in 72 of the 191 studies (37.7%), highlighting an important methodological limitation in the transferability of simulation- and AI-derived results. Methodological heterogeneity, climatic uncertainty, occupant behavior, and restricted transferability across climatic and construction contexts also remain important challenges. Overall, the evidence indicates that AI can complement rather than replace the physical principles of passive design by supporting prediction, design-space exploration, and optimization. From an engineering perspective, the findings support a hierarchical workflow in which passive variables guide early design decisions, simulation evaluates their interactions, multi-objective optimization explores performance trade-offs, and AI or surrogate models provide decision support only after adequate validation for the specific climate and building context.