Regression analysis of solar water heating system for car washing application in Isfahan, Iran

• The feasibility of solar water heaters in car washes was evaluated. • Twenty-five design scenarios were simulated using TSOL software. • Key performance predictors were identified through regression analysis. • High prediction accuracy was achieved with R² up to 0.96. Due to its favorable solar energy potential, Isfahan is one of the most promising regions for applying solar technologies, especially in water heating. These climatic conditions provide a strong basis for implementing solar water heaters (SWHs) in service sectors such as car washes. The scientific aim of this work is to evaluate the technical, energy, and environmental feasibility of employing SWH systems in an urban car wash in Isfahan. The subject of the research was to assess the system’s capacity to supply hot water, quantify fossil fuel savings, and evaluate greenhouse gas reduction. The methodology involved simulating 25 scenarios using TSOL software, with variations in collector area, tilt angle, tank volume, climatic inputs, and consumption. For each scenario, three outputs were obtained: solar energy contribution, annual supplied energy, and reduction in CO₂ emissions. Regression analysis was applied to build simplified models, enabling prediction without repeated simulations and supporting sensitivity analysis to identify key variables. Results show that prediction accuracy was very high in the train/test method (R² = 0.95–0.96), while cross-validation (CV) produced more realistic but robust values (R² = 0.77–0.84), confirming stability. Among the parameters, collector area, desired hot water temperature, and daily demand had the greatest impact, while flow rate and boiler capacity were negligible. This study extends research by introducing a hybrid framework combining simulation with regression analysis, applied to the novel context of urban car washes. The results provide a foundation for engineering design, policy-making, and adoption of solar heating technologies in regions with similar climates.