A predictive COP model for air source heat pumps under extreme heat conditions using no experimental data

As global warming intensifies, extreme weather events have become increasingly frequent. In 2024, Tokyo has experienced a significant increase in the number of days with temperatures exceeding 35 ∘ C. Such extreme heat conditions substantially reduce the coefficient of performance (COP) of air-source heat pumps (ASHPs), especially when outdoor units are exposed to direct sunlight. However, little research has addressed ASHP performance in extreme heat, particularly at outdoor temperatures above 40 ∘ C, and experimental data for these scorching conditions remain severely lacking. To fill this gap, laboratory experiments were conducted to evaluate ASHP performance under the Japanese Industrial Standard condition of 35 ∘ C, as well as under extreme heat conditions of 40 ∘ C and 45 ∘ C. Additionally, a predictive COP model—based on manufacturer-provided performance data—was introduced, capable of accurately predicting the COP under current operating conditions without relying on any measured data. This model was further modified to enhance its accuracy under extreme heat conditions. Through comparisons with experimental results, we confirmed that under extreme heat conditions at 45 ∘ C, the proposed modified predictive COP model improved the accuracy of electric power predictions by over 40 % compared to the unmodified model, achieving an R 2 value of 0.88.