Abstract: Abstract: Ground-coupled heat pump systems (GCHPs) have been recognized as being among the most energy efficient systems for space heating and cooling in residential and commercial buildings. GCHPs consist of a conventional heat pump coupled with a ground heat exchanger (GHE), and the knowledge of underground thermal properties is a prerequisite for the correct design of a GHE. For a GHE, the two important parameters are ground thermal conductivity and borehole thermal resistance, which is decided by borehole diameter, pipe size and configuration, pipe material, and the filling inside the borehole, so that a larger ground thermal conductivity and a small borehole thermal resistance allow the heat to be exchanged at a larger rate for a given borehole. Because of the two important parameters, a ground thermal response test (TRT) experiment is often performed on a test borehole for larger commercial installations, and it has been required in the GCHPs project whose building area is more than 5 000 m2 according to the technical code for GCHPs in China. Based on the relative TRT experimental data, how to calculate the true value of the two important parameters is necessary for GHE design, and the mathematical algorithm becomes one of the important impact factors when the experimental data from a TRT are analyzed and applied. Combining TRT experiments, this paper presents the pattern search algorithm (PSA) for determining ground thermal conductivity and heat resistance of a GHE based on a line source model. As an undetermined parameter, the heat resistance of a GHE is calculated without considering the physical parameters of the GHE, which decreases the calculating workload. In a calculating sample, the conclusion of applying PSA shows the relative errors of ground thermal conductivity and heat resistance of the GHE are respectively 1.42% and 1.73%, and the relative differences of the two parameters calculated by PSA are less, which proves the high precision of PSA. Finally, PSA were applied to calculate ground thermal conductivity and heat resistance of a GHE base on in-suit TRT test data. The two parameters based on the PSA algorithm make the square of difference between the calculated average water temperature and experiment data less than 0.8 after 10 hours, so the reliability of PSA was validated. In general, the PSA coupled with an advanced parameter estimation procedure was proven to result in a significant enhancement in the predictive capability of the ground thermal conductivity and heat resistance of a GHE by maximizing the amount of information that can be extracted from the raw in-suit TRT test data. This study is helpful for the design and application of GCHPs