Steady-state simulation plays a vital role in the design optimization of HVAC systems with vapor compression cycles (VCCs). VCC models often involve highly nonlinear and stiff equations, which can present difficulties for achieving robust convergence with desirable accuracy and computational efficiency. Hybrid solvers have gained great attention, as such approaches can leverage the strengths of different algorithms to yield more desirable performance. In this paper, we present an investigation of two hybrid solvers (HS #1 and HS #2) for steady-state simulation of VCC systems, targeting robust convergence and accuracy with computational efficiency. The two hybrid solvers are evaluated against the Newton solver using three system configurations: i) a simple four-component VCC; ii) a VCC with two condensers in parallel; and iii) a VCC with four condensers in a series and parallel (2x2) arrangement and four evaporators in series. In particular, the refrigerant charge of system operation is reinforced via residual formulation. The solvers and simulation study are carried out with Matlab and Modelica (Dymola), respectively, to facilitate comparative analysis. Through case studies with a number of scenarios, the performance of the solvers is evaluated in terms of convergence rate, accuracy, and computational efficiency. For 99% of the successful simulation scenarios for the simple VCC, HS #1 converges faster than the Newton solver and HS #2. Both hybrid solvers show higher accuracies than the Newton solver in all convergent runs. The computation efficiency of HS #1 is significantly higher than the HS #2 and the Newton solver.
