Air compressor is the critical part of a Compressed Air En- ergy Storage (CAES) system. Efficient and fast compression of air from ambient to a pressure ratio of 200-300 is a challenging problem due to the trade-off between efficiency and power den- sity. Compression efficiency is mainly affected by the amount of heat transfer between the air and its surrounding during the compression. One way to increase heat transfer is to implement an optimal compression trajectory, i.e., a unique trajectory max- imizing the compression efficiency for a given compression time and compression ratio. The main part of the heat transfer model is the convective heat transfer coefficient (h) which in general is a function of local air velocity, air density and air tempera- ture. Depending on the model used for heat transfer, different optimal compression profiles can be achieved. Hence, a good understanding of real heat transfer between air and its surround- ing wall inside the compression chamber is essential in order to calculate the correct optimal profile. A numerical optimization approach has been proposed in previous works to calculate the optimal compression profile for a general heat transfer model. While the results show a good improvement both in the lumped air model as well as Fluent CFD analysis, they have never been experimentally proved. In this work, we have implemented these optimal compression profiles in an experimental setup that con- tains a compression chamber with a liquid piston driven by a wa- ter pump through a flow control valve. The optimal trajectories are found and experimented for different compression times. The actual value of heat transfer coefficient is unknown in the exper- iment. Therefore, an iterative procedure is employed to obtain h corresponding to each compression time. The resulted efficiency versus power density of optimal profiles is then compared with ad-hoc constant flow rate profiles showing up to %4 higher effi- ciency in a same power density or %30 higher power density in a same efficiency in the experiment.