Downsizing and turbocharging yield considerable improvements in part-load fuel economy for gasoline engines while maintaining or exceeding the power output of conventional naturally-aspirated engines. Turbocharger compressors are, however, susceptible to surge – the instability phenomena that impose limitations on the operation of turbocharged engines because of undesired noise, engine torque capability constraints, and hardware strain. Turbocharged engines are typically equipped with a binary compressor recirculation valve (CRV) whose primary function is to prevent compressor surge. Calibration of the associated control strategy requires in-vehicle tests and usually employs subjective criteria. This work aims to reduce the calibration effort for the strategy by developing a test procedure and data processing algorithms. This work develops an automated calibration for CRV control that will generate a baseline calibration that avoids surge events. The effort to obtain the baseline calibration, which can be further fine-tuned, is thereby significantly reduced. Procedures are developed for testing and analysis that combines a previously developed surge characterization method and unconstrained nonlinear optimization. A real-time capable adaptive algorithm is also presented that can update the CRV control calibration online. The developed procedures are demonstrated on vehicle data and compared with manually obtained calibrations.