This paper describes an improved algorithm for calculating the six parameters required by the California Energy Commission (CEC) photovoltaic (PV) Calculator module model. Rebate applications in California require results from the CEC PV model, and thus depend on an up-to-date database of module characteristics. Currently, adding new modules to the database requires calculating operational coefficients using a general purpose equation solver—a cumbersome process for the 300+ modules added on average every month. The combination of empirical regressions and heuristic methods presented herein achieve automated convergence for 99.87% of the 5487 modules in the CEC database and greatly enhance the accuracy and efficiency by which new modules can be characterized and approved for use. The added robustness also permits general purpose use of the CEC/6 parameter module model by modelers and system analysts when standard module specifications are known, even if the module does not exist in a preprocessed database.