Software development for automotive application requires several iterations in order to tune parameters and strategy logic to operate accordantly with optimal performance. Thus, in this paper we present an optimizer method and tool used to tune calibration parameters related to torque estimation for a hybrid automatic transmission application. This optimizer aims to minimize the time invested during the software calibration and software development phases that could take significant time in order to cover the different driving conditions under which a hybrid automatic transmission can operate. For this reason, an optimization function based on the Nelder-Mead simplex algorithm using Matlab software helps to find optimized calibration values based on a cost function (square sum error minimization). This work will present a K0 clutch in a hybrid automatic transmission run under several operating conditions, and the method with which the optimizer aids the parameter calibration process in order to converge to the optimal values. This process also helps in the software development process to identify and include control strategy changes. The simulation environment that will be presented in this paper is based on Simulink/Stateflow Model Based Design (MBD) under Matlab platform. In this environment, the calibration parameters and strategy logic will be loaded to run desktop tests, optimization and further validation. Finally, a quantitative comparison among calibration methods (i.e. with and without the optimization algorithm) will be presented and how this could impact vehicle development processes in terms of test time optimization.