This article demonstrates a novel parameter identification of a rate-dependent damage constitutive model using self-optimizing inverse method. In the self-optimizing inverse method, an implicit-explicit objective function is formulated as a function of two sets of full-field stresses/strains (implicit non-measurable variables) from two nonlinear finite element analyses, that is, force-driven and displacement-driven simulations, respectively, and global boundary displacements and forces (explicit measurable variables) from experimental tests. The self-optimizing inverse method can self-correct the damage parameter set through optimization procedures referring to global responses measured in laboratory tests. A micromechanics and fracture mechanics based damage constitutive law that accounts for the microcrack nucleation and growth is adopted. Synthetic data from impact tension test simulations were used to demonstrate successful performances of the self-optimizing inverse method in identifying the nonlinear constitutive and damage-related parameters. Comparative studies were conducted using two different optimization techniques - the simplex method and the steady-state genetic algorithm. The identified parameters proved to be identical to the reference values. Finally, in order to further verify the inverse identification method, self-optimizing inverse method analyses were conducted to identify the damage parameter set based on real experimental data from impact tension tests at different strain rates.