In the case of fitting nonlinear models, is the COD (R2) sufficient for the selection of the best fitting model or should other criteria be used such as Akaike's information criteria?
As far as I know, information criteria such as the AIC or BIC can only be used in combination with a likelihood. I can't tell how your fits are being performed, but you mentioning R^2 smacks of least squares.
Note that R^2 is only appropriate for linear models. See e.g. Article An evaluation of R2 as an inadequate measure for nonlinear m...
Maybe this thread can help you further with your problem: