Battery parameter identification is emerging as an important topic due to the increasing use of battery energy storage. This paper studies parameter identification for the nonlinear double-capacitor (NDC) model for Lithium-ion batteries, which is a new equivalent circuit model developed in the authors’ previous work . It is noticed that the NDC model has a structure similar to the Wiener system. From the Wiener perspective, this work builds a parameter identification approach for this model upon the well-known maximum a posteriori (MAP) estimation. The purpose of using MAP is to overcome the nonconvexity and local minima that can cause unphysical parameter estimates. The proposed approach is the first one that we aware of exploits MAP for Wiener system identification. It also demonstrates significant effectiveness for accurate identification of the NDC model, validated through simulations and experiments.