Several aspects of the open circuit voltage (OCV) characterization of Li-ion batteries as it applies to battery fuel gauging (BFG) in portable applications are considered in this paper. Accurate knowledge of the nonlinear relationship between the OCV and the state of charge (SOC) is required for adaptive SOC tracking during battery usage. BFG in portable applications requires this OCV–SOC characterization to meet additional constraints: (i) The OCV–SOC characterization has to be defined with a minimum number of parameters; (ii) It should be easily computable and invertible with few operations; and (iii) Computation of the model, its derivative and its inverse should be possible in a numerically stable way. With the help of OCV–SOC characterization data collected from 34 battery cells each at 16 different temperatures ranging from −25 °C to 50 °C, we present the following results in this paper: (a) A robust normalized OCV modeling approach that dramatically reduces the number of OCV–SOC parameters and as a result simplifies and generalizes the BFG across temperatures and aging, (b) Several novel functions for OCV modeling, (c) Efficient methods to simplify the computations of OCV functions, (d) Novel methods for OCV parameter estimation, and (e) A detailed performance analysis.