Parameterization of a Battery Simulation Model Using Numerical . . . In this paper, we propose a semi-automated process for parameterizing a lithium polymer battery (LiPB) cell simulation model that is able to satisfy constraints on the optimized parameters This process uses a number of measured data sets under a variety of conditions
Equivalent-Circuit Cell Models - University of Colorado Colorado Springs We can model SOC as (where z˙ = dz dt) z˙(t) = −i(t) Q z(t) = z(t0)− 1 Q Z t t0 i(τ) dτ, where the sign of i(t) is positive on discharge In discrete time, if we assume that current is constant over sampling interval 1t, z[k +1] = z[k]−i[k]1t Q Note that cells are not perfectly efficient We can accommodate this
Parameterization of a Battery Simulation Model Using Numerical . . . Numerical optimizations can ensure the best possible fit between a simulation model and measured data, given a set of constraints In this paper, we propose a semi-automated process for parameterizing a lithium polymer battery (LiPB) cell simulation model that is able to satisfy constraints on the optimized parameters
A critical review of statistical calibration prediction models handling . . . Our aim in the present study is to review the main approaches used in the computational chemistry literature to deal with data inconsistency and or model inadequacy For instance, Wu et al 9 recently proposed a hierarchical model to calibrate the Lennard-Jones parameters of an interatomic potential on inconsistent viscosity measurements
How Do We Know if Model and Data are really Consistent - MIT OpenCourseWare How Do We Know if Model and Data are really Consistent? If minθ χ2 > tolerance it is very likely that the model is inconsistent with the data Need globally optimal choice of adjustable parameters θ to be 100% sure model data are inconsistent
Data Inconsistency and Incompleteness Processing Model in Decision Matrix Abstract: Data Inconsistency and incompleteness issues of pairwise comparison matrix (PCM) are hot research topics in multi-criteria decision making (MCDM) The goal of this paper is to propose a simple approach to identify and adjust the inconsistent data while estimate the missing data in a PCM