Method for Determining a Control Observer for the SoC,申请号US201414762719-传众专利搜索

Method for Determining a Control Observer for the SoC

申请公布号：US2015362559(A1)

申请号：US201414762719

申请日期：2014.01.17

申请公布日期：2015.12.17

申请人：

AVL LIST GMBH

发明人：HAMETNER CHRISTOPH;JAKUBEK STEFAN;SULJANOVIC AMRA

分类号：G01R31/36

主分类号：G01R31/36

地址：Graz AT

摘要：In order to create a control observer for any battery type in a structured and at least partially automated manner, first, a nonlinear model of the battery, in form of a local model network including a number of local, linear, time-invariant, and dynamic models, which each have validity in specific ranges of the input variables, is determined from the measuring data of a previously ascertained, optimized experimental design via a data-based modeling method. For each local model (LMi) of the model network determined in this manner, a local observer is then determined. The control observer (13) for estimating the SoC then results from a linear combination of the local observers.

主权项：1. A method for determining a control observer (13) to estimate the SoC of a battery (10), comprising the following method steps: specifying an initial excitation signal of the battery (10), wherein the excitation signal comprises a time sequence of a plurality of design points defined by the load current (I) and the SoC value; specifying an initial model of the battery (10) having a model output (y) and model parameters (ψ); determining an optimized experimental design in form of an optimized time sequence of design points by use of a model based design of experiments method on the basis of the Fisher information matrix (IFIM), defined by-IFIM=1σ2∑k=1N∂y(k,ψ)∂ψ∂y(k,ψ)T∂ψand a judgment criterion; impinging the battery (10) with the individual design points in the time-sequence according to the determined experimental design, wherein the measurements are obtained by state variables of the battery (10); determining a nonlinear model of the battery (10) on the basis of the determined measurements and by a local model network comprising a number of local, linear, time-variant, and dynamic models (LMi), which are respectively valid in specific ranges of the input variables, wherein the model output is determined as a weighted linear combination of the outputs of the local models (LMi); converting the local models (LMi) of the model network into local, linear state space models having a state vector comprising the SoC; creating a local observer for each local, linear state space model; and creating the control observer (13) from a linear combination of the local observers.