US 11,733,305 B2
Method, computer-implemented tool and battery management system for estimating states of health of batteries storing electrical energy and battery energy storage system
Joachim Bamberger, Stockdorf (DE); Amer Mesanovic, Munich (DE); and Andrei Szabo, Ottobrunn (DE)
Assigned to SIEMENS AKTIENGESELLSCHAFT
Filed by Siemens Aktiengesellschaft, Munich (DE)
Filed on Mar. 18, 2021, as Appl. No. 17/205,356.
Claims priority of application No. 20165139 (EP), filed on Mar. 24, 2020.
Prior Publication US 2021/0302502 A1, Sep. 30, 2021
Int. Cl. G01R 31/36 (2020.01); G01R 31/367 (2019.01); G01R 31/389 (2019.01); G01R 31/392 (2019.01); G01R 31/3842 (2019.01)
CPC G01R 31/367 (2019.01) [G01R 31/389 (2019.01); G01R 31/3842 (2019.01); G01R 31/392 (2019.01)] 12 Claims
OG exemplary drawing
 
1. A method for automatically estimating states-of-health of batteries storing electrical energy and generating notification information, comprising:
a) collecting and storing direct current measurement data, direct voltage measurement data and temperature measurement data from a battery storing electrical energy due to battery measurements of battery-internal physical properties inter alia the measurement of a terminal direct current IDC as a first physical property, a terminal direct voltage UDV as a second physical property and a battery cell temperature T as a third physical property during a recurring, continuous, time interval (ti), at the most over a lifetime of the battery, wherein the collecting and storing is performed during normal operation of the battery,
b) selecting a time period (tp) with tp≥n·ti, wherein n is a positive integer,
c) executing a dynamical battery model for the time period, which relates to measurable model input sizes u, measurable model output sizes y, model states x and model parameter z and which is a time t discretized such that a model state xt+1 is defined to a first function f with xt+1:=ftp(xt,ut,z) and a model output size yt is defined to a second function g with yt:=gtp(xt,ut,z), by
accessing direct current evaluation data including direct current measurement data of the stored direct current measurement data relating to the measurable model input sizes u,
direct voltage evaluation data including direct voltage measurement data of the stored direct voltage measurement data relating to the measurable model output sizes y and
temperature evaluation data including temperature measurement data of the stored temperature measurement data relating to the measurable model input sizes u,
solving an optimization-/model parameter estimation-problem given by the first function f, the second function g, the model input sizes u and the model output sizes y such that the solution of the problem yields a model parameter for the time period,
minimizing a difference between the battery model and the battery measurements and enabling the indication of the battery-state-of-health due to the model parameter being constant for the selected time period, and
d) evaluating or doing a state-of-health trend analysis of an evolutionary course of the model parameter being determined by solving the optimization-/model parameter estimation-problem over numerous time periods with constant or variable time durations
e) generating notification information about an increase of the battery-state-of-health more than expected or in case of battery operating safety risks as a result of evaluating or doing the state-of-health trend analysis of the model parameter respectively the battery-internal resistance R and/or the battery-internal capacity C, and
f) outputting the notification information.