Avl List Gmbh

Christoph Hametner

Stefan Jakubek

Nico Didcock

Nikolaus Keuth

Markus Stadlbauer

Amra Suljanovic

Andreas Rainer

Christian Mayr

Maxime Deregnaucourt

Herbert Lanschützer

Karl Zettel

Thomas Winsel

Alexander Wasserburger

Markus Dohr

Various aspects of the present disclosure are directed to a method for ascertaining the state of health of a secondary battery. In one example embodiment, the method includes making a first estimation for the state of health by an observer, using an aging prediction model to ascertain a second estimation for the state of health, the aging prediction model being parameterized on the basis of the first estimation for the state of health. The first or second estimation of the state of health, or a combination of the first and second estimation of the state of health, is used as the state of health of the secondary battery.

Method and battery management system for ascertaining a state of health of a secondary battery

Various aspects of the present disclosure are directed to methods for calibrating a technical system with respect to stochastic influences during real operation of the technical system. In one example embodiment of the present disclosure, the method includes the steps of: determining the values of a number of control variables, carrying out the calibration on the basis of a load cycle which results in a sequence of a number of operating points, executing the load cycle multiple times under the influence of at least one random influencing variable, with each realization of the load cycle resulting in a random sequence of the number i of operating points, defining a risk measure of the probability distribution, with which the probability distribution is mapped to a scalar variable, and optimizing the risk measure by varying the number of control variables in order to obtain optimal control variables for calibration.

Method for calibrating a technical system

For the determination of a non-linear controller for a non-linear system it is proposed that a parameter set (K(k)) of the controller () is determined by means of an optimization using a multi-criteria evolutionary algorithm, in which algorithm a plurality of parameter sets (K(k)), which each represent a possible solution of the optimization, are determined in each evolution step and at least two quality values (f) are determined for each parameter set (K(k)) and the quality values (f) are optimized by the multi-criteria evolutionary algorithm.

Method for designing a non-linear controller for non-linear processes

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 (LM) of the model network determined in this manner, a local observer is then determined. The control observer () for estimating the SoC then results from a linear combination of the local observers.

Method for determining a control observer for the SoC

To determine a model for an output quantity (y) of a technical system that is dependent in a nonlinear manner on a number of input quantities in the form of an input quantity vector (u), a target output quantity range (COR) is defined and a model-based experimental design is determined with which the model is parameterized in the target output quantity range (COR) through the selection of associated input quantity vectors (u). A distance-based selection criterion is used for the selection of the input quantity vectors (u).

Method for determining a model of an output quantity of a technical system

A method for obtaining data from a nonlinear dynamic real system during a test run, for instance an internal combustion engine, a drivetrain, or parts thereof, a sequence of dynamic excitation signals is generated according to an initial design and a system output is measured. To enable the quick and precise generation of experimental designs for global measurement, modeling, and optimization of a nonlinear dynamic real system, a sequence of dynamic excitation signals was generated by generating a design with a sequence of excitation signals, obtaining output data by feeding said sequence into a model for the real system, determining a criterion for the information content of the complete design of experiment sequence, varying the sequence, obtaining new output data by feeding said modified sequence into the model, determining again said criterion, iterating until said criterion improves, and using the improved sequence of excitation signals for the real system.

Growing community of inventors

Vienna, Austria

Christoph Hametner