18512684. METHOD FOR DETERMINING THE AGING OF A BATTERY STORAGE DEVICE, APPARATUS, AND COMPUTER PROGRAM PRODUCT simplified abstract (Siemens Aktiengesellschaft)

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METHOD FOR DETERMINING THE AGING OF A BATTERY STORAGE DEVICE, APPARATUS, AND COMPUTER PROGRAM PRODUCT

Organization Name

Siemens Aktiengesellschaft

Inventor(s)

Barbara Schricker of Erlangen (DE)

Arno Arzberger of Stegaurach (DE)

Kilian Scheer of Bad Staffelstein (DE)

METHOD FOR DETERMINING THE AGING OF A BATTERY STORAGE DEVICE, APPARATUS, AND COMPUTER PROGRAM PRODUCT - A simplified explanation of the abstract

This abstract first appeared for US patent application 18512684 titled 'METHOD FOR DETERMINING THE AGING OF A BATTERY STORAGE DEVICE, APPARATUS, AND COMPUTER PROGRAM PRODUCT

Simplified Explanation

The patent application describes a method for measuring parameters within cycles of a cycling process, manipulating the measurement data, forming a generated measurement data set, generating signals representing the values of the generated data, and determining the aging of the system.

  • The method involves running through at least two cycles of a cycling process to measure parameters in the first phase.
  • The measurement data formed by the parameters measured over the cycles is manipulated in a second phase, changing at least one part of the data within the cycles.
  • A generated measurement data set is formed by merging the modified parameters with the unmanipulated data from the cycles.
  • Signals representing the values of the generated measurement data are generated.
  • The aging of the system is determined based on the collected data.

Potential Applications

This technology could be applied in industries where monitoring and analyzing cycling processes are crucial, such as in battery testing, material fatigue testing, and performance evaluation of electronic components.

Problems Solved

This method helps in accurately measuring and analyzing parameters within cycles, identifying any anomalies or deviations, and determining the aging of the system. It provides a comprehensive approach to data manipulation and analysis in cycling processes.

Benefits

The benefits of this technology include improved accuracy in parameter measurement, early detection of potential issues within the system, and a better understanding of the aging process. It can lead to enhanced performance and longevity of systems.

Potential Commercial Applications

Potential commercial applications of this technology could include quality control in manufacturing processes, predictive maintenance in industrial equipment, and performance optimization in electronic devices.

Possible Prior Art

One possible prior art could be methods for data manipulation and analysis in cycling processes, such as algorithms for signal processing and pattern recognition in time-series data.

Unanswered Questions

How does this method compare to traditional data analysis techniques in cycling processes?

This article does not provide a direct comparison between this method and traditional data analysis techniques. It would be interesting to know the specific advantages and limitations of this approach compared to existing methods.

What are the specific parameters that can be measured and analyzed using this method?

The article mentions measuring parameters within cycles, but it does not specify the exact parameters or variables that can be analyzed. Understanding the range of parameters that can be monitored would provide a clearer picture of the applicability of this technology.


Original Abstract Submitted

A method including a) running through at least two cycles of a cycling process for measuring parameters within the cycles in the temporally first phase, b) manipulating measurement data formed by the parameters measured over the cycles in a second phase in such a way that at least one part of the measurement data from at least one part of the cycles is changed within the cycles with respect to parameters at least partially correlating with an upper voltage limit and a lower voltage limit, c) forming a generated measurement data set for the part of the cycles in such a way that modified at least partially correlating parameters of the manipulated part of the measurement data and the unmanipulated part of the measurement data from the part of the cycles are merged, d) generating signals representing the values of the generated measurement data, e) determining the aging.