Samsung electronics co., ltd. (20240111921). METHOD AND DEVICE WITH BATTERY MODEL OPTIMIZATION simplified abstract
Contents
- 1 METHOD AND DEVICE WITH BATTERY MODEL OPTIMIZATION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD AND DEVICE WITH BATTERY MODEL OPTIMIZATION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
METHOD AND DEVICE WITH BATTERY MODEL OPTIMIZATION
Organization Name
Inventor(s)
Myeongjae Lee of Suwon-si (KR)
Huiyong Chun of Pohang-si (KR)
METHOD AND DEVICE WITH BATTERY MODEL OPTIMIZATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240111921 titled 'METHOD AND DEVICE WITH BATTERY MODEL OPTIMIZATION
Simplified Explanation
The patent application describes a method for optimizing parameters of a battery model using two predetermined optimization techniques.
- The method starts with performing first parameter optimization of the battery model using a first predetermined optimization technique.
- When a switching criterion is met, based on a count accumulated during the first optimization, the method switches to a second predetermined optimization technique.
- The second parameter optimization of the battery model is then performed using the second technique.
- A final parameter combination is determined as the optimized parameter of the battery model when an optimization end event occurs during the second parameter optimization.
Potential Applications
The technology described in this patent application could be applied in the development and optimization of battery models for various applications, such as electric vehicles, energy storage systems, and portable electronics.
Problems Solved
This technology solves the problem of efficiently optimizing parameters of battery models by utilizing multiple optimization techniques in a systematic manner. It helps in improving the accuracy and performance of battery models for different use cases.
Benefits
The benefits of this technology include improved accuracy in predicting battery behavior, enhanced performance of battery systems, and optimized design of battery-powered devices. It can lead to better energy management and longer battery life in various applications.
Potential Commercial Applications
The technology could find commercial applications in industries related to electric vehicles, renewable energy, consumer electronics, and grid energy storage. Companies involved in battery research, development, and manufacturing could benefit from implementing this optimization method.
Possible Prior Art
One possible prior art could be related to existing optimization techniques used in battery modeling and simulation software. These techniques may involve single-parameter optimization methods or traditional optimization algorithms applied to battery models.
Original Abstract Submitted
a processor-implemented method includes performing first parameter optimization of a battery model through a first predetermined optimization technique; switching, based on a count accumulated while performing the first parameter optimization indicating that a switching criterion has been met, from the first optimization technique to a second predetermined optimization technique; performing second parameter optimization of the battery model through the second predetermined optimization technique; and determining a final parameter combination as an optimized parameter of the battery model, in response to an occurrence of an optimization end event during the performance of the second parameter optimization.
