Digital Twin Solid State Battery Component Identification
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Solution Overview
Problem
Existing technologies face challenges in identifying components within industrial assets that can be replaced with solid state batteries to enhance energy efficiency and reduce weight, while minimizing the need for additional safety components.
Innovation Solution
The method involves generating digital twins for industrial assets, simulating their performance, and using machine learning to identify components suitable for solid state battery integration, either by replacement or addition, to optimize energy density and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If liquid electrolyte batteries are used in industrial assets, then power supply functionality is maintained, but energy density per unit area is limited and safety risks increase
Solution Approach 1:
The patent applies parameter changes by transitioning from liquid electrolyte to solid electrolyte in battery components. This fundamental material parameter change enables higher energy density while eliminating safety hazards associated with liquid electrolytes, directly resolving the technical contradiction between energy density and safety risks
Solution Approach 2:
The patent utilizes composite materials by integrating solid state batteries into industrial assets. The solid electrolyte composite structure provides both high energy density and inherent safety, as the solid material composition prevents the leakage and combustion issues inherent in liquid electrolyte systems
2Use of energy by moving object
If solid state batteries are integrated into industrial assets, then energy efficiency and energy density are improved, but identification of suitable components becomes complex
Solution Approach 1:
The patent applies preliminary action by using digital twin simulations to pre-identify and evaluate suitable battery components before actual implementation. The simulation model predicts performance outcomes and identifies optimal replacement targets, simplifying the complex task of component selection and enabling informed decision-making about solid state battery integration
Solution Approach 2:
The patent uses copying by creating a digital twin - a virtual replica of the industrial asset - to test and evaluate battery component replacements without affecting the physical system. This digital copy allows comprehensive analysis of energy efficiency improvements and component compatibility, reducing the complexity of identifying suitable integration points
Data Source
AI summary
A method, computer system, and a computer program product for battery component identification is provided. The present invention may include receiving data for one or more industrial assets. The present invention may include generating a digital twin for each of the one or more industrial assets. The present invention may include simulating a performance of the digital twin for each of the one or more industrial assets. The present invention may include identifying one or more components of the one or more industrial assets for solid state battery integration based on the simulated performance of the digital twin, wherein the solid state battery integration includes the replacement of the one or more components with a solid state battery or the addition of the solid state battery to the one or more components.