Battery Charging Progress Prediction Using Historical SOC Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current battery charging progress prediction methods require chemical knowledge and are difficult to implement, making accurate prediction of charging duration challenging.
Innovation Solution
A method and apparatus for predicting battery charging progress using a prediction model based on historical charging data, dividing SOC intervals into subintervals, and incorporating parameters like charging voltage, current, and temperature to improve accuracy and adaptability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If equivalent circuit modeling based on chemical characteristics is used to predict battery charging progress, then prediction accuracy can be improved, but implementation complexity increases due to requiring chemical professional knowledge and solving nonlinear equations
Solution Approach 1:
The patent uses historical charging data to create a simplified prediction model that copies the essential charging patterns without requiring complex chemical modeling. The system builds a database of actual charging behaviors and uses this empirical data to predict future charging progress, avoiding the need to solve nonlinear chemical equations while maintaining practical prediction accuracy
Solution Approach 2:
The patent replaces the chemical/electrochemical modeling approach with a data-driven statistical approach. Instead of using equivalent circuit models based on chemical characteristics, the system uses historical charging data and statistical analysis to predict charging progress, substituting complex chemical principles with simpler data processing methods
2Measurement precision
If equivalent circuit modeling with nonlinear equations is used to describe charge-discharge process, then theoretical accuracy is improved, but ease of operation deteriorates due to difficulty in solving equations
Solution Approach 1:
The patent uses simple, easily obtainable historical charging data instead of complex theoretical models. The system collects actual charging data from battery operations and uses this empirical information for predictions, replacing the need for sophisticated equation-solving infrastructure with simple data lookup and statistical methods that are easy to implement and maintain
Solution Approach 2:
The patent changes the approach from using fixed theoretical parameters in nonlinear equations to using dynamic parameters derived from historical data. The system adjusts prediction parameters based on actual charging patterns observed in the data, making the implementation more flexible and easier to operate without requiring expert knowledge of battery chemistry
Data Source
AI summary
A battery charging progress prediction method and apparatus are provided. One example method includes: receiving a request message from a first terminal or a second terminal, where the request message includes a battery model of a battery of the first terminal and a first state of charge (SOC); determining charging progress information of the battery of the first terminal based on the request message; and sending a response message to the first terminal or the second terminal, where the response message includes the charging progress information.