Toyota jidosha kabushiki kaisha (20240210480). METHOD OF ESTIMATING FULL CHARGE CAPACITY AFTER DEGRADATION OF BATTERY, AND METHOD OF CREATING ESTIMATING EQUATION FOR FULL CHARGE CAPACITY AFTER DEGRADATION simplified abstract
Contents
- 1 METHOD OF ESTIMATING FULL CHARGE CAPACITY AFTER DEGRADATION OF BATTERY, AND METHOD OF CREATING ESTIMATING EQUATION FOR FULL CHARGE CAPACITY AFTER DEGRADATION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD OF ESTIMATING FULL CHARGE CAPACITY AFTER DEGRADATION OF BATTERY, AND METHOD OF CREATING ESTIMATING EQUATION FOR FULL CHARGE CAPACITY AFTER DEGRADATION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about Battery Degradation Prediction
- 1.13 Original Abstract Submitted
METHOD OF ESTIMATING FULL CHARGE CAPACITY AFTER DEGRADATION OF BATTERY, AND METHOD OF CREATING ESTIMATING EQUATION FOR FULL CHARGE CAPACITY AFTER DEGRADATION
Organization Name
toyota jidosha kabushiki kaisha
Inventor(s)
Kumiko Noda of Toyota-shi (JP)
Kouichi Yokoyama of Toyota-shi (JP)
METHOD OF ESTIMATING FULL CHARGE CAPACITY AFTER DEGRADATION OF BATTERY, AND METHOD OF CREATING ESTIMATING EQUATION FOR FULL CHARGE CAPACITY AFTER DEGRADATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240210480 titled 'METHOD OF ESTIMATING FULL CHARGE CAPACITY AFTER DEGRADATION OF BATTERY, AND METHOD OF CREATING ESTIMATING EQUATION FOR FULL CHARGE CAPACITY AFTER DEGRADATION
Simplified Explanation
The patent application describes a method to predict the decrease in full charge capacity of batteries in electric vehicles based on various state-related variables.
Key Features and Innovation
- Development of degradation contribution relations between battery state-related variables and full charge capacity decrease.
- Selection of variables with high correlation coefficients to estimate full charge capacity after degradation.
- Formulation of an equation using selected variables to accurately predict full charge capacity post-degradation.
Potential Applications
This technology can be applied in the electric vehicle industry to predict battery degradation and plan for maintenance or replacement.
Problems Solved
- Provides a method to estimate battery degradation in electric vehicles.
- Helps in predicting the remaining capacity of batteries for better planning and maintenance.
Benefits
- Improved maintenance planning for electric vehicle batteries.
- Enhanced efficiency and performance of electric vehicles.
- Cost savings by avoiding premature battery replacements.
Commercial Applications
Predictive Battery Degradation Technology for Electric Vehicles This technology can be utilized by electric vehicle manufacturers, fleet operators, and battery management companies to optimize battery usage and prolong battery life, leading to cost savings and improved performance.
Prior Art
Readers can explore prior research on battery degradation prediction models in electric vehicles to understand the existing knowledge in this field.
Frequently Updated Research
Stay updated on the latest advancements in battery degradation prediction models for electric vehicles to incorporate cutting-edge techniques into this technology.
Questions about Battery Degradation Prediction
How accurate are the predictions made by this technology?
The accuracy of predictions depends on the selected variables and coefficients in the equation, which are determined based on historical data.
What impact can this technology have on the electric vehicle industry?
This technology can revolutionize battery maintenance practices in electric vehicles, leading to improved efficiency and cost savings.
Original Abstract Submitted
through an experiment or the like, a degradation contribution relation representing a relation between each of n battery state-related variables and a decrease in full charge capacity is obtained. historical data on the variables is collected from l battery electric vehicles, and l simple estimated values of full charge capacity after degradation are obtained by using the degradation contribution relations. a correlation coefficient between the l historical data sets on each variable and the l simple estimated values is calculated, and m variables having the correlation coefficient exceeding a predetermined threshold are selected. an equation is formulated where the selected variables are explanatory variables and a high-accuracy estimated value of full charge capacity after degradation is an objective variable. the coefficients are determined by substituting k historical data sets into the variables of the equation and substituting k simple estimated values into a left side of the equation.
