Battery Charge-Discharge Curve Estimation for Real-Time Efficiency Degradation
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Solution Overview
Problem
Existing methods for estimating the economic efficiency and efficiency degradation of lithium ion batteries, particularly when used in aggregates, are not suitable for operational conditions due to their requirement for long constant current periods and are not applicable to reused batteries.
Innovation Solution
An economic efficiency estimation apparatus and method using a charge-discharge curve, which involves deriving approximate open-end voltage and impedance functions, employing a Kalman filter for state estimation, and correcting these functions using a Gaussian function to estimate charge-discharge energy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If poCV or GITT methods are used to estimate OCV and Z values, then measurement precision is improved, but the measurement time becomes excessively long and the method is not suitable for operational conditions
Solution Approach 1:
The patent changes the estimation parameters from requiring long constant current periods (poCV/GITT) to using dynamic charge-discharge curves with varying currents. By estimating OCV and Z values during actual operational charge-discharge cycles rather than during extended relaxation periods, the method achieves accurate parameter estimation without excessive measurement time.
Solution Approach 2:
The patent transitions from static measurement methods (poCV/GITT requiring constant current and long relaxation) to dynamic estimation during actual charge-discharge operation. The system continuously estimates OCV and Z values while the battery undergoes normal charge-discharge cycles, making the measurement process adaptive to operational conditions rather than requiring the system to be taken out of service for extended periods.
2Device complexity
If traditional efficiency estimation methods are applied to reused batteries in aggregate, then device complexity is reduced, but measurement precision and reliability of efficiency estimation deteriorate due to varying degradation states
Solution Approach 1:
The patent applies local quality by individually estimating charge-discharge curves and efficiency parameters for each battery unit in the aggregate rather than using a single averaged model. This allows the system to account for varying degradation states, reuse histories, and performance characteristics of each battery while maintaining manageable system complexity through modular processing of individual battery data.
Solution Approach 2:
The patent segments the aggregate battery system into individual battery units for separate analysis. Each battery's charge-discharge curve is estimated independently, allowing for precise efficiency degradation assessment of each unit while the overall system maintains simplicity through standardized processing procedures applied to each segment.
3Productivity
If charge-discharge efficiency is optimized for economic benefits, then productivity increases, but the requirement for continuous monitoring and updating of battery parameters increases device complexity
Solution Approach 1:
The patent implements feedback by continuously monitoring charge-discharge voltage and current during operation, estimating the charge-discharge curve in real-time, and using this information to assess efficiency degradation. This feedback loop enables dynamic optimization of battery usage for economic benefits while the complexity is managed through efficient algorithms that process data during normal operation without requiring additional complex monitoring infrastructure.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate estimation of economic efficiency and efficiency degradation for various rechargeable batteries, including reused ones, by continuously updating open circuit voltage and impedance profiles during operation, allowing for real-time evaluation and improved battery management.
Implementation Method 1
a state estimation unit configured to estimate state parameters including a value of a charging rate, and a polarization voltage and an internal impedance of the secondary battery using an algorithm of a Kalman filter
Implementation Method 2
calculate a posterior estimation value by correcting the open-end voltage value and the impedance value in accordance with a correction expression using a Gaussian function having a predetermined learning rate L and a correction width σ as terms
Data Source
AI summary
An economic efficiency estimation apparatus derives an approximate curve of an initial open-end voltage function and an initial impedance function, sets a prior estimation function, and measures a charge-discharge voltage and a charge-discharge current. The apparatus estimates state parameters including an SOC value, and a polarization voltage and an internal impedance using a Kalman filter. The apparatus obtains an estimation error, calculates a posterior estimation value by a correction expression, corrects the prior estimation function based on the posterior estimation value, sets a new prior estimation function, estimates a charge-discharge curve, and estimates an economic efficiency index based on a charge-discharge power amount estimated from the curve.