CCIR Calibration for Rapid EV Battery Health Screening
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Solution Overview
Problem
Current battery screening methods for EV batteries are time-consuming and costly, requiring lengthy tests to determine State-of-Health (SOH) accurately, which hampers efficient reuse and recycling, and existing fast methods lack accuracy and require complex setups.
Innovation Solution
A method utilizing Constant-Current (CC) and Constant-Voltage (CV) charging to calculate the Constant-Current Impulse Ratio (CCIR), combined with Artificial Intelligence (AI) modeling to rapidly assess battery health, reducing testing time from 26 hours to 6 hours and improving accuracy by using a neural network to generate a calibration curve for SOH estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional constant-current discharge testing is used to accurately measure battery storage capacity, then measurement precision is improved, but testing time increases significantly (exceeding 26 hours)
Solution Approach 1:
The patent changes the testing parameters by using constant-current impulse charging instead of traditional constant-current discharge testing. It measures the constant-current impulse ratio (CCIR) during charging phases and uses AI modeling to estimate SOH, reducing test time from over 26 hours to approximately 6 hours while maintaining accuracy.
Solution Approach 2:
The patent replaces the traditional mechanical/chemical discharge testing process with an AI-based modeling system. It substitutes physical discharge testing with computational modeling that uses CCIR measurements and neural networks to predict battery health, significantly accelerating the assessment process.
2Productivity
If rapid charging or discharging is performed to reduce testing time, then productivity is improved, but measurement precision deteriorates due to battery heating effects
Solution Approach 1:
The patent performs preliminary measurements during the constant-current charging phase before the battery undergoes significant heating. By measuring CCIR early in the charging process and using AI modeling to extrapolate SOH, it obtains accurate results before thermal effects contaminate the measurements.
Solution Approach 2:
The patent introduces CCIR (constant-current impulse ratio) as an intermediary parameter that correlates with SOH without requiring full discharge cycles. This intermediary measurement allows rapid assessment without subjecting the battery to prolonged high-current stress that causes heating.
3Loss of time
If existing fast screening methods are used to reduce testing time, then loss of time is improved, but measurement precision and reliability deteriorate
Solution Approach 1:
The patent employs AI modeling with neural networks that learn from training data to establish relationships between CCIR measurements and actual SOH values. The model continuously refines its predictions based on patterns recognized during training, providing accurate SOH estimates from rapid CCIR measurements.
Solution Approach 2:
The patent creates a universal AI model that can estimate SOH for various battery conditions and aging states using a single standardized CCIR measurement protocol. This multi-functional approach maintains accuracy across different battery types and states while enabling rapid screening.
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
This approach allows for rapid and accurate assessment of battery health, enabling efficient sorting and reuse of EV batteries, reducing environmental impact by extending their useful life and reducing disposal burdens.
Implementation Method 1
The battery being tested is initially charged to 3.8 volts by applying a Constant Current (CC) having a value of 1C amps
Implementation Method 2
The battery is then discharged using a Constant Current (CC) having a fixed current value of 1C
Data Source
AI summary
Used batteries are screened based on a measured Constant-Current Impulse Ratio. A used battery is charged using a Constant Current (CC) until a voltage target is reached, and the current integrated to obtain the CC charge applied, QCC. Then the battery continues to be charged using a Constant Voltage (CV) of the voltage target until the charging current falls to a minimum current target. The current is integrated over the CV period to obtain the CV charge applied, QCV. The measured CCIR is the ratio of QCC to (QCC+QCV). The measured CCIR is input to a calibration curve function to obtain a modeled State of Health (SOH) value. The used battery is sorted for reuse or disposal based on the modeled SOH value. The calibration curve function is obtained by aging new batteries to obtain CCIR and SOH data that are modeled using a neural network.