Traction Battery Charge Time Estimation for Partial SOC Accuracy
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Solution Overview
Problem
Existing methods for estimating the time required to charge a traction battery in electrified vehicles are inaccurate, especially when the target state of charge is less than full, as they do not account for the age of components and the correlation between state of charge and energy is not linear.
Innovation Solution
A strategy selection method that uses two different approaches: the first strategy estimates the time required for a full charge by calculating available charging power, while the second strategy, involving communication between control modules, estimates the energy needed to reach a target state of charge and calculates the corresponding time, accounting for factors like component age and energy correlation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single strategy is used to estimate charge time for all target states of charge, then the system complexity is reduced, but the measurement precision of charge time estimation deteriorates
Solution Approach 1:
The patent divides the charge time estimation into two distinct strategies based on the target state of charge: Strategy 1 for full charge (100% SOC) and Strategy 2 for partial charge (less than 100% SOC). This segmentation allows each strategy to be optimized for its specific use case, improving overall estimation accuracy while keeping individual strategies relatively simple.
Solution Approach 2:
The system dynamically selects between two estimation strategies based on the target state of charge. When target SOC is 100%, Strategy 1 is used; when target SOC is less than 100%, Strategy 2 is used. This dynamic adaptation allows the system to maintain high precision across different charging scenarios without requiring a single complex unified model.
2Measurement precision
If strategy 2 is used for partial charge estimation, then the charge time estimation accuracy improves by accounting for component age and non-linear energy correlation, but the device complexity increases due to additional control module communication
Solution Approach 1:
The patent introduces a second control module that acts as an intermediary to calculate the estimated amount of energy needed for partial charging. This module communicates with the first control module, enabling accurate charge time estimation for partial charges by accounting for component age and non-linear energy-state of charge correlation, while keeping the complexity localized to the energy calculation function.
3Measurement precision
If calibrated energy losses are subtracted from incoming charging power, then the charge time estimation accuracy improves, but the loss of information increases due to calibration data requirements
Solution Approach 1:
The patent performs preliminary calibration to determine energy losses between the charger and battery, storing this calibration data for future use. By pre-calculating and storing the calibration factors, the system avoids repeated complex measurements during actual charging operations, improving real-time estimation accuracy while minimizing ongoing information loss.
Data Source
AI summary
A strategy selection method for estimating a charge time includes, when a target state of charge for a traction battery is a full charge, establishing an estimated time required to charge the traction battery using a first strategy, and when a target state of charge for the traction battery is less than a full charge, establishing the estimated time required to charge the traction battery using a different, second strategy.