Battery Parameter Setting via Temperature-SOC Segmentation
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Solution Overview
Problem
Existing methods for determining battery parameters for equivalent circuit models are time-consuming and difficult to accurately control experimental conditions, particularly in HPPC experiments for temperature and State of Charge (SOC).
Innovation Solution
A battery parameter setting apparatus and method that quickly sets battery parameters by segmenting battery information into temperature and SOC sections, calculating reference and candidate parameters, and updating them based on comparison of predicted values, without the need for separate experiments like HPPC.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If HPPC experiments are performed for temperature and SOC individually to obtain battery parameters, then the battery parameters can be extracted and tuned, but the determination process takes a long time and it is difficult to accurately control experimental conditions
Solution Approach 1:
The patent pre-divides the battery operating range into multiple temperature sections and SOC sections, and pre-calculates reference parameters for each section. This preliminary preparation eliminates the need for time-consuming HPPC experiments during actual operation, as the parameter determination can be quickly retrieved from pre-computed data tables based on current temperature and SOC measurements.
Solution Approach 2:
The patent segments the battery operating range into discrete temperature sections and SOC sections, creating a grid structure for parameter lookup. This segmentation allows the system to quickly identify the appropriate parameter set without performing full experiments, reducing determination time while maintaining accuracy through targeted parameter selection for specific operating conditions.
2Measurement precision
If HPPC experiments are performed for temperature and SOC individually to obtain battery parameters, then the battery parameters can be extracted and tuned, but it is difficult to accurately control experimental conditions
Solution Approach 1:
The patent creates a virtual model of battery parameters through pre-calculated reference parameter tables that replicate the results of HPPC experiments. Instead of performing actual physical experiments with complex condition control, the system uses these copied parameter sets retrieved from tables based on measured temperature and SOC, eliminating experimental control difficulties while maintaining parameter accuracy.
Solution Approach 2:
The patent introduces reference parameter tables as an intermediary between actual battery operation and parameter determination. These tables serve as a pre-computed lookup mechanism that translates measured temperature and SOC values into appropriate battery parameters without requiring direct experimental intervention, simplifying the operation while preserving accuracy.
3Productivity
If reference parameters are used directly without updating, then the calculation is simple and fast, but the parameters may not reflect the current state of the battery
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors actual battery voltage and compares it with predicted voltage calculated using reference parameters. When the difference exceeds a threshold, the system updates the parameters by performing HPPC experiments and adjusting the reference values. This feedback loop ensures parameters remain accurate for current battery states while minimizing unnecessary updates to maintain speed.
Solution Approach 2:
The patent makes the parameter selection dynamic by allowing the system to switch between using pre-stored reference parameters (for speed) and performing updated HPPC experiments (for accuracy). The system adapts its approach based on whether the current operating conditions match existing reference data or require parameter updates, optimizing the balance between productivity and reliability in real-time.
Data Source
AI summary
The present disclosure is directed to a battery parameter setting apparatus and method, which may quickly generate and set a battery parameter most suitable for an equivalent circuit model from battery information without going through a separate experiment such as a HPPC experiment. According to one aspect of the present disclosure, there is an advantage that a battery parameter of an equivalent circuit model more suitable for a current state of a battery may be set.