Battery SOH Estimation Using WLS Charging Time Analysis
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Solution Overview
Problem
Existing battery management systems face challenges in accurately estimating the state of health (SOH) of batteries due to measurement errors in internal battery resistance and current, leading to unreliable SOH estimation over time.
Innovation Solution
A weighted least square (WLS)-based method that calculates the time required for charging at preset voltage intervals and uses a metamodel to estimate SOH, minimizing errors by replacing current integration with WLS and enhancing reliability through parallel SOH estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If internal battery resistance is indirectly calculated using Ohm's law with measured voltage and current, then the measurement process is simple, but the SOH estimation accuracy deteriorates due to measurement errors and IR drop phenomenon
Solution Approach 1:
The patent extracts the problematic current measurement component from the SOH estimation process. Instead of using directly measured current values that accumulate errors, the invention formulates an estimation model that eliminates current measurement dependency, thereby removing the source of error accumulation while maintaining estimation functionality.
Solution Approach 2:
The patent introduces voltage as an intermediary parameter to replace direct current measurement. By using voltage measurements combined with a predefined resistance model, the system achieves current information without direct current sensing, thereby avoiding the IR drop phenomenon and measurement error accumulation associated with traditional amperometric methods.
2Ease of manufacture
If charging/discharging currents are accumulated to estimate SOC and subsequently SOH, then the estimation method is straightforward, but accuracy deteriorates over time due to error accumulation
Solution Approach 1:
The patent implements a feedback mechanism where the estimation model continuously refines SOC and SOH values based on voltage measurements. The model uses the relationship between voltage, current, and state variables to correct estimation deviations, preventing error accumulation that would otherwise occur with simple current integration methods.
Solution Approach 2:
The patent changes the fundamental parameter used for estimation from accumulated current (prone to drift) to voltage-based measurements combined with an electrochemical model. This parameter transformation fundamentally alters the estimation approach, replacing error-prone integration with a model-based method that maintains accuracy over time through physical consistency constraints.
3Device complexity
If traditional current integration method is used for SOC estimation, then calculation is simple, but estimation accuracy deteriorates with lapse of time
Solution Approach 1:
The patent replaces the mechanical integration approach (simple but error-prone current accumulation) with an electrochemical model-based calculation system. This substitution introduces a more complex but physically accurate model that accounts for voltage-current-state relationships, thereby maintaining precision without relying on error-prone numerical integration over time.
Data Source
AI summary
Provided are a weighted least square (WLS)-based state of health (SOH) estimating system and method. A battery management system according to an aspect of the present invention includes a measurer measuring a time required for charging at each of preset voltage intervals within a preset voltage range in which a battery is charged with a constant current; and an estimator estimating a parameter using an estimated value of time required for charging according to a preset metamodel and a measured value of a time required for charging after completion of the constant current charging.