Estimating Battery OCP from Discharge Curves
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Solution Overview
Problem
Lithium-ion batteries face challenges in accurately determining thermodynamic parameters, such as open circuit potential (OCP), which are essential for sophisticated physics-based models, due to their complexity and the need for destructive testing, limiting the adoption of these models for optimal charging profiles and battery management.
Innovation Solution
A methodology is developed to estimate OCP of the positive electrode based on a single discharge curve, allowing for real-time parameter estimation without destructive testing, enabling more accurate battery modeling and control, and facilitating the use of second-hand batteries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If destructive testing methods are used to measure battery parameters, then measurement precision is improved, but the battery is damaged and cannot be used again
Solution Approach 1:
The patent creates a virtual copy of the battery's internal state by using physics-based models that replicate battery behavior. Instead of physically dissecting the battery to measure parameters, the system uses electrical measurements combined with mathematical models to generate accurate virtual representations of internal parameters like electrode potential and state of charge, achieving precise measurement without physical damage
Solution Approach 2:
The patent replaces physical/mechanical measurement methods (disassembly, direct measurement of electrode thickness and particle size) with electrical measurement methods. By applying electrical stimuli and measuring voltage responses, the system indirectly determines physical parameters through mathematical relationships, eliminating the need for mechanical dissection while maintaining measurement accuracy
2Measurement precision
If sophisticated physics-based models are used for battery management, then battery control accuracy is improved, but the complexity of the system increases due to lack of accurate parameters
Solution Approach 1:
The patent implements a feedback mechanism where the physics-based model continuously receives electrical measurement data from the battery and adjusts its internal parameter estimates accordingly. The model predicts battery behavior based on current parameters, compares predictions with actual measurements, and refines parameter estimates through iterative optimization, maintaining high accuracy while adapting to changing battery conditions without requiring manual recalibration
Solution Approach 2:
The system performs self-characterization by automatically determining its own parameters through electrical measurements and mathematical modeling. The battery management system independently extracts internal parameters like open circuit potential and diffusion coefficients from routine charge/discharge data without requiring external destructive testing or manual intervention, enabling the system to maintain accurate physics-based models autonomously
3Ease of operation
If conventional empirical models are used for battery management, then ease of operation is improved, but the ability to optimize charging profiles and reduce degradation is limited
Solution Approach 1:
The patent transitions from fixed, pre-determined parameters in conventional empirical models to dynamic, time-varying parameters in physics-based models. The system continuously updates parameters like diffusion coefficients and reaction rates based on current battery state (temperature, state of charge, aging), allowing the model to adapt to changing conditions and enable optimized charging profiles that maximize efficiency and minimize degradation throughout the battery's lifecycle
Data Source
AI summary
Electrochemical models for the lithium-ion battery are useful in predicting and controlling its performance. The values of the parameters in these models are vital to their accuracy. However, not all parameters can be measured precisely, especially when destructive methods are prohibited. In some embodiments of the present disclosure, a parameter estimation approach is used to estimate the open circuit potential of the positive electrode (Up) using piecewise linear approximation together with all the other parameters of a single particle model. Up and 10 more parameters may be estimated from a single discharge curve without knowledge of the electrode chemistry using a technique such as a genetic algorithm. Different case studies were presented for estimating Up with different types of parameters of the battery model. The estimated parameters were then validated by comparing simulations at different discharge rates with experimental data.