Battery Voltage Relaxation Modeling With Diffusion-Based OCV Estimation
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Solution Overview
Problem
Existing models struggle to precisely estimate the voltage relaxation process of storage batteries, especially in long stopped states due to dominance of voltage relaxation processes with longer time constants, making it difficult to estimate model parameters based on short time-series data.
Innovation Solution
A characteristic estimation device and method for storage batteries that includes a voltage detection unit, time-series data acquisition unit, and a model provision unit using a storage battery model with an OCV term and an interparticle diffusion term based on a one-dimensional diffusion equation to estimate model parameters from acquired time-series data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a multiple-series model with CR parallel elements is used to express voltage relaxation process, then the model can represent electrochemical response through first-order delay elements, but the model cannot highly precisely estimate voltage relaxation process when stopped state duration varies significantly
Solution Approach 1:
The patent changes the mathematical form of the model from first-order delay elements (exponential functions) to half-order delay elements based on the fundamental solution of the one-dimensional diffusion equation. This parameter change in the model structure enables it to capture the voltage relaxation behavior across a wider range of time constants, thereby improving adaptability to different stopped state durations while maintaining high estimation precision.
2Productivity
If model parameters are estimated based on time-series data from short stopped periods, then the estimation process is efficient, but the model parameters cannot accurately represent voltage relaxation process in long stopped states
Solution Approach 1:
The patent replaces the traditional mechanical/electrical analogy model (CR parallel elements with first-order delay) with a diffusion-based model (half-order delay elements from one-dimensional diffusion equation). This substitution allows the model to inherently capture long-term diffusion processes occurring in the battery particles, enabling accurate parameter estimation from short stopped period data while maintaining validity for long stopped states.
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
Enables highly precise estimation of the voltage relaxation process, allowing for accurate modeling and prediction of long-term voltage relaxation and OCV, reducing the need for pre-acquired model parameter values and improving industrial application efficiency.
Implementation Method 1
an interparticle diffusion term which is based on a fundamental solution of a one-dimensional diffusion equation expressing ion diffusion among particles forming an electrode of the storage battery
Data Source
AI summary
Provided is a characteristic estimation device for a storage battery including: a voltage detection unit configured to detect a terminal voltage of the storage battery; a time-series data acquisition unit configured to acquire time-series data on the terminal voltage in a stopped state of the storage battery; a model provision unit configured to provide a storage battery model; and a model parameter estimation unit configured to estimate a model parameter of the storage battery model based on the time-series data on the terminal voltage acquired by the time-series data acquisition unit and on the storage battery model provided by the model provision unit. The storage battery model includes an OCV term for expressing OCV of the storage battery and an interparticle diffusion term which is based on a fundamental solution of a one-dimensional diffusion equation expressing ion diffusion among particles forming electrodes of the storage battery.