Secondary Battery State Estimation Using Diffusion Parameter Identification
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Solution Overview
Problem
Existing state estimating devices for secondary batteries face challenges in accurately estimating battery parameters due to changes in battery state, leading to decreased estimation accuracy and potential delays and errors in deterioration assessment, particularly when using adaptive digital filters with linear equalization circuits.
Innovation Solution
A state estimating device for secondary batteries that includes a detecting unit, a battery state estimating unit, and a change rate estimating unit, which detects voltage, current, and temperature, and estimates parameter change rates using a battery model equation that accounts for diffusion processes, allowing for precise estimation of internal battery states and deterioration without requiring nonlinear adaptive digital filters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If an RC parallel circuit is used as an equalization circuit model to represent voltage changes, then the model can be implemented with simple circuit elements, but it is practically difficult to achieve sufficiently high accuracy with consideration given to the diffusion of the reaction-participating material inside the secondary battery
Solution Approach 1:
The patent changes the fundamental parameters of the battery model from simple RC circuit elements to electrochemical parameters including diffusion coefficient, reaction rate constant, and open-circuit voltage characteristics. This allows the model to accurately represent the diffusion of reaction-participating material while maintaining computational tractability through parameter identification from experimental data.
Solution Approach 2:
The patent replaces the mechanical/electrical RC circuit analogy with an electrochemical model based on mass transport and reaction kinetics. By substituting the electrical resistance-capacitance framework with diffusion-reaction equations, the model can capture the true physics of material diffusion inside the battery without relying on approximate electrical analogies.
2Measurement precision
If an RC ladder circuit formed of a series connection of a plurality of RC parallel circuits is used as the equalization circuit model to obtain sufficiently high estimation accuracy, then the estimation accuracy expressing the actual diffusion process is improved, but the number of parameters to be estimated by the adaptive digital filter increases, which results in a problem of increase in arithmetic quantity
Solution Approach 1:
The patent extracts the essential diffusion characteristics from complex RC ladder circuits by identifying and modeling only the key electrochemical parameters: diffusion coefficient, reaction rate constant, and open-circuit voltage. This extraction reduces the parameter set from multiple RC time constants to a smaller set of physically meaningful parameters that can be estimated with lower arithmetic complexity.
Solution Approach 2:
Instead of using multiple RC circuits to approximate diffusion behavior, the patent inverts the approach by directly modeling the diffusion process using electrochemical equations. This inversion allows accurate representation of diffusion with fewer parameters by capturing the underlying physics rather than approximating it with electrical analogies.
3Productivity
If battery parameters are estimated without considering the diffusion of reaction-participating material, then the estimation process is simpler and faster, but it is practically difficult to achieve sufficiently high accuracy
Solution Approach 1:
The patent performs preliminary identification of electrochemical parameters (diffusion coefficient, reaction rate constant, open-circuit voltage characteristics) from experimental data before using them in the battery model. This preliminary action allows the model to accurately represent diffusion effects during normal operation without requiring complex real-time estimation of diffusion parameters, thus maintaining both accuracy and computational efficiency.
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
This solution enables stable estimation of battery parameter changes independent of rapid changes in battery state, reducing estimation delays and errors, and allows for accurate assessment of battery deterioration using parameter change rates, thereby improving overall estimation accuracy.
Implementation Method 1
the diffusion of the reaction-participating material (lithium) in the active material is governed by a diffusion equation of polar coordinates handling the active materials as spheres
Implementation Method 2
a detecting unit that detects a voltage, a current and a temperature of the secondary battery
Data Source
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Figure 5
AI summary
A battery state estimating unit (110) estimates an internal state of a secondary battery according to a battery model equation in every arithmetic cycle, and calculates an SOC based on a result of the estimation. A parameter characteristic map (120) stores a characteristic map based on a result of actual measurement performed in an initial state (in a new state) on a parameter diffusion coefficient (Ds) and a DC resistance (Ra) in the battery model equation. The parameter change rate estimating unit (130) estimates a DC resistance change rate (gr) represented by a ratio of a present DC resistance (Ra) with respect to a new-state parameter value (Ran) by parameter identification based on the battery model equation, using battery data (Tb, Vb and Ib) measured by sensors as well as the new-state parameter value (Ran) of the DC resistance corresponding to the present battery state and read from the parameter characteristic map (120).