US-12626786-B2 - Method and system for predicting working conditions of lithium batteries

US12626786B2US 12626786 B2US12626786 B2US 12626786B2US-12626786-B2

Abstract

The invention discloses method and system for predicting working conditions of lithium batteries. The method includes performing a Fourier transform on a physicochemical state quantity distribution function of a solid-phase lithium battery to calculate a physicochemical state quantity distribution series function in a frequency domain and obtain a solid-phase physicochemical state quantity in the frequency domain according to the physicochemical state quantity distribution series function; performing a Laplace transform on a partial differential governing equation set of the solid-phase physicochemical state quantity to obtain a solid-phase ordinary differential equation set in a complex frequency domain and obtain an analytical solution in the time domain through an inverse Laplace transform; and calculating, according to the analytical solution, a predicted value of the working conditions of the solid-phase lithium battery at any location and at any time in the future.

Inventors

Danfei Gu
Pingchao Hao
Mingchen Jiang
Siyuan Chen
Weikun Wu
Pei Song
Enhai Zhao
Xiao Yan
Xiaohua Chen
Peng Ding

Assignees

Makesense Energy Technology Co., Limited

Dates

Publication Date: 20260512
Application Date: 20230607
Priority Date: 20220617

Claims (10)

1 . A method for predicting working conditions of lithium batteries, comprising: performing a Fourier transform on a physicochemical state quantity distribution function of a solid-phase lithium battery to calculate a physicochemical state quantity distribution series function in a frequency domain and obtain a solid-phase physicochemical state quantity in the frequency domain according to the physicochemical state quantity distribution series function, wherein the physicochemical state quantity distribution function is an equation expression of physical and chemical quantities of the solid-phase lithium battery that change continuously in space in a time domain, and wherein the physical and chemical quantities comprise at least one state quantity of physical parameters and chemical parameters of the solid-phase lithium battery; performing a Laplace transform on a partial differential governing equation set of the solid-phase physicochemical state quantity to obtain a solid-phase ordinary differential equation set in a complex frequency domain and obtain an analytical solution in the time domain through an inverse Laplace transform; and calculating, according to the analytical solution, a predicted value of the working conditions of the solid-phase lithium battery at any location and at any time in the future.
2 . The method of claim 1 , wherein said performing the Fourier transform on the physicochemical state quantity distribution function of the solid-phase lithium battery comprises: performing a cosine Fourier transform on the physicochemical state quantity distribution function of the solid-phase lithium battery before relaxation; and calculating the physicochemical state quantity distribution series function in the frequency domain.
3 . The method of claim 1 , wherein the partial differential governing equation set of the solid-phase physical chemical quantity comprises a governing equation, a boundary condition and an initial condition, wherein the governing equation is a mathematical expression that characterizes an electrochemical model of the solid-phase lithium battery for a spatial distribution of the physical and chemical quantities as a function of time, the boundary condition is an exchange condition of a solid phase and the outside, and the initial condition is an initial value of the physicochemical state quantity distribution function; and wherein said performing the Laplace transform on the partial differential governing equation set of the solid-phase physicochemical state quantity comprises: performing a frequency domain conversion on the governing equation and the boundary condition based on the Laplace transform to obtain a complex frequency domain governing equation and a complex frequency domain boundary condition, so as to obtain a solid-phase ordinary differential equation set in the complex frequency domain, wherein the complex frequency domain solid-phase ordinary differential equation set comprises the complex frequency domain governing equation, the complex frequency domain boundary condition and the physicochemical state quantity distribution series function in the frequency domain; and solving the complex frequency domain solid-phase ordinary differential equation set, and calculating the solved result using the inverse Laplace transform to obtain the analytical solution of infinite series in the time domain.
4 . The method of claim 1 , wherein said calculating the predicted value of the working conditions of the solid-phase lithium battery comprises: substituting spatial coordinates and future time of a state quantity to be solved into the corresponding analytical solution to calculate the predicted values of the working conditions of the solid-phase lithium battery at the future time and the location corresponding to the spatial coordinates.
5 . The method of claim 1 , wherein said calculating the predicted value of the working conditions of the solid-phase lithium battery comprises: comparing the predicted value of the working conditions with a corresponding threshold value; and generating prompt information for notification and early warning, when the predicted value of the working conditions exceeds the corresponding threshold value.
6 . A system for predicting working conditions of lithium batteries, comprising: a first calculation module, configured to perform a Fourier transform on a physicochemical state quantity distribution function of a solid-phase lithium battery to calculate a physicochemical state quantity distribution series function in a frequency domain and obtain a solid-phase physicochemical state quantity in the frequency domain according to the physicochemical state quantity distribution series function, wherein the physicochemical state quantity distribution function is an equation expression of physical and chemical quantities of the solid-phase lithium battery that change continuously in space in a time domain, and wherein the physical and chemical quantities comprise at least one state quantity of physical parameters and chemical parameters of the solid-phase lithium battery; a second calculation module, configured to perform a Laplace transform on a partial differential governing equation set of the solid-phase physicochemical state quantity to obtain a solid-phase ordinary differential equation set in a complex frequency domain and obtain an analytical solution in the time domain through an inverse Laplace transform; and a prediction module, configured to calculate a predicted value of the working conditions of the solid-phase lithium battery at any location and at any time in the future according to the analytical solution.
7 . The system of claim 6 , wherein the first calculating module comprises a first conversion unit, configured to: perform a cosine Fourier transform on the physicochemical state quantity distribution function of the solid-phase lithium battery before relaxation; and calculate the physicochemical state quantity distribution series function in the frequency domain.
8 . The system of claim 6 , wherein the partial differential governing equation set of the solid-phase physical chemical quantity comprises a governing equation, a boundary condition and an initial condition, wherein the governing equation is a mathematical expression that characterizes an electrochemical model of the solid-phase lithium battery for a spatial distribution of the physical and chemical quantities as a function of time, the boundary condition is an exchange condition of a solid phase and the outside, and the initial condition is an initial value of the physicochemical state quantity distribution function; and wherein the second calculation module comprises a second conversion unit, configured to perform a frequency domain conversion on the governing equation and the boundary condition based on the Laplace transform to obtain a complex frequency domain governing equation and a complex frequency domain boundary condition, so as to obtain a solid-phase ordinary differential equation set in the complex frequency domain, wherein the complex frequency domain solid-phase ordinary differential equation set comprises the complex frequency domain governing equation, the complex frequency domain boundary condition and the physicochemical state quantity distribution series function in the frequency domain; and an inverse Laplace calculation unit, configured to solve the complex frequency domain solid-phase ordinary differential equation set, and calculate the solved result using the inverse Laplace transform to obtain the analytical solution of infinite series in the time domain.
9 . The system of claim 6 , wherein the prediction module comprises: a prediction unit, configured to substitute spatial coordinates and future time of a state quantity to be solved into the corresponding analytical solution to calculate the predicted values of the working conditions of the solid-phase lithium battery at the future time and the location corresponding to the spatial coordinates.
10 . The system of claim 6 , further comprising: a comparison module, configured to compare the predicted value of the working conditions with a corresponding threshold value; and an alarm module, configured to generate prompt information for notification and early warning, when the predicted value of the working conditions exceeds the corresponding threshold value.

Description

CROSS-REFERENCE TO RELATED PATENT APPLICATION This application claims priority to and the benefit of Chinese Patent Application No. 202210689858.8 filed Jun. 17, 2022, which are incorporated herein in their entireties by reference. FIELD OF THE INVENTION The invention relates generally to the field of batteries, and more particularly to method and system for predicting working conditions of lithium batteries. BACKGROUND OF THE INVENTION In the context of global “carbon neutral”, the search for clean energy that can replace petroleum energy continues to heat up. Solar energy, tidal energy, wind energy, water energy, etc. are clean and sustainable energy sources, but the controllability of media that generate energy is relatively not very strong. Lithium batteries are currently a new generation of batteries, which have high energy density and long cycle life, and are widely used in mobile communications, digital technology, electric vehicles, energy storage and other fields. The demand for lithium batteries and materials thereof in the future is incalculable, and the corresponding upstream and downstream industrial chains have a huge market, which makes the research on lithium battery simulation a research hotspot. The current mainstream electrochemical model simulation methods use finite difference methods, finite element methods, finite volume methods, fitting function methods, and methods to simplify physical and chemical control conditions to simulate electrochemical models. Using discrete iterative solutions such as the finite difference methods, the finite element methods, and the finite volume methods requires high computational power on the computation end, and the calculation is slow, which make it impossible to perform electrochemical calculations of high-flux multi-batteries. However, the solution method using the fitting function methods and the methods of simplifying the physical and chemical control conditions is only an approximate solution and a simplified solution of the governing equation, and the accuracy of the solution is not high, which may bring cumulative errors to the actual applications. In the current battery early warning algorithms, the early warning of the battery is mostly based on threshold judgment of macroscopic quantity, or based on a black box obtained by machine learning of macroscopic quantity change and possibly occurring events through big data. However, in the actual lithium battery, each macroscopic physical quantity inside the lithium battery has a great relationship with whether the lithium battery can continuously and efficiently operate safely and healthily. Therefore, how to accurately predict the working condition of the lithium battery is a technical problem that needs to be solved urgently. SUMMARY OF THE INVENTION In view of the above-noted shortcomings of the prior art, one of the objectives of this invention is to provide lithium battery working condition prediction method and system to solve the technical problems that the future working condition of the lithium battery cannot be accurately predicted in the prior art, and further the thermal safety problem of the lithium battery under different working conditions cannot be prevented in time. In one aspect of the invention, the method comprises performing a Fourier transform on a physicochemical state quantity distribution function of a solid-phase lithium battery to calculate a physicochemical state quantity distribution series function in a frequency domain and obtain a solid-phase physicochemical state quantity in the frequency domain according to the physicochemical state quantity distribution series function, wherein the physicochemical state quantity distribution function is an equation expression of physical and chemical quantities of the solid-phase lithium battery that change continuously in space in a time domain, and wherein the physical and chemical quantities comprise at least one state quantity of physical parameters and chemical parameters of the solid-phase lithium battery; performing a Laplace transform on a partial differential governing equation set of the solid-phase physicochemical state quantity to obtain a solid-phase ordinary differential equation set in a complex frequency domain and obtain an analytical solution in the time domain through an inverse Laplace transform; and calculating, according to the analytical solution, a predicted value of the working conditions of the solid-phase lithium battery at any location and at any time in the future. In one embodiment, said performing the Fourier transform on the physicochemical state quantity distribution function of the solid-phase lithium battery comprises performing a cosine Fourier transform on the physicochemical state quantity distribution function of the solid-phase lithium battery before relaxation; and calculating the physicochemical state quantity distribution series function in the frequency domain. In one embodiment, the pa