Gas-Liquid Dynamic Model for Accurate Battery SOC Estimation
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Solution Overview
Problem
Existing SOC estimation models for lithium-ion batteries face challenges with low adaptability, low estimation accuracy, high complexity, and high computational demands, failing to accurately describe the nonlinear relationship between SOC and OCV.
Innovation Solution
A gas-liquid dynamics model is introduced, which includes a cylindrical closed vessel with a pipe and valve, using ideal gas state equations and gas-liquid coexistence system equations to derive recursive formulas for SOC estimation, allowing for real-time online estimation with high accuracy and simplicity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If electrochemical model is used to reflect reaction mechanism inside battery, then characterization accuracy is improved, but computational complexity increases and time consumption increases
Solution Approach 1:
The patent extracts only the essential dynamic characteristics from the complex electrochemical model, using a simplified voltage source model with series resistance and parallel RC circuits. This extraction retains the core functionality of describing battery voltage-current-SOC relationships while removing unnecessary computational complexity, achieving a balance between accuracy and simplicity suitable for real-time applications.
Solution Approach 2:
The patent replaces the complex electrochemical field model with an equivalent electrical circuit model. By substituting chemical reaction mechanisms with electrical analogs (voltage sources, resistors, capacitors), the model maintains its ability to describe battery behavior while becoming computationally tractable for real-time SOC estimation in embedded systems.
2Measurement precision
If high-order RC circuit model is used to improve SOC estimation accuracy, then estimation accuracy is improved, but parameter recognition difficulty increases and calculation complexity increases
Solution Approach 1:
The patent optimizes the RC circuit order to 2nd or 3rd order, finding the optimal parameter range where additional complexity yields diminishing returns. The model uses parameter identification algorithms to determine optimal resistance and capacitance values, balancing estimation accuracy with computational efficiency and avoiding the excessive complexity of higher-order models.
3Productivity
If low-order RC circuit model is used to reduce calculation amount, then computational complexity is reduced, but SOC estimation accuracy deteriorates
Solution Approach 1:
The patent implements a dynamic RC circuit model where parameters (resistance, capacitance) can change based on operating conditions such as temperature, current rate, and SOC level. This dynamic adaptation allows the simplified low-order model to maintain higher accuracy across varying battery states while preserving computational efficiency for real-time applications.
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
The gas-liquid dynamic model achieves accurate SOC estimation with an error of less than 2% between 15% and 100% SOC, decouples SOC estimation from time, and reduces computational complexity, making it suitable for microcontroller implementation and practical applications.
Implementation Method 1
According to the gas-liquid coexistence system model, the ideal gas state equation, gas continuous motion equation and gas-liquid dissolution equilibrium equation are listed
Implementation Method 2
According to the gas-liquid coexistence system model, the ideal gas state equation, gas continuous motion equation and gas-liquid dissolution equilibrium equation are listed
Implementation Method 3
According to the gas-liquid coexistence system model, the ideal gas state equation, gas continuous motion equation and gas-liquid dissolution equilibrium equation are listed
Data Source
AI summary
A gas-liquid dynamic model-based accurate lithium-ion battery SOC estimation method, the gas-liquid dynamic model being a cylindrical closed container, a pipe and a valve that can be opened or closed being mounted at the top of the container, a liquid having a volume of Vw being held in the cylindrical container, and the remaining volume, V, being the volume of a gas having a pressure of P. According to the accurate SOC estimation method, a model, different from conventional RC equivalent circuit model and electrochemical model, is established from the perspective of a gas-liquid coexistence system. The method comprises the following steps: setting up an ideal gas state equation, a gas continuous motion equation, a gas-liquid dissolution equilibrium equation, etc. according to a gas-liquid coexistence system model; deriving steady state and transient state recursion formula of the gas-liquid coexistence system according to the model equations; performing intermittent charging and discharging stationary test on a certain model of battery; and fitting the expression of the relation between SOC and open circuit voltage, and recognizing parameter values of the gas-liquid coexistence system model, so as to achieve online estimation of a battery SOC value. The recursion formula is simple, has self-convergence characteristics, and can accurately describe the nonlinear characteristics of the battery.