Battery State of Charge Estimator Using RC Circuit Regression

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Solution Overview

Problem

Current battery state estimation methods are not robust and adaptive enough to accurately predict the future behavior of energy storage devices like batteries, especially in varying temperature and state of charge conditions, which can lead to inefficient vehicle operations and potential engine shutdowns.

Innovation Solution

The method employs real-time linear regression using an equivalent RC circuit modeled from electrochemical impedance spectroscopy data, processed with algorithms like weighted recursive least squares (WRLS) or Kalman filter, to provide a robust and fast-adapting impedance response estimator, preventing engine shutdown by maintaining accurate state of charge monitoring.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional battery state estimation methods are used, then the system is simpler to implement, but the accuracy and adaptability to varying temperature and state of charge conditions deteriorates

Engineering Contradiction:

Improvebattery state estimation accuracyVSAvoidestimation system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent introduces an equivalent RC circuit as an intermediary model between the battery and the estimation algorithm. This RC circuit, characterized by resistance R and capacitance C parameters, serves as a mediator that translates complex battery electrochemical behavior into a simplified electrical model that can be accurately estimated using linear regression, thereby improving measurement precision without proportionally increasing system complexity

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces traditional complex battery state estimation methods with a simplified electrical circuit model approach. By substituting the mechanical/electrochemical battery system with an equivalent RC electrical circuit model, the system achieves more accurate state estimation through standard electrical measurement techniques and linear regression algorithms

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Adaptability or versatility

If real-time linear regression with RC circuit modeling is implemented, then the adaptability to varying conditions improves, but the computational complexity and processing requirements increase

Engineering Contradiction:

Improveadaptability to temperature and state of charge variationsVSAvoidcomputational algorithm complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent implements a dynamic estimation system where the RC circuit parameters (R and C) are continuously updated in real-time using linear regression algorithms. This dynamic approach allows the model to adapt to changing battery conditions such as temperature variations and state of charge changes, improving versatility while maintaining manageable computational complexity through efficient recursive least squares or Kalman filter methods

Inventive Principle:

Principle #15Dynamics

3Speed

If voltage-based Battery State Estimation data is processed with linear regression, then the response time and adaptability improve, but the measurement precision requirements increase

Engineering Contradiction:

Improveresponse time of state estimationVSAvoidvoltage measurement precision

Core Design Contradiction:

SpeedVSMeasurement precision

Solution Approach 1:

The patent performs preliminary action by pre-characterizing the battery's equivalent RC circuit parameters through offline electrochemical impedance spectroscopy (EIS) measurements. This preliminary characterization establishes baseline R and C values that are then used in real-time estimation, allowing for faster response time during operation while reducing the precision requirements for real-time voltage measurements since the heavy characterization work was done beforehand

Inventive Principle:

Principle #10Preliminary action

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 approach enables accurate battery state estimation, ensuring efficient vehicle operations by preventing unnecessary engine shutdowns and optimizing battery performance across a range of temperatures and states of charge.

Implementation Method 1

using real-time linear regression, which may be a method of estimating future behavior of a system based on current and previous data points

Methodology Applied

Scientific EffectLinear regression:

Implementation Method 2

a RC circuit which is modeled based on electrochemical impedance spectroscopy data from an energy storage device

Methodology Applied

Scientific EffectElectrochemical impedance spectroscopy:

Data Source

PatentUS10288693B2State of charge estimator and methods of making and using the same

Publication Date: 2019.05.14 GM GLOBAL TECHNOLOGY OPERATIONS LLC

AI summary

A number of variations include a method, which may include using at least a segment of voltage-based Battery State Estimation data, and using real-time linear regression, which may be a method of estimating future behavior of a system based on current and previous data points, to provide a robust and fast-adapting impedance response approximator. Linear regression may be performed by forming an RC circuit which is “equivalent” to electrochemical impedance spectroscopy data and processing the runtime values of that RC circuit using any number of known real-time linear regression algorithms including, but not limited, to a weighted recursive least squares (WRLS), Kalman filter or other means.