Battery State of Charge Estimation Using Adaptive Extended Kalman Filter

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Solution Overview

Problem

Existing methods for estimating the state of charge of secondary batteries, such as ampere counting and Extended Kalman Filter (EKF), face accuracy issues due to degradation over time, especially when batteries are used under harsh conditions, making it difficult to accurately update parameters like capacity and resistance.

Innovation Solution

An apparatus and method using an Extended Kalman Filter that measures voltage and current, with a control unit implementing a state equation to update the state of charge and polarization voltage, and an output equation to predict battery voltage, while adjusting noise levels to improve estimation accuracy, especially during key-off states.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If ampere counting is used to estimate state of charge, then the method is simple to implement, but accuracy deteriorates over time due to sensor error accumulation

Engineering Contradiction:

Improvesimplicity of implementationVSAvoidstate of charge estimation accuracy

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The patent implements a feedback mechanism by using the estimated state of charge to update EKF parameters adaptively. The system continuously monitors the battery state and adjusts the EKF parameters based on the estimated SOC and state of health, creating a closed-loop system that corrects accumulated errors over time.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent changes the parameters of the EKF algorithm adaptively based on battery degradation. Specifically, it updates the capacity and resistance parameters of the battery model according to the estimated state of health, allowing the system to maintain accuracy as the battery ages and its characteristics change.

Inventive Principle:

Principle #35Parameter changes

2Measurement precision

If Extended Kalman Filter is used to estimate state of charge, then estimation accuracy is improved, but accuracy deteriorates as battery degrades due to parameter changes

Engineering Contradiction:

Improvestate of charge estimation accuracyVSAvoidestimation reliability under degradation

Core Design Contradiction:

Measurement precisionVSReliability

Solution Approach 1:

The patent makes the EKF parameters dynamic rather than static. The capacity and resistance parameters are updated adaptively based on the estimated state of health, allowing the system to respond to battery degradation in real-time. This dynamic adjustment maintains the reliability of SOC estimation as the battery ages.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system performs self-updating of its parameters based on its own operational data. By using the estimated SOC and current battery characteristics to update the EKF parameters, the system serves itself by automatically adapting to degradation without external intervention.

Inventive Principle:

Principle #25Self-service

3Measurement precision

If EKF parameters are updated according to state of health, then estimation accuracy is maintained, but it is difficult to accurately estimate state of health during battery use

Engineering Contradiction:

Improvestate of charge estimation accuracyVSAvoidstate of health estimation difficulty

Core Design Contradiction:

Measurement precisionVSDifficulty of detecting and measuring

Solution Approach 1:

The patent uses the EKF algorithm as an intermediary to indirectly estimate the state of health. Instead of directly measuring difficult-to-obtain state of health parameters, the system uses the EKF to estimate SOC and then derives state of health information from the relationship between estimated and actual battery characteristics, making the measurement process feasible.

Inventive Principle:

Principle #24Intermediary (Mediator)

4Reliability

If EKF parameters are updated adaptively, then robustness against degradation is improved, but computational complexity increases

Engineering Contradiction:

Improverobustness against battery degradationVSAvoidcomputational complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent applies partial updating of EKF parameters rather than complete re-estimation. By selectively updating only the necessary parameters (capacity and resistance) based on state of health estimates, the system achieves improved robustness without the full computational burden of complete parameter re-estimation.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS10261134B2Apparatus for estimating charge state of secondary battery and method therefor

Publication Date: 2019.04.16 LG ENERGY SOLUTION LTD

AI summary

Apparatus for estimating charge state of secondary battery and method therefor are disclosed. The apparatus includes a control unit configured to estimate the state of charge of the secondary battery by repeatedly performing an algorithm of the Extended Kalman Filter by using a state equation that time-updates a state parameter including the state of charge of the secondary battery and a polarization voltage of the secondary battery, and an output equation that predicts the voltage of the secondary battery using an open circuit voltage according to the state of charge, the polarization voltage, and an internal resistance voltage generated by an internal resistance of the secondary battery, and the control unit increases a difference between state of charge noise and polarization voltage noise of the Extended Kalman Filter when the secondary battery becomes key-off state.