State of Health Estimation for Lithium-ion Battery Based on D-UKF

다국어 초록 (Multilingual Abstract)

This paper considers an accurate estimation method of State of Health (SOH) for lithium battery. An improved battery model is proposed which is based on equivalent circuit model and battery internal electrochemical characteristics. In our study, Double Unscented Kalman Filtering (D-UKF) algorithm is designed to calculate State of Charge (SOC) and SOH of lithium battery at the same time. The feature of our new method is SOH estimation model is derived based on battery internal resistances. The Ohmic resistance (one of internal resistances) can be identified online based on D-UKF algorithm. Two filters defined as UKF1 and UKF2 are working together to calculate the real-value of SOC and Ohmic resistance to obtain final SOH value. The experimental results indicate that our new battery model considers different value of battery internal resistances on different working condition (as different voltages, different currents). Besides, our study verifies the performance and feasibility of new estimation method based on D-UKF. This new algorithm has the practical value to further study for other types of lithium battery.

목차 (Table of Contents)

• Abstract
• 1. Introduction
• 2. Principle of UKF Algorithm
• 3. Comprehensive Battery Model
• 3.1. New Type of Circuit Model for Lithium Battery
• 3.2. Online Estimation Model for Battery Ohmic Resistance
• 4. SOH Estimation Method for Lithium Battery
• 4.1. Double UKF Algorithm for SOH Estimation
• 4.2. Online Estimation Method for SOH
• 5. Battery SOH Estimation Based On D-UKF Algorithm
• 5.1 R0 Estimation
• 5.2 SOH Estimation Model
• 5.3 SOH Estimation Algorithm Based on D-UKF
• 6. The Experimental Results and Its Analysis
• 6.1 Test Setup
• 6.2 Experimental Results
• 6.3 Experimental Verification of D-UKF
• 7. Conclusion and Future Work
• Acknowledgements
• References