Jointly Estimation Method of the SOC and SOH of Lithium-ion Battery based on Fractional Order Multi-Innovation Dual Unscented Kalman Filter
Author:
Affiliation:
1. Henan University,School of Artificial Intelligence,Zhengzhou,China
2. International Joint Research Laboratory for Cooperative Vehicular Networks of Henan
3. Henan University Henan University,Shenzhen Research Institute,Shenzhen,China
Funder
Technology Development
Education Department of Henan Province
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9968313/9968303/09968585.pdf?arnumber=9968585
Reference14 articles.
1. Battery Parameter Evaluation Using Unscented Kalman Filter for Electric Vehicle Drive Cycles
2. A New State of Charge Estimation Method for Lithium-Ion Battery Based on the Fractional Order Model
3. A novel online identification algorithm of lithium‐ion battery parameters and model order based on a fractional order model
4. Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Cataclysmic Mutation Genetic Algorithm and Support Vector Regression
5. A Novel Open Circuit Voltage Based State of Charge Estimation for Lithium-Ion Battery by Multi-Innovation Kalman Filter
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1. A Novel Method for SoC Estimation of Lithium-Ion Batteries Based on Kalman Filter in Electric Vehicle;International Journal of Advanced Natural Sciences and Engineering Researches;2023-06-20
2. A Single-Stage Differential Boost Inverter with Modified SPWM Control for BESS Applications;2023 11th International Conference on Power Electronics and ECCE Asia (ICPE 2023 - ECCE Asia);2023-05-22
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