Novel co‐estimation strategy based on forgetting factor dual particle filter algorithm for the state of charge and state of health of the lithium‐ion battery

Author:

Ren Pu1ORCID,Wang Shunli1,Huang Junhan1ORCID,Chen Xianpei1,He Mingfang1ORCID,Cao Wen1

Affiliation:

1. School of Information Engineering Southwest University of Science and Technology Mianyang China

Funder

China Scholarship Council

National Natural Science Foundation of China

Publisher

Wiley

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Reference51 articles.

1. Adaptive robust unscented Kalman filter with recursive least square for state of charge estimation of batteries;Havangi R;Electr Eng,2021

2. A novel fading memory square root UKF algorithm for the high‐precision state of charge estimation of high‐power Lithium‐ion batteries;Ji W;Int J Electrochem Sci,2021

3. Estimation of Lithium-Ion Batteries State-Condition in Electric Vehicle Applications: Issues and State of the Art

4. Prognostics for lithium-ion batteries using a two-phase gamma degradation process model

5. A novel remaining useful life prediction framework for lithium‐ion battery using grey model and particle filtering

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