The State of Charge Estimation of Lithium-Ion Batteries Based on a Proportional-Integral Observer
Abstract
With the development of electric drive vehicles (EDVs), the state-of-charge (SOC) estimation for lithium-ion (Li-ion) batteries has become increasingly more important. Based on the analysis of some of the most popular model-based SOC estimation methods, the proportional-integral (PI) observer is proposed to estimate the SOC of lithium-ion batteries in EDVs. The structure of the proposed PI observer is analyzed, and the convergence of the estimation method with model errors is verified. To demonstrate the superiority and compensation properties of the proposed PI observer, the simple-structure RC battery model is utilized to model the Li-ion battery. To validate the results of the proposed PI-based SOC estimation method, the experimental battery test bench is established. In the validation, the urban dynamometer driving schedule (UDDS) drive cycle is utilized, and the PI-based SOC estimation results are found to agree with the reference SOC, generally within the 2% error band for both the known and unknown initial SOC cases.
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Due to intrinsic peculiarities of ECMs, there is deficiency in capturing non-linear battery behaviors induced by load variations, which will undermine SOE estimation accuracy if ECMs work alone under strenuous loads.
“Additionally, due to the intrinsical peculiarities of ECMs, there is some deficiency in capturing the non -linear battery behaviors induced by the load variations and will undermine the SOE estimation accuracy if ECMs work alone under strenuous loads.”
From A Practical Lithium-Ion Battery Model for State of Energy and Voltage Responses Prediction Incorporating Temperature and Ageing Effects (2018) · cites this paper as [31]
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- Authors
- Xu, J., Mi, C. C., Cao, B., Deng, J., Chen, Z., & Li, S.
- Affiliations
- Xi'an Jiaotong University (CN)
- Dept. of Electr. & Comput. Eng., Univ. of Michigan, Dearborn, MI, USA
- University of Michigan (US)
- Venue
- IEEE Transactions on Vehicular Technology
- Published
- 2014-05
- Volume
- 63
- Issue
- 4
- Pages
- 1614-1621
- ISSN
- 0018-9545 (ISSN-L)
- 1939-9359
- OpenAlex
- W2030615475
- Cited by
- 367
- References
- 30
- Citations by year
- 2026: 16 · 2025: 25 · 2024: 36 · 2023: 36 · 2022: 36 · 2021: 31 · 2020: 39 · 2019: 26 · 2018: 29 · 2017: 32 · 2016: 37 · 2015: 17 · 2014: 5 · 2013: 2
- FWCI
- 31.66
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Vehicular Technology (publishedVersion)
- Funders
- DOE/Chrysler (EE0002720)
- China Scholarship Council
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Advanced Battery Technologies Research
- Physical Sciences › Engineering › Automotive Engineering › Electric and Hybrid Vehicle Technologies
- Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
- Keywords
- state of charge estimation, lithium-ion batteries, proportional-integral observer, electrified vehicles, model error
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