A Generalized SOC-OCV Model for Lithium-Ion Batteries and the SOC Estimation for LNMCO Battery
By Caiping Zhang, Jiuchun Jiang, Linjing Zhang, Sijia Liu, Le Yi Wang, Poh Chiang Loh. 2016
192 citations recorded by the source corpus.
A state-of-charge (SOC) versus open-circuit-voltage (OCV) model developed for batteries should preferably be simple, especially for real-time SOC estimation. It should also be capable of representing different types of lithium-ion batteries (LIBs), regardless of temperature change and battery degradation. It must therefore be generic, robust and adaptive, in addition to being accurate. These challenges have now been addressed by proposing a generalized SOC-OCV model for representing a few most widely used LIBs. The model is developed from analyzing electrochemical processes of the LIBs, before arriving at the sum of a logarithmic, a linear and an exponential function with six parameters. Values for these parameters are determined by a nonlinear estimation algorithm, which progressively shows that only four parameters need to be updated in real time. The remaining two parameters can be kept constant, regardless of temperature change and aging. Fitting errors demonstrated with different types of LIBs have been found to be within 0.5%. The proposed model is thus accurate, and can be flexibly applied to different LIBs, as verified by hardware-in-the-loop simulation designed for real-time SOC estimation.
Subfields: Automotive Engineering, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/2adbf859c8bca38b81d4d28fff9798e959050815
How researchers see this paper
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In Automotive Engineering
- Moh Yamani Idna Idris
- Najoua Essoukri Ben Amara
- Saad Mekhilef
- Prashant Shrivastava
- Bilal Manai
- Sabeur Jemmali
- Tey Kok Soon
- Ines Baccouche
In Electrical and Electronic Engineering
- Moh Yamani Idna Idris
- Najoua Essoukri Ben Amara
- Saad Mekhilef
- Prashant Shrivastava
- Bilal Manai
- Sabeur Jemmali
- Tey Kok Soon
- Ines Baccouche
Citations in the corpus
- Improved OCV Model of a Li-Ion NMC Battery for Online SOC Estimation Using the Extended Kalman Filter (2017, background): “2016 [20] combined Model 1st order PI Observer 5% Tran et al.”
- Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries (2019, methodology): “Despite its simple computation, this method is not suitable for online SOC estimation because of its large error accumulation and the need for an initial SOC value [74].”