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On-line scheme for parameter estimation of nonlinear lithium ion battery equivalent circuit models using the simplified refined instrumental variable method for a modified Wiener continuous-time model
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Allafi, Walid, Uddin, Kotub, Zhang, Cheng, Mazuir Raja Ahsan Sha, Raja and Marco, James (2017) On-line scheme for parameter estimation of nonlinear lithium ion battery equivalent circuit models using the simplified refined instrumental variable method for a modified Wiener continuous-time model. Applied Energy, 204 . pp. 497-508. doi:10.1016/j.apenergy.2017.07.030 ISSN 0306-2619.
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Official URL: http://dx.doi.org/10.1016/j.apenergy.2017.07.030
Abstract
The accuracy of identifying the parameters of models describing lithium ion batteries (LIBs) in typical battery management system (BMS) applications is critical to the estimation of key states such as the state of charge (SoC) and state of health (SoH). In applications such as electric vehicles (EVs) where LIBs are subjected to highly demanding cycles of operation and varying environmental conditions leading to non-trivial interactions of ageing stress factors, this identification is more challenging. This paper proposes an algorithm that directly estimates the parameters of a nonlinear battery model from measured input and output data in the continuous time-domain. The simplified refined instrumental variable method is extended to estimate the parameters of a Wiener model where there is no requirement for the nonlinear function to be invertible. To account for nonlinear battery dynamics, in this paper, the typical linear equivalent circuit model (ECM) is enhanced by a block-oriented Wiener configuration where the nonlinear memoryless block following the typical ECM is defined to be a sigmoid static nonlinearity. The nonlinear Weiner model is reformulated in the form of a multi-input, single-output linear model. This linear form allows the parameters of the nonlinear model to be estimated using any linear estimator such as the well-established least squares (LS) algorithm. In this paper, the recursive least square (RLS) method is adopted for online parameter estimation. The approach was validated on experimental data measured from an 18650-type Graphite/Lithium-Nickel-Cobalt-Aluminium-Oxide (C6/LiNiCoAlO2) lithium-ion cell. A comparison between the results obtained by the proposed method and by nonparametric frequency-based approaches for obtaining the model parameters is presented. It is shown that although both approaches give similar estimates, the advantages of the proposed method are (i) the simplicity by which the algorithm can be employed on-line for updating nonlinear equivalent circuit model (NL-ECM) parameters and (ii) the improved convergence efficiency of the on-line estimation.
Item Type: | Journal Article | ||||||||
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Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering | ||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | ||||||||
Library of Congress Subject Headings (LCSH): | Lithium ion batteries, Electric vehicles | ||||||||
Journal or Publication Title: | Applied Energy | ||||||||
Publisher: | Elsevier BV | ||||||||
ISSN: | 0306-2619 | ||||||||
Official Date: | 15 October 2017 | ||||||||
Dates: |
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Volume: | 204 | ||||||||
Page Range: | pp. 497-508 | ||||||||
DOI: | 10.1016/j.apenergy.2017.07.030 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||
Date of first compliant deposit: | 26 July 2017 | ||||||||
Date of first compliant Open Access: | 26 July 2017 | ||||||||
Funder: | Engineering and Physical Sciences Research Council (EPSRC) | ||||||||
Grant number: | EP/M507143/1, EP/N001745/1, EP/P511432/1 |
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