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Remaining energy estimation for lithium-ion batteries via Gaussian mixture and Markov models for future load prediction
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Faraji Niri, Mona, Bui, Truong Minh Ngoc, Dinh, Truong Quang, Hosseinzadeh, Elham, Yu, Tung Fai and Marco, James (2020) Remaining energy estimation for lithium-ion batteries via Gaussian mixture and Markov models for future load prediction. Journal of Energy Storage . doi:10.1016/j.est.2020.101271 ISSN 2352-152X.
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WRAP-remaining-energy-estimation-lithium-ion-batteries-via-Gaussian-mixture-Markov-models-future-load-prediction-Faraji-Niri-2020.pdf - Accepted Version - Requires a PDF viewer. Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. Download (6Mb) | Preview |
Official URL: https://doi.org/10.1016/j.est.2020.101271
Abstract
Other than upgrading the energy storage technology employed within electric vehicles (EVs), improving the driving range estimation methods will help to reduce the phenomena, known as range anxiety. The remaining discharge energy (RDE) of the battery affects the remaining driving range of the vehicle directly and its accurate calculation is crucial. In this paper a novel approach for the RDE calculation of the battery is proposed. First a stochastic load prediction algorithm is prepared via a Markov model and Gaussian mixture data clustering. Then, the load prediction algorithm is connected to the battery second order equivalent circuit model (ECM) coupled with a bulk parameter thermal model. Based on the extrapolated load and the battery dynamics, the battery future temperature conditions, future parameter variations and its internal states are predicted. Finally, the battery end of discharge time is prognosed and its RDE is calculated iteratively. In order to prove the proposed concept, lithium-ion battery cells are selected and the performance of the method is validated experimentally under real-world dynamic current charge/discharge profiles.
| Item Type: | Journal Article | ||||||||
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| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | ||||||||
| Journal or Publication Title: | Journal of Energy Storage | ||||||||
| Publisher: | Elsevier | ||||||||
| ISSN: | 2352-152X | ||||||||
| Official Date: | April 2020 | ||||||||
| Dates: |
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| DOI: | 10.1016/j.est.2020.101271 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||
| Date of first compliant deposit: | 25 February 2020 | ||||||||
| Date of first compliant Open Access: | 25 February 2021 |
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