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A Method for the Combined Estimation of Battery State of Charge and State of Health Based on Artificial Neural Networks
Open AccessArticle

Leveraging Cell Expansion Sensing in State of Charge Estimation: Practical Considerations

Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
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Energies 2020, 13(10), 2653; https://doi.org/10.3390/en13102653
Received: 11 April 2020 / Revised: 30 April 2020 / Accepted: 14 May 2020 / Published: 22 May 2020
(This article belongs to the Special Issue Energy Storage Systems for Electric Vehicles)
Measurements such as current and terminal voltage that are typically used to determine the battery’s state of charge (SOC) are augmented with measured force associated with electrode expansion as the lithium intercalates in its structure. The combination of the sensed behavior is shown to improve SOC estimation even for the lithium ion iron phosphate (LFP) chemistry, where the voltage–SOC relation is flat (low slope) making SOC estimation using measured voltage difficult. For the LFP cells, the measured force has a non-monotonic F–SOC relationship. This presents a challenge for estimation as multiple force values can correspond to the same SOC. The traditional linear quadratic estimator can be driven to an incorrect SOC value. To address these difficulties, a novel switching estimation gain is used based on determining the operating region that corresponds to the actual SOC. Moreover, a drift in the measured force associated with a shift of the cell SOC–expansion behavior over time is addressed with a bias estimator for the force signal. The performance of Voltage-based (V) and Voltage and Force-based (V&F) SOC estimation algorithms are then compared and evaluated against a desired ± 5 % absolute error bound of the SOC using a dynamic stress test current protocol that tests the proposed estimation scheme across wide range of SOC and current rates. View Full-Text
Keywords: state-of-charge estimation (SOC); linear quadratic estimator; lithium ion battery; iron phosphate; cell expansion; force state-of-charge estimation (SOC); linear quadratic estimator; lithium ion battery; iron phosphate; cell expansion; force
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Figueroa-Santos, M.A.; Siegel, J.B.; Stefanopoulou, A.G. Leveraging Cell Expansion Sensing in State of Charge Estimation: Practical Considerations. Energies 2020, 13, 2653.

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