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A Continuous-time L...
A Continuous-time LPV model for battery state-of-health estimation using real vehicle data
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- Andersson, Malin (author)
- KTH,Reglerteknik
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- Johansson, Mikael (author)
- KTH,Reglerteknik
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Klass, V. L. (author)
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(creator_code:org_t)
- Institute of Electrical and Electronics Engineers Inc. 2020
- 2020
- English.
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In: CCTA 2020 - 4th IEEE Conference on Control Technology and Applications. - : Institute of Electrical and Electronics Engineers Inc.. ; , s. 692-698
- Related links:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Subject headings
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- One approach for State-of-health estimation onboard electric vehicles is to train a data-driven virtual battery on operational data and use this model, rather than the actual battery, for performance tests. A temperature-dependent continuous-time output-error (OE) model is proposed as virtual battery and identified and validated on real operational data from electric buses. The proposed model is compared to discrete-time and parameter-invariant models and shows better performance on all data sets. In addition, the OE model structure is shown to be superior to a conventional Auto Regressive eXogenous (ARX) model for the purpose of modeling the battery voltage response. Finally, challenges regarding vehicle log data are identified and improvements to the model are suggested in order to capture observed un-modeled phenomena.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Maskinteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Mechanical Engineering (hsv//eng)
Keyword
- Continuous-time
- Li-ion battery
- LPV
- SOH
- System identification
- Battery management systems
- Continuous time systems
- Vehicles
- Auto-regressive
- Battery voltages
- Operational data
- Output errors
- Performance tests
- State of health
- Temperature dependent
- Secondary batteries
Publication and Content Type
- ref (subject category)
- kon (subject category)
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