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Electric Vehicles Batteries Modeling Analysis Based on a Multiple Layered Perceptron Identification Approach
Technical Paper
2015-36-0142
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
A reliable battery state estimation management system in electric vehicles greatly depends on the validity and generalizability of battery models. This paper presents a Li-ion and Lead Acid batteries neural model. This model does not consider battery details, bringing universality, which is suitable for parameters estimation of all battery kinds. The final model proposes describe the dynamic contributions due to open-circuit voltage, polarization time constants, electrochemical hysteresis, effects of temperature, state of charge and state of health.
Authors
- Sender Rocha dos Santos - Fundação Centro de Pesquisa e Desenvolvimento em Telecomun
- Thais Tóssoli de Sousa - Fundação Centro de Pesquisa e Desenvolvimento em Telecomunic
- Paulo de Tarso Peres - Fundação Centro de Pesquisa e Desenvolvimento em Telecomunic
- Maria de Fátima Negreli Campos Rosolem - Fundação Centro de Pesquisa e Desenvolvimento em Telecomunic
- Alex Pereira França - Fundação Centro de Pesquisa e Desenvolvimento em Telecomunic
Citation
dos Santos, S., de Sousa, T., de Tarso Peres, P., de Fátima Negreli Campos Rosolem, M. et al., "Electric Vehicles Batteries Modeling Analysis Based on a Multiple Layered Perceptron Identification Approach," SAE Technical Paper 2015-36-0142, 2015, https://doi.org/10.4271/2015-36-0142.Also In
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