Electric Vehicles Batteries Modeling Analysis Based on a Multiple Layered Perceptron Identification Approach 2015-36-0142
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.
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. Download Citation
Author(s):
Sender Rocha dos Santos, Thais Tóssoli de Sousa, Paulo de Tarso Peres, Maria de Fátima Negreli Campos Rosolem, Alex Pereira França
Affiliated:
Fundação Centro de Pesquisa e Desenvolvimento em Telecomun, Fundação Centro de Pesquisa e Desenvolvimento em Telecomunic
Pages: 10
Event:
24th SAE Brasil International Congress and Display
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Lead-acid batteries
Electric vehicles
Batteries
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