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Fast intelligent battery charging: neural-fuzzy approach

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3 Author(s)
Ullah, Z. ; Nat. Semicond. Corp., USA ; Burford, B. ; Dillip, S.

This paper focuses on the design of a super fast battery charger based on National's proprietary neural network based NeuFuz technology. In this application, we have used a NiCd battery pack as the test vehicle. However, this technology can be extended to other chemistries such as Ni-MH, Li-ion, etc. This technology allows the designer to accurately model the charge controller using a neural network, based on battery charge characteristics provided by the manufacturer. This approach continuously monitors the battery status, and modifies the charge current accordingly. It also eliminates the need for standard charge termination methods used in today's conventional chargers. The result is super fast charging in 20 to 30 minutes, and increased battery life. A low cost embedded controller (COP8) performs all the fuel-gauging and charge control functions by processing data obtained from the battery circuitry

Published in:

Aerospace and Electronic Systems Magazine, IEEE  (Volume:11 ,  Issue: 6 )