State of available capacity estimation for lead-acid batteries in electric vehicles using neural network

Energy Conversion and Management ◽

10.1016/j.enconman.2006.06.023 ◽

2007 ◽

Vol 48 (2) ◽

pp. 433-442 ◽

Author(s):

W.X. Shen

Keyword(s):

Neural Network ◽

Electric Vehicles ◽

Capacity Estimation ◽

Lead Acid Batteries ◽

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A Novel Residual Capacity Estimation Method Based on Extension Neural Network for Lead-Acid Batteries

Advances in Neural Networks – ISNN 2007 - Lecture Notes in Computer Science ◽

10.1007/978-3-540-72395-0_139 ◽

2007 ◽

pp. 1145-1154 ◽

Author(s):

Kuei-Hsiang Chao ◽

Meng-Hui Wang ◽

Chia-Chang Hsu

Keyword(s):

Neural Network ◽

Estimation Method ◽

Capacity Estimation ◽

Lead Acid Batteries ◽

Residual Capacity ◽

Residual Capacity Estimation ◽

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Residual capacity estimation of sealed lead-acid batteries for electric vehicles

Proceedings of Power Conversion Conference - PCC '97 ◽

10.1109/pccon.1997.638380 ◽

2002 ◽

Author(s):

T. Yanagihara ◽

A. Kawamura

Keyword(s):

Electric Vehicles ◽

Capacity Estimation ◽

Lead Acid Batteries ◽

Residual Capacity ◽

Residual Capacity Estimation ◽

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00/02641 The available capacity computation model based on artificial neural network for lead-acid batteries in electric vehicles

Fuel and Energy Abstracts ◽

10.1016/s0140-6701(00)96554-8 ◽

2000 ◽

Vol 41 (5) ◽

pp. 294

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Electric Vehicles ◽

Computation Model ◽

Model Based ◽

Lead Acid Batteries ◽

Artificial Neural ◽

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The available capacity computation model based on artificial neural network for lead–acid batteries in electric vehicles

Journal of Power Sources ◽

10.1016/s0378-7753(99)00502-9 ◽

2000 ◽

Vol 87 (1-2) ◽

pp. 201-204 ◽

Author(s):

C.C Chan ◽

E.W.C Lo ◽

Shen Weixiang

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Electric Vehicles ◽

Computation Model ◽

Model Based ◽

Lead Acid Batteries ◽

Artificial Neural ◽

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CMAC Neural Network Application on Lead-Acid Batteries Residual Capacity Estimation

Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence - Lecture Notes in Computer Science ◽

10.1007/978-3-540-74205-0_100 ◽

2007 ◽

pp. 961-970 ◽

Author(s):

Chin-Pao Hung ◽

Kuei-Hsiang Chao

Keyword(s):

Neural Network ◽

Capacity Estimation ◽

Lead Acid Batteries ◽

Cmac Neural Network ◽

Residual Capacity ◽

Network Application ◽

Residual Capacity Estimation ◽

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Specification for lead-acid batteries for the propulsion of light electric vehicles

10.3403/00256267 ◽

1991 ◽

Keyword(s):

Electric Vehicles ◽

Lead Acid Batteries ◽

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00/01380 High-rate, valve-regulated lead-acid batteries—suitable for hybrid electric vehicles?

Fuel and Energy Abstracts ◽

10.1016/s0140-6701(00)93110-2 ◽

2000 ◽

Vol 41 (3) ◽

pp. 155

Keyword(s):

Electric Vehicles ◽

Hybrid Electric Vehicles ◽

High Rate ◽

Lead Acid Batteries ◽

Hybrid Electric ◽

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The practical realisation of lead-acid batteries for electric vehicles

Lead 68 ◽

10.1016/b978-0-08-015644-6.50023-7 ◽

1969 ◽

pp. 249-252

Author(s):

G. UITENBROEK

Keyword(s):

Electric Vehicles ◽

Lead Acid Batteries ◽

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Valve-regulated lead/acid batteries for electric vehicles: present and future

Journal of Power Sources ◽

10.1016/0378-7753(95)02319-4 ◽

1996 ◽

Vol 59 (1-2) ◽

pp. 171-175 ◽

Author(s):

K. Suzuki ◽

K. Nishida ◽

M. Tsubota

Keyword(s):

Electric Vehicles ◽

Lead Acid Batteries ◽

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Estimation of the residual capacity of sealed lead-acid batteries by neural network

INTELEC - Twentieth International Telecommunications Energy Conference (Cat. No.98CH36263) ◽

10.1109/intlec.1998.793500 ◽

2002 ◽

Author(s):

T. Yamazaki ◽

K. Sakurai ◽

K. Muramoto

Keyword(s):

Neural Network ◽

Lead Acid Batteries ◽

Residual Capacity ◽

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