A new battery available capacity indicator for electric vehicles using neural network

W. X. Shen; C. C. Chan; Wai Chau Edward Lo; K. T. Chau

doi:10.1016/S0196-8904(01)00078-4

A new battery available capacity indicator for electric vehicles using neural network

W. X. Shen, C. C. Chan, Wai Chau Edward Lo, K. T. Chau

Research output: Journal article publication › Journal article › Academic research › peer-review

125 Citations (Scopus)

Abstract

The ability to calculate the battery available capacity (BAC) for electric vehicles (EVs) is very important. Knowing the BAC and, thus, the driving range cannot only prevent EVs from being stranding on the road but also optimize the utilization of the battery energy storage in EVs. In order to determine the BAC, this paper presents a new neural network (NN) model of the lead-acid battery, based on the battery discharge current and temperature. Comparisons between the calculated BAC from the NN model and the measured BAC from experiments show good agreement. Furthermore, this new approach can readily be extended to the calculation of the BAC for other types of batteries.

Original language	English
Pages (from-to)	817-826
Number of pages	10
Journal	Energy Conversion and Management
Volume	43
Issue number	6
DOIs	https://doi.org/10.1016/S0196-8904(01)00078-4
Publication status	Published - 1 Apr 2002
Externally published	Yes

Keywords

Battery available capacity
Electric vehicles
Neural network model

ASJC Scopus subject areas

Renewable Energy, Sustainability and the Environment
Nuclear Energy and Engineering
Fuel Technology
Energy Engineering and Power Technology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

More information

10.1016/S0196-8904(01)00078-4

Cite this

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title = "A new battery available capacity indicator for electric vehicles using neural network",

abstract = "The ability to calculate the battery available capacity (BAC) for electric vehicles (EVs) is very important. Knowing the BAC and, thus, the driving range cannot only prevent EVs from being stranding on the road but also optimize the utilization of the battery energy storage in EVs. In order to determine the BAC, this paper presents a new neural network (NN) model of the lead-acid battery, based on the battery discharge current and temperature. Comparisons between the calculated BAC from the NN model and the measured BAC from experiments show good agreement. Furthermore, this new approach can readily be extended to the calculation of the BAC for other types of batteries.",

keywords = "Battery available capacity, Electric vehicles, Neural network model",

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AU - Chan, C. C.

AU - Lo, Wai Chau Edward

AU - Chau, K. T.

PY - 2002/4/1

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N2 - The ability to calculate the battery available capacity (BAC) for electric vehicles (EVs) is very important. Knowing the BAC and, thus, the driving range cannot only prevent EVs from being stranding on the road but also optimize the utilization of the battery energy storage in EVs. In order to determine the BAC, this paper presents a new neural network (NN) model of the lead-acid battery, based on the battery discharge current and temperature. Comparisons between the calculated BAC from the NN model and the measured BAC from experiments show good agreement. Furthermore, this new approach can readily be extended to the calculation of the BAC for other types of batteries.

AB - The ability to calculate the battery available capacity (BAC) for electric vehicles (EVs) is very important. Knowing the BAC and, thus, the driving range cannot only prevent EVs from being stranding on the road but also optimize the utilization of the battery energy storage in EVs. In order to determine the BAC, this paper presents a new neural network (NN) model of the lead-acid battery, based on the battery discharge current and temperature. Comparisons between the calculated BAC from the NN model and the measured BAC from experiments show good agreement. Furthermore, this new approach can readily be extended to the calculation of the BAC for other types of batteries.

KW - Battery available capacity

KW - Electric vehicles

KW - Neural network model

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JO - Energy Conversion and Management

JF - Energy Conversion and Management

IS - 6

ER -

A new battery available capacity indicator for electric vehicles using neural network

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

More information

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