EV battery state of charge: Neural network based estimation

被引：30

作者：

Affanni, A ^{[1
]}

Bellini, A ^{[1
]}

Concari, C ^{[1
]}

Franceschini, G ^{[1
]}

Lorenzani, E ^{[1
]}

Tassoni, C ^{[1
]}

机构：

[1] Univ Parma, Dipartimento Ingn Informaz, Parco Area Sci 181-A, I-43100 Parma, Italy

来源：

IEEE IEMDC'03: IEEE INTERNATIONAL ELECTRIC MACHINES AND DRIVES CONFERENCE, VOLS 1-3 | 2003年

关键词：

D O I：

10.1109/IEMDC.2003.1210310

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Different Electric Vehicles (EV) types have been recently developed with the aim of solving pollution problems caused by the emission of gasoline -powered engines. Environmental considerations promote the adoption of EV for urban transportation. As it is-well known one of the weakest points of electric vehicle is the battery system. Vehicle autonomy and therefore accurate detection of battery state of charge are among the main drawbacks that prevent the spread of electric vehicles in the consumer market. This paper deals with the analysis of battery state of charge: performances of a few sizes of batteries are analyzed and their state of charge is estimated with a Neural Network (NN) based system. The obtained results have been used to design a ion-lithium battery pack suitable for electric vehicles. The proposed system presents high capability of energy recovering in braking conditions, together with charge equalization, over and under voltage protection. Moreover a Neural Network based estimation of battery state of charge has been implemented in order to optimize autonomy instead of performances or vice-versa depending on journey.

引用

页码：684 / +

页数：2

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