Supervised Chaos Genetic Algorithm Based State of Charge Determination for LiFePO4 Batteries in Electric Vehicles

被引：3

作者：

Shen, Yanqing ^{[1
]}

机构：

[1] Chongqing Ind Polytech Coll, Chongqing, Peoples R China

来源：

ADVANCES IN MATERIALS, MACHINERY, ELECTRONICS II | 2018年 / 1955卷

关键词：

Supervised Chaos Genetic Algorithm; Adaptive Switch Mechanism; State of Charge; LiFePO4; Batteries; LITHIUM-ION BATTERY; PARTICLE FILTER; KALMAN FILTER; MODEL; ESTIMATOR;

D O I：

10.1063/1.5033714

中图分类号：

O59 [应用物理学];

学科分类号：

摘要：

LiFePO4 battery is developed rapidly in electric vehicle, whose safety and functional capabilities are influenced greatly by the evaluation of available cell capacity. Added with adaptive switch mechanism, this paper advances a supervised chaos genetic algorithm based state of charge determination method, where a combined state space model is employed to simulate battery dynamics. The method is validated by the experiment data collected from battery test system. Results indicate that the supervised chaos genetic algorithm based state of charge determination method shows great performance with less computation complexity and is little influenced by the unknown initial cell state.

引用

页数：8

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