An efficient field programmable gate arrays based real-time implementation of smooth variable structure filter to estimate the state of charge of Li-ion battery in electric vehicle application

IF 1.9 4区 工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC IET Electrical Systems in Transportation Pub Date : 2022-10-12 DOI:10.1049/els2.12055
Sabeur Jemmali, Mahmoud Hamouda, Bilal Manaï
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Abstract

The computational efficiency is a challenging task in the real-time implementation of battery State of Charge (SoC) estimation algorithms in Electric Vehicle (EV) application. This study proposes for the first time a pure hardware architecture of a Smooth Variable Structure Filter (SVSF) to estimate the SoC of a lithium-ion battery in an EV. The proposed embedded architecture is implemented on a Xilinx Zynq-7000 field programmable gate arrays board without using any soft-core, and validated with real-time tests carried out on a 20 Ah NMC battery with nominal voltage about 3.65 V. The whole embedded architecture of the SVSF needs a reduced execution time in the range of 921 ns, and it consumes only 466 mW. The average estimation errors of the SoC and battery voltage at different temperatures are kept within 4.95% and 2.35% respectively. The successful convergence of the algorithm and the accurate results obtained in different circumstances, prove the practicability and computational efficiency of the proposed hardware architecture.

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一种基于现场可编程门阵列的光滑变结构滤波器的实时实现,用于估计电动汽车中锂离子电池的充电状态
在电动汽车(EV)应用中,电池荷电状态(SoC)估计算法的实时实现是一个具有挑战性的任务。本研究首次提出了光滑变结构滤波器(SVSF)的纯硬件架构,用于估计电动汽车锂离子电池的SoC。提出的嵌入式架构在Xilinx Zynq-7000现场可编程门阵列板上实现,不使用任何软核,并在标称电压约3.65 V的20 Ah NMC电池上进行了实时测试。整个SVSF的嵌入式架构需要在921 ns的范围内减少执行时间,并且仅消耗466 mW。不同温度下SoC和电池电压的平均估计误差分别保持在4.95%和2.35%以内。算法的成功收敛和在不同情况下得到的准确结果,证明了所提硬件架构的实用性和计算效率。
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来源期刊
CiteScore
5.80
自引率
4.30%
发文量
18
审稿时长
29 weeks
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