约束嵌入式器件的电荷状态估计

Edina Omerovic, Edin Golubovic, T. Uzunović
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引用次数: 0

摘要

可充电电池供电设备的广泛使用,特别是嵌入式设备,使得高效的电池管理系统(BMS)变得越来越重要。电池剩余电量的估计准确性至关重要,因为它影响设备的运行和可靠性。因此,充电状态(SoC)的估计被认为是BMS的主要功能之一。然而,SoC评估仍然是一项复杂的任务,取决于一系列内部和外部因素。大多数传统的SoC估算方法要么计算复杂,要么需要特殊的实验室设备或额外的配置工作。此外,大多数方法需要连续测量电池参数,这反过来又使这些方法不适用于受限的嵌入式设备。本文旨在通过设计一种结合基于电压的评估和预先记录的任务功率曲线的算法来估计SoC,将库仑计数方法扩展到占空比能量受限器件的类别。此外,本文还开发并描述了一套电池参数识别系统和算法验证系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
State of Charge Estimation on Constrained Embedded Devices
The broader use of devices powered by rechargeable batteries, especially constrained embedded devices, makes the efficient Battery Management System (BMS) increasingly more important. The estimation accuracy of the amount of remaining charge in the battery is critical as it affects the device’s operation and reliability. For that reason, the estimation of state-of-charge (SoC) is considered one of the main functionalities of a BMS. However, SoC estimation remains a complex task that depends on a range of internal and external factors. Most traditional SoC estimation methods are either computationally complex, require special laboratory equipment or additional configuration efforts. In addition, most methods require continuous measurement of battery parameters, which, in turn, renders these methods not applicable to the class of constrained embedded devices. This paper aims to extend the Coulomb counting method to the class of duty-cycled energy-constrained devices by designing an algorithm that combines voltage-based evaluation and pre-recorded task power profiles to estimate the SoC. In addition, a setup for identifying the battery parameters and algorithm validation setup were also developed and described in the paper.
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