一个电池意识的传感器融合策略:统一磁性-惯性态度和动力,用于能量受限制的运动系统
Raphael Diego Comesanha E Silva1, Thiago Martins1, João Paulo Bedretchuk1
1Electrical Engineering Department, Federal University of Santa Catarina, Florianópolis 88040-900, SC, Brazil.
Sensors (Basel, Switzerland)
|February 13, 2026
概括
这项研究将电池充电状态 (SOC) 估计整合到扩展卡尔曼波器 (EKF) 中,用于传感器系统的态度估计. 这种统一的方法准确地估计了态度和能量水平,而不会影响性能.
科学领域:
- 嵌入式系统 嵌入式系统
- 传感器融合式传感器
- 收集能源 收集能源
背景情况:
- 扩展卡尔曼波器 (EKF) 对于使用磁性和惯性测量单元 (MIMU) 的电池驱动传感系统的态度估计至关重要.
- 当前的方法往往在外部管理电池状态,将其与核心估计过程分开.
研究的目的:
- 开发基于EKF的配方,在单一的过框架内共同估计电池的态度和电池充电状态 (SOC).
- 为了使资源有限的嵌入式系统能够进行集成的能源意识态度估计.
主要方法:
- 嵌入式电池SOC作为EKF内的明确状态变量.
- 使用基于终端电压和电流的低复杂度估计器建模SOC动态.
- 采用简化扩展卡尔曼波器 (SEKF) 来进行为MIMU应用量身定制的态度估计.
主要成果:
- 联合SOC和态度估计没有降低最初的SEKF态度估计的表现.
- 在各种负载配置文件下,SOC估计误差低于8% (约. 消耗电量为0.1瓦).
- 已证明适用于可穿戴设备和小型自主平台等低功耗电子设备.
结论:
- 拟议的统一EKF配方有效地整合了态度和能量状态估计.
- 这种方法适用于基于MIMU的嵌入式系统,其计算和能源资源有限.
- 直接将能量状态纳入过结构提供了一个更有效和统一的解决方案.
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