Intelligent battery management system with parallel-connected cell-balance algorithm on the humanoid robot

2007 IEEE Workshop on Advanced Robotics and Its Social Impacts Pub Date : 2007-12-01 DOI:10.1109/ARSO.2007.4531410

Ching-Kuo Wang, Sheng Chen, Han-Pang Huang

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引用次数: 5

Abstract

The cruising scope of the humanoid robot is conspicuously restrained by the heavy weight and the discharge instability of the lithium cell structure. Generally speaking, most of the key performance indices (KPI) of the state of discharge (SOD) can be satisfied by the series-connected cells with traditional gas-gauge if the current is small enough. However, the reliable cycle-lifespan would be shortened and KPI are no longer assured whenever the cell-inbalance phenomenon occurs under the heavy-duty discharge conditions. This paper is aimed to develop an inexpensive, lightweight, durable, reliable, and predictable cell-balance algorithm (ICBA) with parallel-connected circuit to stabilize the respective cells and protect the battery management system (BMS). A PC-based graphic-user interface (GUI) will be implemented to detect the on-line SOD and evaluate KPI for the existed cell-group. Finally, computer simulations and the SOD experiment with data acquisition are carefully examined and successfully demonstrated the advantages of the proposed algorithm.

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基于并联电池平衡算法的人形机器人智能电池管理系统

锂电池结构的重量和放电不稳定性明显限制了仿人机器人的巡航范围。一般来说，如果电流足够小，传统气表串联电池可以满足放电状态(SOD)的大部分关键性能指标。但在重载放电条件下，一旦出现电池不平衡现象，就会缩短可靠的循环寿命，无法保证KPI。本文旨在开发一种廉价、轻便、耐用、可靠和可预测的电池平衡算法(ICBA)，并采用并联电路来稳定各自的电池并保护电池管理系统(BMS)。将实现基于pc的图形用户界面(GUI)来检测在线SOD并评估现有细胞组的KPI。最后，通过计算机仿真和数据采集的超氧化物歧化酶实验验证了该算法的优越性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2007 IEEE Workshop on Advanced Robotics and Its Social Impacts

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