An active balancer with rapid bidirectional charge shuttling and adaptive equalization current control for lithium-ion battery strings

This article proposes an active balancer, which features bidirectional charge shuttling and adaptive equalization current control, to fast counterbalance the state of charge (SOC) of cells in a lithium-ion battery (LIB) string. The power circuit consists of certain bidirectional buck-boost converters to transfer energy among the different cells back and forth. Owing to the characterization of the open-circuit voltage (OCV) vs SOC in LIB being relatively smooth near the SOC middle range, the SOC-inspected balance strategy can achieve more precise and efficient equilibrium than the voltage-based control. Accordingly, a compensated OCV-based SOC estimation is put forward to take into account the discrepancy of SOC estimation. Besides, the varied-duty-cycle (VDC) and curve-fitting modulation (CFM) methods are devised herein to tackle the problems of slow equalization rate and low balance efficacy, which arise from the diminution in balancing current as the SOC difference between the cells decreases in the later duration of equalization especially. The proposed strategies have taken the battery nonlinear characteristic and circuit parameter nonideality into account and can adaptively modulate the duty cycle with the SOC difference to keep balancing current constant throughout the balancing cycle. Simulated and experimental results are given to demonstrate the feasibility and effectiveness of the same prototype constructed. Compared with the fixed duty cycle and the VDC methods, the proposed CFM has the best balancing efficiency of 81.4%, and the balance time is shortened by 27.1% and 18.6%, respectively.     

8VSB芯片的层次式设计方法

提出了深亚微米下系统级芯片层次式版图设计的方法，并用该方法设计了HDTV信道解码芯片8VSB的版图。实例设计结果表明，该方法在节约面积、加速时序收敛方面效果明显，大大缩短了芯片设计周期。     

一种用于SOC设计中的智能I/O处理器的实现

文章介绍了SOC设计流程，智能I／O处理器组成，在开发该处理器对VHDL源代码的优化问题。     

基于DELPHI的镍氢电池管理系统软件设计

通过对镍氢电池性能的研究，给出了一个应用ISA总线技术构建的、基于DELPHI编程平台的镍氢电池管理系统的设计方案，重点介绍了该系统的软件技术和实现方法。     

On‐Line Detection Of State‐Of‐Charge In Lead Acid Battery Using Radial Basis Function Neural Network

To realize a stable supply of electric power in an automobile, an accurate and reliable detection method of SOC (state‐of‐charge) in a lead acid battery is required. However the dynamics of the battery is very complicated. The characteristics of the battery greatly change due to its degradation. Moreover a automobile has many driving patterns, which are unknown beforehand. Thus it is not easy to detect the SOC analytically. In this paper, to overcome this problem, a new on‐line SOC detection method with a radial basis function neural network is proposed. In order to increase the detection accuracy of degraded batteries, physical values related to the degradation degree are used as input signal in the neural network. The detection accuracies for different sized batteries and various degradation states are investigated.     

集成电路的现状及其发展趋势

集成电路是信息社会经济发展的基石。通过对集成电路发展规律的分析,从集成电路的设计、制造、新产品研发和市场动态等方面,描述了集成电路的最新动态;探讨了集成电路的发展趋势;指出集成电路与其它学科、技术的结合,不断形成新的研究方向;新材料、新结构、新器件不断涌现,特征尺寸继续缩小,摩尔定律仍然起作用。     

一种基于SOC技术的车载终端优化设计方案

介绍一种基于嵌入式技术的车载监控系统。通过对各种定位技术、无线通信技术研究比较论证,确定以SOC为核心处理器、GPS实现定位、GPRS无线网络为通信方式的解决方案。详细阐述车载终端的软硬件设计,并对系统性能测试结果做介绍。测试证明,该车载终端系统能够胜任车辆定位、跟踪监控等工作,而且系统具备盲区补偿的功能,扩展空间大,易于升级。     

超低功耗的锂电池管理系统设计

为了满足某微功耗仪表的应用,提高安全性能,提出了一种超低功耗锂电池管理系统的设计方案。该方案采用双向高端微电流检测电路,结合开路电压和电荷积分算法实现电量检测。采用纽扣电池代替DC/DC降压电路最大程度降低功耗。系统实现了基本保护、剩余电量检测、故障记录等功能。该锂电池管理系统在仪表上进行验证,结果表明具有良好的稳定性和可靠性,平均工作电流仅145μA。     

地震触发崩塌滑坡自组织临界性研究

汶川地震触发了大量崩塌滑坡灾害.这些规模差异巨大的现象之间,能量及空间是否存在着确定的分布规律?巨型崩滑和小规模坍塌是否遵从不同的形成机理?这些都是亟待解决的基本科学问题.作者在自组织临界状态(SOC)的概念框架下,通过震区典型路段考察,发现位于地震Ⅸ度区的崩滑工点,崩滑方量及崩滑体深度,与崩滑工点数目之间存在着良好的负幂律关系,地震Ⅹ度区也体现出有类似特征;拟静力模拟地震的沙堆离心模型实验表明,模型底板倾斜1.5°时,崩塌的动力学特性可以用幂律描述,底板倾斜达到3°时服从正态分布;元胞自动机模型数值模拟表明,随扰动强度增加沙堆模型动力学特性的演变是渐进的.从而从整体理论上对上述问题提出新的解释:处于青壮年期的山地斜坡系统具有SOC的内禀基本属性;存在一个地震强度阈值,在此之下地震触发的崩滑规模与出现频率之间的分布规律可用幂律描述,巨型崩滑灾害和小规模坍塌现象遵从同一形成机理.全新的认识可望为地震触发崩塌滑坡灾势评估提供普适性的概型并建立应用框架.     

电动汽车锂电池SOC估算研究

为了精确估算电动汽车锂电池的荷电状态(state of charge,SOC),本文通过对主流SOC估算方法进行分析与比较,提出了一种基于卡尔曼滤波算法的电动汽车能量管理系统(energy management system,EMS)SOC估算方法,同时采用联合模型以保证估算过程中有较好的精度,并在实验室条件下进行实测数据及MATLAB仿真分析。仿真结果表明,卡尔曼滤波算法对锂电池SOC进行在线实时估计是有效的,能够较为准确地计算出SOC值,且估算结果与实测值基本一致,该方法可以用于电动汽车锂电池SOC的估算,具有很强的实际应用价值。