关于阀控密封铅蓄电池容量与电导的相关性

阀控密封铅蓄电池荷电态在50％以上时，其内阻(或电导)是看不出什么变化的。只是荷电态在50％以下时，铅蓄电池的内阻才逐渐增大。若将荷电态在0至100％的全部铅蓄电池都统计进去，其容量与电导才有线性相关关系。然而对荷电态大于80％的在线使用的铅蓄电池而言，却不存在上述关系。因而不能用铅蓄电池的电导值去推断在线使用的铅电池的荷电态或健康状态。     

阀控密封铅蓄电池在线检测技术评述

1电池组在线检测的必要性和迫切性目前在通信电源系统中阀控密封铅蓄电池(包括AGM式密封铅蓄电池和胶体密封铅蓄电池)已基本上取代了自由电解液式的固定型铅酸蓄电池。为了确保通信电源的可靠性,必须及时了解电源系统中的蓄电池组的荷电态SOC(State-of-Charge)和健康状态SOH(State-of-Health),即评估蓄电池组的放电容量和使用寿命。虽然通过深放电检查蓄电池容量是评价蓄电池性能和健康状态的最有效的办法,然而对于在线使用的蓄电池组,这样做风险很大,若无备用蓄电池组,一般不允许使用这种方法。过去人们由在线检测电解液密度就可以判…     

蓄电池内阻与容量的关系

蓄电池的内阻跟额定容量有关。荷电态SOC高于50%时,阀控密封铅酸蓄电池、锂离子电池、金属氢化物镍电池、镉镍蓄电池、锌镍电池的内阻都是保持不变的;只是SOC低于40%以下时,它们的内阻才很快升高。     

阀控密封铅蓄电池的充电和放电

1阀控密封铅蓄电池的充电特性1.1充电反应阀控密封铅蓄电池虽然在结构和性能上不同于传统的铅蓄电池,但它仍然是铅酸电池体系,因而传统铅蓄电池的充电特性大都适合于阀控密封铅蓄电池。放完电的阀控密封铅蓄电池正负极活性物质(PbO2和Pb)都转化为硫酸铅(PbSO4),完成由活性物质(PbO2和Pb)的化学能转化为电能的过程。此后必须由外界向电池充电,使硫酸铅(PbSO4)重新转化为PbO2和Pb,使电能转化为活性物质(PbO2和Pb)的化学能储存在电池内。充电过程中发生的主反应是:2PbSO4 2H2O→PbO2 Pb 2H2SO4(1)副反应是电解水:H2O→H2 O2(2)反…     

阀控密封铅蓄电池常见故障原因和对策

用于通信电源系统中的阀控密封铅蓄电池基本上有两种规格:2 V/200 Ah~3000 Ah的大容量电池(有人称为大密电池)以及12 V/24 Ah~120 Ah的中等容量电池(有人称为中密电池)。每种规格又包括AGM电池和胶体电池。它们的外形虽然不同,但其内部基本结构是一致的。因而它们的故障既有共同性,又有个别的特殊性。1新电池容量不足在标准YD/T799-2002《通信用阀控式密封铅蓄电池》和YD/T1360-2005《通信用阀控式胶体蓄电池》中规定了新电池10 h率放电容量应达到额定值的95%以上,3次循环后必须达到100%。达不到上述要求就表示新电池容量不足。其主要…     

两类阀控密封铅蓄电池的比较

当今阀控式密封铅蓄电池有两类,即分别采用玻璃纤维隔板和硅凝胶两种不同方式来“固定”硫酸电解液。它们都是利用阴极吸收原理使电池得以密封的,但给阳极析出的氧到达阴极提供的通道是不同的,因而两种电池的性能各有千秋。     

密封铅蓄电池阻抗参数与荷电态

蓄电池的交流阻抗特性远比理想的单电极要复杂，不同类型的蓄电池的阻抗参数差别很大，其中有些参数有可能用于指示蓄电池的荷电态。密封铅蓄电池的荷电态在50%以上时，电池内阻几乎没有变化，但其电化学反应内阻与双层电容之积，却对荷电态很敏感。     

串联锂离子电池组荷电状态评估方法对比

分析了多芯串联锂离子电池组中各组成电芯初始荷电状态差异引起的安全问题,研究了充电电压、放电电压和开路电压与荷电状态对应关系,并进行了试验验证,定量分析和试验验证了电芯间的初始开路电压差异、初始放电电压差异、初始荷电状态差异三者与锂离子电池组安全性的对应关系,提出了初始荷电状态差异的考核方法。     

蓄电池组的连接方式与可靠性

同型号阀控式密封铅蓄电池并联运时,荷电不同的电池虽然初始充放电电流值不同,但电池之间会自动弥补,最终电流趋于一致,没有发现恶性循环现象,根据上述事实和可靠性工程原理,可以认为采用先并后串的方式组成蓄电池组,对延长电池使用寿命和提高蓄电池组的可靠性是有利的。     

阀控密封铅蓄电池的基本结构和工作原理

阀控密封铅蓄电池已广泛应用于通信电源系统,为了保证通信电源系统的可靠性,更好地发挥阀控密封铅蓄电池的优越性,延长电池的使用寿命,降低通信电源系统的运行费用,我刊特邀知名专家根据阀控密封铅蓄电池的特点,对电池在使用维护工作中经常遇到的问题及其解决办法进行讲解,共分6讲,向广大通信电源系统的使用维护人员作一系统地介绍,尽力使大家在对蓄电池使用维护工作中做到知其然,又知其所以然。     

VRLA battery discharge reserve time estimation

The discharge reserve time of a valve regulated lead acid (VRLA) battery is dependent on both discharge operating conditions as well as battery condition. Operating conditions include discharge type and rate, ambient temperature and initial state of charge while battery conditions include battery state of health and battery type. For this reason determining the discharge reserve time can be a very complex problem. This paper presents a simple approach for estimating VRLA battery state of charge (SOC) and thus discharge reserve time during discharge over a wide range of operating and battery conditions. A discharge characteristic, referred to as the unified characteristic, is employed that is shown to be robust to variations in operating conditions as well as battery condition. Furthermore, the resulting accurate estimations of SOC (within 10%) and reserve time (within 10% from the early stages of the discharge) do not come at the cost of complexity.     

VRLA battery state-of-charge estimation in telecommunication powersystems

This paper presents the logical analysis of valve-regulated lead-acid battery discharge behavior and suggests a model for obtaining estimates of the state of charge (SOC) and reserve time throughout discharge. The basis of the model is the relationship between the discharge voltage and SOC. This relationship is valid for a wide range of discharge rates and ambient temperatures as related to the telecommunications backup power supply application. Due to the robust nature of this relationship, only a single discharge characteristic under nominal operating conditions is required by the model. Case studies reveal that the model enables accuracy in estimation of SOC of better than 10% of actual SOC after discharging 10% of the rated capacity. As the discharge proceeds, the error reduces substantially. A feature of the model is that it is easily adaptable to changes in battery characteristics which occur as a result of extreme stress     

VRLA蓄电池在线监测技术综述

随着铅酸蓄电池的广泛应用,人们对其运行的安全性、可靠性提出了更高的要求。同时,蓄电池在线监测技术也得到了迅猛发展。文章简单介绍了阀控式铅酸（VRLA）蓄电池在线监测及剩余容量（SOC）在线预测的几种方法,并进行了对比分析,提出了较为有效的监测方法。     

阀控式铅酸蓄电池VRLA在线维护技术的应用研究

以往对阀控式铅酸蓄电池的监测仅仅停留在对电池电压和内阻的测试上,没有有效的分析及维护手段,文章从浮充电压对阀控电池容量及寿命的影响角度,讨论了阀控电池浮充状态的分析判断方法,并提出了通过在线充放电的控制来调整阀控电池浮充状态的技术,达到对电池在线维护、改善性能、延长寿命的目的。文中还提出了具体的实现方案,列举了应用实例。     

State-of-Charge Determination From EMF Voltage Estimation: Using Impedance, Terminal Voltage, and Current for Lead-Acid and Lithium-Ion Batteries

State-of-charge (SOC) determination is an increasingly important issue in battery technology. In addition to the immediate display of the remaining battery capacity to the user, precise knowledge of SOC exerts additional control over the charging/discharging process, which can be employed to increase battery life. This reduces the risk of overvoltage and gassing, which degrade the chemical composition of the electrolyte and plates. The proposed model in this paper determines the SOC by incorporating the changes occurring due to terminal voltage, current load, and internal resistance, which mitigate the disadvantages of using impedance only. Electromotive force (EMF) voltage is predicted while the battery is under load conditions; from the estimated EMF voltage, the SOC is then determined. The method divides the battery voltage curve into two regions: 1) the linear region for full to partial SOC and 2) the hyperbolic region from partial to low SOC. Algorithms are developed to correspond to the different characteristic changes occurring within each region. In the hyperbolic region, the rate of change in impedance and terminal voltage is greater than that in the linear region. The magnitude of current discharge causes varying rates of change to the terminal voltage and impedance. Experimental tests and results are presented to validate the new models.     

动力电池荷电状态估算方法的研究

由于电池本身特性决定了电池电量的预测成为电动汽车开发的一个难点。但目前各种方法都难以精确地测量蓄电池的剩余电量,并以此计算电动汽车蓄电池的荷电状态（SOC）。在对目前常用的剩余电量计量方法分析基础上,提出了一种基于开路电压法和安时法复合的估算方法,然后利用卡尔曼滤波估计递推算法对蓄电池SOC进行实时估算,并在MATLAB下进行了仿真,实现了电池荷电状态（SOC）的精确估算。     

A novel prediction method based on the support vector regression for the remaining useful life of lithium-ion batteries

Traditional approaches to lithium-ion battery health management mostly focus on the state of charge (SOC) estimation issues, whereas the state of health (SOH) estimation is also critical to lithium-ion batteries for safe operation. For online battery prognostics, it is critical to make timely and accurate response to SOH. The loss of rated capacity of a battery is usually used to determine the battery SOH, whereas the measurement of the capacity of an operating battery is quite challenging. Normally, the rated capacity fading largely relies on laboratory measurements and offline analysis. In this paper, two real-time measurable health indicators (HI) - one is the time interval of an equal charging voltage difference (TIECVD), and the other is the time interval of an equal discharging voltage difference (TIEDVD) - are extracted. A novel method which combines feature vector selection (FVS) with SVR is utilized to model the relationship between these two HIs and capacity, then the online capacity can be evaluated, more accurate prognostics of SOH and remaining useful life (RUL) can be made. Besides, compared to standard SVR, the proposed method takes FVS to cut down the training data size, which improves the efficiency of model training and prediction. In the end, two datasets demonstrated this approach performs both well in accuracy and efficiency.     

A new approach to intermittent charging of valve-regulated lead-acid batteries in standby applications

For many years, intensive research has been undertaken to increase the life of valve-regulated lead-acid (VRLA) batteries. Overcharging results in excessive temperature in the battery, which degrades the chemical composition of the electrolyte. When the battery reaches the end-of-charge state, the energy being supplied to the battery is no longer consumed in the charge reaction and this additional energy is dissipated as heat within the battery. At this point, the oxygen cycle accelerates, which leads to temperature rise inside the battery. State-of-the-art control technology is required to control the charging of the battery and prevent the battery going into thermal runaway. This paper discusses the charging strategies for VRLA batteries in standby applications. Intermittent charging decreases the continuous overcharge which arises in the case of float charging. The charging regime used in intermittent charging must ensure the full recharge of the battery. This paper describes a new efficient method of charging batteries employing an intermittent charging technique called "Interrupted Charge Control." Laboratory tests and results are presented.     

阀控铅酸蓄电池的监控和故障预测

阀控铅酸蓄电池需要维护测试和故障预测,通常采用的电池容量试验和通过监测电池电压预测单体电池故障的方法不是理想的方法。而利用电池内阻预测单体电池故障是非常有效的。该方法可以替代电池容量试验方法。本文讨论阀控铅酸蓄电池故障机理,分析现行电池故障预测方法存在的问题。介绍通过测量电池内阻预测阀控铅酸蓄电池故障的方法。