Measurement of the maximum charge and discharge powers of a nickel/metal hydride battery for hybrid electric vehicles

The determination of the maximum acceptable charge power and power output is of special significance in the development of hybrid electric vehicles. Theoretically, the maximum acceptable charge power and the power output can be defined as those relating to the maximum current levels before the occurrence of any side reaction. A new method has been developed to measure these maximum currents for nickel/metal hydride batteries used in hybrid electric vehicles. The method involves three step: (i) measurement of the transient voltage vs. current relation during charge or discharge by a sequence of pulse currents; (ii) calculation of the overall battery internal impedance at different times and current magnitudes; (iii) determination of the maximum current from the minimum point of the internal impedance. This method is based on the principle that, with increasing current level, mass transport becomes the rate-limiting step. Any extra increase in current can only cause the occurrence of a side reaction which will result in an increase in the battery internal impedance. The maximum current can thus be determined by the minimum internal impedance from a plot of this parameter against current. Experimental results show that the maximum current strongly depends on battery state-of-charge and also, battery structure. Increase in the surface area of the battery plates is an efficient way to increase the charge-acceptance and power output of the battery, and also to reduce the internal impedance.     

The equivalent circuit battery model parameter sensitivity analysis for lithium‐ion batteries by Monte Carlo simulation

To enhance the estimation accuracy of battery's state of charge, it is imperative to estimate the battery model parameter. To reduce the calculation efforts, the number of the battery model parameter to be estimated should be less while ensuring the state of charge estimation accuracy. Especially in engineering applications, the calculating ability is usually limited. So, it needs to choose the critical battery model parameter to be estimated. This paper's contributions are as follows: The global sensitivity analysis of the battery model parameter is achieved by the Monte Carlo simulation method. The results show that the open circuit voltage and the ohmic resistance are the high sensitivity parameters. Guided by the results of parameter sensitivity analysis, a dual extended Kalman filters method is utilized to achieve online battery model parameter estimation. The experiments prove that the state of charge estimation accuracy is improved by the online parameter estimation. Estimating high sensitivity parameters can reduce running time. And the SOC estimation accuracy can be guaranteed.     

Online detection method for incremental capacity internal resistance consistency

电池包单体内阻的不一致会导致短板单体的过充过放,诱发渐变性故障,加剧电池组的失效,安全检测成为市场需求。本文对不同老化程度的磷酸铁锂充电曲线进行分析之后,提出一种基于容量增量的内阻一致性在线检测方法：对充电数据进行分析得到容量增量峰的特征,进而表征单体之间的内阻差异,最后使用箱型图进行异常检测。使用已设计的电池检测系统对电池包进行在线检测与HPPC检测,验证对比发现：两者归一化的单体内阻分布存在较高的一致性,且容量增量在线检测方法成本低、操作简便,适用于大规模的商业电池进行内阻一致性检测,不会对工程效率以及电池组寿命产生影响。在线检测方法为锂离子电池全生命周期预防性安全检测提供方法指导。     

退役动力电池梯级利用分选技术研究

首先利用熵权法对退役电池各特征参数进行权重计算,依据计算结果选取电池剩余容量、开路电压和放电直流等效内阻作为电池聚类的分选因子。其次利用支持向量机算法预测退役电池剩余容量,最后利用K-均值聚类算法将电池分成4种等级,并通过实验证明了该方法的准确性。     

磷酸铁锂电池内阻连续动态测量与分析

磷酸铁锂电池内阻测量目前大多存在耗时长、测量结果不连续等问题。文章提出一种新型的内阻测量方法——双倍率曲线法。基于该方法,对不同温度下电池内阻进行测量并进行误差分析。结合误差分析结果发现,该测量方法的适用放电状态（state of discharge, SoD）区间为5% ~ 90%。对该区间内平均内阻与温度之间的关系进行定量分析,得到平均内阻随温度变化的关系式。相比于以往的其他测量方法,该方法的提出能够有效缩短内阻测量时耗,可为在线内阻测量的实现提供一定的研究基础。     

Dynamic time warping and multidimensional scaling approach based abnormal battery visual recognition for series-connected lithium-ion batteries pack

精确、可靠地识别异常电池是保障电池系统安全、稳定运行的有效手段。但是,从实时测量得到的电流、电压和温度有限外部信息,推断内阻、容量等电池内部信息,并识别异常电池难度很大。本工作针对串联锂离子电池组,基于各单体电压测量数据,提出了一种融合动态时间规整和多维标度策略的异常电池识别方法。通过采用动态时间规整策略,计算动态时间规整距离相似性指标,以消除电池组中荷电状态不一致的影响;进而结合多维标度法提取异常特征参数,实现异常电池可视化识别。通过电池系统仿真实验,验证了所提方法的有效性,为异常电池在线识别提供了一种有效技术。     

Design and implementation of power battery charging and discharging detection system

电动汽车的快速增长带来的动力电池安全问题日趋成为行业关注的焦点,对动力电池快速安全检测成为目前市场的需求。本工作设计了一套基于以双向逆变器为主的硬件模块和C#.NET上位机软件模块的动力电池充放电检测系统。该系统检测对象为电动汽车动力电池和梯次动力电池,其特点为快速检测和深入检测。快速性表现在两分钟内检测出电池包绝缘安全、单体一致性等问题。深入性是对单体层面的诊断,根据直流内阻检测模块得到单体OCV和直流内阻分布图从而快速对电池一致性问题做诊断。每个检测模块的数据最终生成电子检测报告,同时也保存至Excel中,用于后期进一步分析。系统运行可靠,可为在储能领域的推广应用提供一定的参考。     

家用光伏蓄电池在线监测系统设计

人类已经广泛利用太阳能,并已进入家用,尤其是在农村、偏远地区的使用更为广泛。太阳能要想孤岛运行,就离不开储能设备。倘若对储能设备管理不善,会使储存的电能无法充分利用。以单片机C8051f020为核心,设计一种蓄电池在线监测设备,包括充放电电路、电压转换装置等,实现了对蓄电池的电压、电流、温度的监测;通过控制每个蓄电池的充放电,从而达到保护蓄电池的目的。同时,通过MODBUS、TCP/IP协议实现设备与控制中心的通信,把蓄电池参数上传到主机,实现了对蓄电池的实时监测。     

Designing current collector/composite electrode interfacial structure of organic radical battery

Charge/discharge processes of organic radical batteries based on the radical polymer's redox reaction should be largely influenced by the structure and the composition of the composite electrodes. AC impedance measurement of the composite electrodes reveals a strong correlation between the overall electron transfer resistance of the composite electrode and the material of the current collector, and suggests that the electric conduction to the current collector through the contact resistance should be crucial. We also find that the adhesion and the contact area between the composite electrode and the current collector strongly influence the contact resistance rather than the work functions and the volume resistivities of the composite electrode and the current collector. It is also confirmed that the charge/discharge performance of the composite electrode is related to the overall electron transfer resistance of the composite electrode. These results indicate that the charge/discharge performance of the radical battery is dominated by the interfacial electron transfer processes at the current collector/carbon fiber interface. In fact, the composite electrode which has a high adhesion to the current collector shows a small overall electron transfer resistance and an excellent charge/discharge performance. The rate performance would be much improved by suitably designing the interfacial structure including adhesion and contact area.     

Dynamic model of a lead acid battery for use in a domestic fuel cell system

This paper presents a review of existing dynamic electrical battery models and subsequently describes a new mathematical model of a lead acid battery, using a non-linear function for the maximum available energy related to the battery discharge rate. The battery state of charge (SOC) is expressed in a look-up table relative to the battery open circuit voltage (VOC). This look-up table has been developed through low discharge experiments of the battery modelled. Further, both the internal resistance and self-discharge resistance of the battery are subsequently expressed as functions of the open circuit voltage. By using an electrical model with these characteristics and a temperature compensation element to model different rates of charge and discharge, a relatively simple and accurate battery model has been developed.The new model takes into account battery storage capacity, internal resistance, self-discharge resistance, the electric losses and the temperature dependence of a lead acid battery. It is shown in this paper how the necessary parameters for the model were found. The battery modelled was a Hawker Genesis 42 Ah rated gelled lead acid battery.The simulation results of the new model are compared with test data recorded from battery discharge tests, which validate the accuracy of the new model.     

Online estimation of internal resistance and open-circuit voltage of lithium-ion batteries in electric vehicles

State-of-charge (SoC) and state-of-health (SoH) define the amount of charge and rated capacity loss of a battery, respectively. In order to determine these two measures, open-circuit voltage (OCV) and internal resistance of the battery are indispensable parameters that are obtained with difficulty through direct measurement. The motivation of this study is to develop an online, simple, training-free, and easily implementable scheme that is capable of estimating such parameters, particularly for the lithium-ion battery in battery-powered vehicles. Based on an equivalent circuit model (ECM), the electrical performance of a battery can be formulated into state-space representation. Also, underdetermined model parameters can be arranged to appear linearly so that an adaptive control approach can be applied. An adaptation algorithm is developed by exploiting the Lyapunov-stability criteria. The OCV and internal resistance can be extracted exactly without limitations of a system input signal, such as persistent excitation (PE), enhancing the method applicability for vehicular power systems. In this study, both simulations and experiments are established to verify the capability and effectiveness of the proposed estimation scheme.     

Experimental analysis on the degradation behavior of overdischarged lithium-ion battery combined with the effect of high-temperature environment

A set of experiments are performed in the present work to investigate the degradation behavior of lithium-ion battery during overdischarge cycling, as well as the influence of a high-temperature environment on the degradation. Among, different discharge cut-off voltages (1.0, 0.5, and 0.2 V) are included. During the overdischarge process, batteries experience a stage where a violent electro-thermal behavior is exhibited, involving sharp decreases in the voltage and current, and a fierce increase in the surface temperature; moreover, several parameters such as the discharge capacity, energy density, and internal resistances are all increased after overdischarge. Besides, a poor rate capacity and serious capacity degradation can also be seen during the overdischarge cycling, which is further reflected by the evolution of battery surface temperature, charge/discharge voltage, and internal resistances. What is more, it is found that battery electro-thermal parameters, eg, temperature rise, degradation rate, and internal resistances, increase exponentially as overdischarge deepens. Finally, a high-temperature environment is verified to deteriorate the degradation of overdischarged battery.     

Nonuniform current distribution within parallel‐connected batteries

An imbalanced current distribution is often observed in cables of parallel batteries, which may limit the release of the energy and power in the battery pack. Hence, it is very important to analyze the homogeneous current distributions within parallel battery batteries and explore the effect on the state of charge and energy loss. Initially, it can be found that a battery near the load will experience a large local current under higher discharge rate. With the discharge, the current distribution will show a surge wave distribution, and the peak is gradually shifted backwards. As discharge continues, local current profile in segments will have different development trends, while current profile with lower initial current values increase, which leads to an entirely different form of current distribution with the initial stage of discharge. The current profile moves in a wavelike form transmission when the total discharge rate is low. The higher the current rate, the more divergent the current distribution. The state of charge distribution is also nonuniform, clearly indicating underutilization of active materials, which will further aggravate the nonuniformity of the local current distribution in the parallel battery pack.     

Experimental investigation on the online fuzzy energy management of hybrid fuel cell/battery power system for UAVs

The hybrid powerplant combining a fuel cell and a battery has become one of the most promising alternative power systems for electric unmanned aerial vehicles (UAVs). To enhance the fuel efficiency and battery service life, highly effective and robust online energy management strategies are needed in real applications.In this work, an energy management system is designed to control the hybrid fuel cell and battery power system for electric UAVs. To reduce the weight, only one programmable direct-current to direct-current (dcdc) converter is used as the critical power split component to implement the power management strategy. The output voltage and current of the dcdc is controlled by an independent energy management controller. An executable process of online fuzzy energy management strategy is proposed and established. According to the demand power and battery state of charge, the online fuzzy energy management strategy produces the current command for the dcdc to directly control the output current of the fuel cell and to indirectly control the charge/discharge current of the battery based on the power balance principle.Another two online strategies, the passive control strategy and the state machine strategy, are also employed to compare with the proposed online fuzzy strategy in terms of the battery management and fuel efficiency. To evaluate and compare the feasibility of the online energy management strategies in application, experiments with three types of missions are carried out using the hybrid power system test-bench, which consists of a commercial fuel cell EOS600, a Lipo battery, a programmable dcdc converter, an energy management controller, and an electric load. The experimental investigation shows that the proposed online fuzzy strategy prefers to use the most power from the battery and consumes the least amount of hydrogen fuel compared with the other two online energy management strategies.     

3D electro‐thermal modelling and experimental validation of lithium polymer‐based batteries for automotive applications

This article presents an electro‐thermal model of a stack of three lithium ion batteries for automotive applications. This tool can help to predict thermal behaviour of battery cells inside a stack. The open source software OpenFOAM provides the possibility to add heat generation because of Joule losses in a CFD model. Heat sources are introduced at the connectors and are calculated as a function of battery discharge current and internal resistance. The internal resistance is described in function of temperature. Simulation results are validated against experimental results with regard to cooling air flow field characteristic and thermal behaviour of the cell surface. The validation shows that the simulation is capable to anticipate air flow field characteristics inside the battery box. It also predicts correctly the thermal behaviour of the battery cells for various discharge rates and different cooling system conditions. The simulation supports the observation that batteries have a higher temperature close to the connectors and that the temperature increase depends highly on discharge rate and cooling system conditions. Copyright © 2016 John Wiley & Sons, Ltd.     

State of health prediction model based on internal resistance

The state of health (SOH) is a crucial indicator of lithium-ion batteries. A battery cycle and calendar life are critical for electric vehicle batteries. Complex interactions occur between the SOH and internal resistance of a battery. In this study, several ternary lithium-ion battery charge discharge experiments were performed to investigate the effects of the ambient temperature, discharge rate, and depth of discharge on a battery's internal resistance. An SOH prediction model was then constructed and used to evaluate the remaining capacity of the electric vehicle battery. The model was verified through various experiments, and a comparison of experimental and model-derived data revealed a favorable agreement. Thus, the model accurately predicted the SOH of a ternary lithium-ion battery.     

A new dynamic SOH estimation of lead‐acid battery for substation application

State of Health (SOH) is one of the most important parameters of lead‐acid batteries. Most of the existing SOH estimation methods only take the influence of charge cycles into consideration, and the estimation accuracy is limited. Batteries in the substations have two typical states: one is the check‐discharge state, in which the batteries are discharged for 8 h at 0.1 C (Capacity) to determine whether the battery pack has certain reliability. The other is the floating charge state, in which the batteries are connected to the charger to maintain full power. This paper proposes a novel SOH estimation method based on the two states. In the check‐discharge state, the relationship between the voltage and the age of battery is analysed. The health index, which is introduced in this model, is affected by the age of battery. In the floating state, the relationship between the internal resistance and the age of battery is discussed. Another SOH model is established based on the change of the internal resistance. By combining the two models, the estimation method can achieve real‐time estimation and high accuracy for substation application. An accelerated life test is applied to verify the theoretical analysis. The experimental results demonstrate that the SOH estimation error is less than 3% which is very satisfactory for practical applications. Copyright © 2016 John Wiley & Sons, Ltd.     

Estimation of power battery SOC based on firefly BP neural network

针对BP神经网络算法对电动汽车电池荷电状态（state of charge,SOC）估算的缺陷,提出一种基于萤火虫（firefly algorithm,FA）神经网络的SOC估算方法。以磷酸铁锂电池为测试对象,在ARBIN公司生产的EVTS电动车动力电池测试系统装置上进行测试,收集锂电池的各项性能参数。采用端电压和放电电流作为输入参数,SOC作为输出参数,建立FA-BP神经网络模型,用于估算锂离子电池充放电过程中的任一状态下的SOC。仿真实验结果表明,与现有的BP神经网络估算方法相比,基于FA-BP神经网络的锂电池SOC估算方法准确度高,具备很好的实用性。     

A new state‐of‐charge estimation method for electric vehicle lithium‐ion batteries based on multiple input parameter fitting model

The estimation of state‐of‐charge (SOC) is crucial to determine the remaining capacity of the Lithium‐Ion battery, and thus plays an important role in many electric vehicle control and energy storage management problems. The accuracy of the estimated SOC depends mostly on the accuracy of the battery model, which is mainly affected by factors like temperature, State of Health (SOH), and chemical reactions. Also many characteristic parameters of the battery cell, such as the output voltage, the internal resistance and so on, have close relations with SOC. Battery models are often identified by a large amount of experiments under different SOCs and temperatures. To resolve this difficulty and also improve modeling accuracy, a multiple input parameter fitting model of the Lithium‐Ion battery and the factors that would affect the accuracy of the battery model are derived from the Nernst equation in this paper. Statistics theory is applied to obtain a more accurate battery model while using less measurement data. The relevant parameters can be calculated by data fitting through measurement on factors like continuously changing temperatures. From the obtained battery model, Extended Kalman Filter algorithm is applied to estimate the SOC. Finally, simulation and experimental results are given to illustrate the advantage of the proposed SOC estimation method. It is found that the proposed SOC estimation method always satisfies the precision requirement in the relevant Standards under different environmental temperatures. Particularly, the SOC estimation accuracy can be improved by 14% under low temperatures below 0 °C compared with existing methods. Copyright © 2017 John Wiley & Sons, Ltd.     

Study on the measurement methods for the DC internal resistance of lithium-ion capacitors

直流内阻（简称“内阻”）是衡量超级电容器性能最重要的电化学参数之一,但目前尚未有统一的测试方法用于锂离子电容器的内阻测试。本工作使用不同的充放电测试程序,采用不同的内阻计算方法来评测比较锂离子电容单体样品的内阻值。结果表明,不同的充放电测试方法、不同的放电截止电压、不同的内阻计算方法,影响锂离子电容器内阻测量值。以100 ms压降法计算的内阻可能接近放电开始阶段的稳态内阻,可以使用普通国产电池测试设备,简单、易行、可靠,经进一步的验证后,可以考虑推广使用。