SOC distribution-based modeling for lithium-ion battery for electric vehicles using numerical optimization

In order to simulate electrical characteristics of a lithium-ion battery used in electric vehicles in a good manner,a three-layer battery model is established.The charge of the lithium-ion battery is assumed to distribute among the three layers and their interaction is used to depict hysteresis and relaxation effect observed in the lithium-ion battery.The model parameters are calibrated and optimized through a numerically nonlinear least squares algorithm in Simulink Parameter Estimation Toolbox for an experimental data set sampled in a hybrid pulse test of the battery.Evaluation results showed that the established model is able to provide an acceptable accuracy in estimating the State of Charge of the lithium-ion battery in an open-loop fashion for a sufficiently long time and to describe the battery voltage behavior more accurately than a commonly used battery model.The battery modeling accuracy can thereby satisfy the requirement for practical electric vehicle applications.

Atomic-scale engineering of advanced catalytic and energy materials via atomic layer deposition for eco-friendly vehicles

Zero-emission eco-friendly vehicles with partly or fully electric powertrains have exhibited rapidly increased demand for reducing the emissions of air pollutants and improving the energy efficiency. Advanced catalytic and energy materials are essential as the significant portions in the key technologies of eco-friendly vehicles, such as the exhaust emission control system,power lithium ion battery and hydrogen fuel cell. Precise synthesis and surface modification of the functional materials and electrodes are required to satisfy the efficient surface and interface catalysis, as well as rapid electron/ion transport. Atomic layer deposition(ALD), an atomic and close-to-atomic scale manufacturing method, shows unique characteristics of precise thickness control, uniformity and conformality for film deposition, which has emerged as an important technique to design and engineer advanced catalytic and energy materials. This review has summarized recent process of ALD on the controllable preparation and modification of metal and oxide catalysts, as well as lithium ion battery and fuel cell electrodes. The enhanced catalytic and electrochemical performances are discussed with the unique nanostructures prepared by ALD. Recent works on ALD reactors for mass production are highlighted. The challenges involved in the research and development of ALD on the future practical applications are presented, including precursor and deposition process investigation, practical device performance evaluation, large-scale and efficient production, etc.

Experimental Investigation on Cooling/Heating Characteristics of Ultra-Thin Micro Heat Pipe for Electric Vehicle Battery Thermal Management

Due to the heat pipes’ transient conduction,phase change and fluid dynamics during cooling/heating with high frequency charging/discharging of batteries,it is crucial to investigate in depth the experimental dynamic thermal characteristics in such complex heat transfer processes for more accurate thermal analysis and design of a BTMS. In this paper,the use of ultra?thin micro heat pipe(UMHP) for thermal management of a lithium?ion battery pack in EVs is explored by experiments to reveal the cooling/heating characteristics of the UMHP pack. The cooling performance is evaluated under di erent constant discharging and transient heat inputs conditions. And the heating e ciency is assessed under several sub?zero temperatures through heating films with/without UMHPs. Results show that the pro?posed UMHP BTMS with forced convection can keep the maximum temperature of the pack below 40 °C under 1 ~ 3 C discharging,and e ectively reduced the instant temperature increases and minimize the temperature fluctuation of the pack during transient federal urban driving schedule(FUDS) road conditions. Experimental data also indicate that heating films stuck on the fins of UMHPs brought about adequate high heating e ciency comparing with that stuck on the surface of cells under the same heating power,but has more convenient maintenance and less cost for the BTMS. The experimental dynamic temperature characteristics of UMHP which is found to be a high?e cient and low?energy consumption cooling/heating method for BTMSs,can be performed to guide thermal analysis and optimiza?tion of heat pipe BTMSs.

Fuzzy Model for Estimation of the State-of-Charge of Lithium-Ion Batteries for Electric Vehicles

A fuzzy model was established to estimate the state of charge（SOC） of a lithium-ion battery for electric vehicles.The robust Gustafson-Kessel（GK） clustering algorithm based on clustering validity indices was applied to identify the structure and antecedent parameters of the model.The least squares algorithm was utilized to determine the consequent parameters.Validation results show that this model can provide accurate SOC estimation for the lithium-ion battery and satisfy the requirement for practical electric vehicle applications.

A Comparative Study of Fractional Order Models on State of Charge Estimation for Lithium Ion Batteries

State of charge(SOC)estimation for lithium ion batteries plays a critical role in battery management systems for electric vehicles.Battery fractional order models(FOMs)which come from frequency-domain modelling have provided a distinct insight into SOC estimation.In this article,we compare five state-of-the-art FOMs in terms of SOC estimation.To this end,firstly,characterisation tests on lithium ion batteries are conducted,and the experimental results are used to identify FOM parameters.Parameter identification results show that increasing the complexity of FOMs cannot always improve accuracy.The model R(RQ)W shows superior identification accuracy than the other four FOMs.Secondly,the SOC estimation based on a fractional order unscented Kalman filter is conducted to compare model accuracy and computational burden under different profiles,memory lengths,ambient temperatures,cells and voltage/current drifts.The evaluation results reveal that the SOC estimation accuracy does not necessarily positively correlate to the complexity of FOMs.Although more complex models can have better robustness against temperature variation,R(RQ),the simplest FOM,can overall provide satisfactory accuracy.Validation results on different cells demonstrate the generalisation ability of FOMs,and R(RQ)outperforms other models.Moreover,R(RQ)shows better robustness against truncation error and can maintain high accuracy even under the occurrence of current or voltage sensor drift.

基于AGV车的锂离子电池系统均衡控制策略设计研究

根据电池单体和储能设备对储能单元的要求,对电池模块化成组进行了分析,为了能够实现AGV的电池组的均衡,保证在使用中SOC容量能够趋于一致,对均衡策略进行了研究,提出了AGV车电池组的柔性成组的方法,并提出了容量不一致下的改进型电池系统的均衡控制方法,并验证其有效性和可行性。

Analysis of Hybrid Rechargeable Energy Storage Systems in Series Plug-In Hybrid Electric Vehicles Based on Simulations

In this paper, an extended analysis of the performance of different hybrid Rechargeable Energy Storage Systems (RESS) for use in Plug-in Hybrid Electric Vehicle (PHEV) with a series drivetrain topology is analyzed, based on simulations with three different driving cycles. The investigated hybrid energy storage topologies are an energy optimized lithium-ion battery (HE) in combination with an Electrical Double-Layer Capacitor (EDLC) system, in combination with a power optimized lithium-ion battery (HP) system or in combination with a Lithium-ion Capacitor (LiCap) system, that act as a Peak Power System. From the simulation results it was observed that hybridization of the HE lithium-ion based energy storage system resulted from the three topologies in an increased overall energy efficiency of the RESS, in an extended all electric range of the PHEV and in a reduced average current through the HE battery. The lowest consumption during the three driving cycles was obtained for the HE-LiCap topology, where fuel savings of respectively 6.0%, 10.3% and 6.8% compared with the battery stand-alone system were achieved. The largest extension of the range was achieved for the HE-HP configuration (17% based on FTP-75 driving cycle). HP batteries however have a large internal resistance in comparison to EDLC and LiCap systems, which resulted in a reduced overall energy efficiency of the hybrid RESS. Additionally, it was observed that the HP and LiCap systems both offer significant benefits for the integration of a peak power system in the drivetrain of a Plug-in Hybrid Electric Vehicle due to their low volume and weight in comparison to that of the EDLC system.

Modeling of a Lithium-Ion Capacitor and Its Charging and Discharging Circuit in a Model-Based Design

For several years now, electric vehicles (EVs) have been expected to become widely available in the micro-mobility field. However, the insufficiency of such vehicles’ battery-charging and discharging performance has limited their practical use. A hybrid energy storage system, which comprises a capacitor and battery, is a promising solution to this problem;however, to apply model-based designs, which are indispensable to embedded systems, such as the electronic control units used in EVs, a simple and accurate capacitor model is required. Within this framework, a lithium-ion capacitor (LIC) model is proposed, and its charging and discharging performances are evaluated against an actual LIC. The model corresponds accurately to the actual LIC, and the results indicate that the proposed LIC model will work well when used with Model-Based Design (MBD).

改进非线性系统滤波算法AGV动力电池荷电状态估算

智能工厂中运行的纯电动自动导引车(AGV),对锂离子动力电池的荷电状态(SOC)进行实时估算是一项重要的任务.其目的在于,对AGV任务分配、路径规划以及充电管理等工作提供有效的参考依据.通过建立锂离子动力电池的等效电路模型以及运用次优多重渐消因子扩展卡尔曼滤波(SMFFEKF)算法,对电池SOC进行估算.首先,利用特性实验数据和经典最小二乘算法对锂离子动力电池进行建模和参数辨识;然后,利用SMFFEKF算法对SOC进行实时估算,最后,介绍了锂离子动力电池及AGV的实际应用场景.通过计算机软件仿真和实验室环境下测试设备获取的电池数据结果的对比,表明该算法具有很好的实时性和预测精度,能够满足实际应用的需求.

特种车辆电池热管理设计与实验研究

为确保消防特种车辆能在高温环境下正常工作,该文设计了一种新型的电池热管理系统。提出在电池外围布置隔热结构进行热防护,电池放电过程中产生的热量则通过相变材料进行吸收。此外在相变材料中布置液冷管道,待消防特种车辆撤离火场后利用液体换热实现相变材料的再生。该文重点关注相变材料对电池组的温度控制情况,对电池放电温升的仿真结果显示,电池组温度始终处在正常范围内,初步验证了设计的可行性。在此基础上进行了实验验证,恒流放电的过程中电池组工作正常,在相变材料的作用下电池组温度得到了有效控制。为进一步优化设计,通过仿真模型研究了相变材料相变点、相变潜热等因素对热管理冷却性能的影响。

基于SCSSA-CNN-BiLSTM的行驶工况下锂电池寿命预测

随着锂离子电池广泛应用,电池寿命预测的重要性日益突显。锂离子电池剩余寿命(RUL)的准确预测是其健康管理的关键组成部分。基于此提出了一种名为SCSSA-CNN-BiLSTM的算法,旨在实现应用于整车的锂离子电池RUL预测。采用卷积神经网络(CNN)和双向长短时记忆神经网络(BiLSTM),并结合了正余弦和柯西变异的麻雀优化算法(sine-cosine and Cauchy mutation sparrow search algorithm, SCSSA),形成了一种新型的混合神经网络,以提高锂离子电池RUL预测的准确性和稳定性。CNN用于电池健康状态(SOH)深度特征的全面提取,而BiLSTM以双向方式研究这些深度特征,并通过密集层生成锂离子电池的RUL预测。为验证所提出方法的有效性,首先使用NASA的电池数据,将多个常用模型与所提出的混合神经网络模型进行比较。研究结果显示,混合模型的决定系数(R2)提高了4%~23%,RUL绝对误差降至1,这表明模型具备更高的预测准确性。随后,在整车层面进行了CLTC动态工况下的循环试验,并对寿命衰减数据进行了预测。最终的结果显示,SCSSA-CNN-BiLSTM模型对应的均方根误差(RMSE)、R2分别为1.64、0.98 Ah,展现出了良好的预测和泛化性能。

锂离子电池汽车全尺寸火灾试验研究进展综述

分析近年来国内外发生的锂离子电池电动汽车火灾事故,对电动汽车的火灾风险进行简要概括。重点针对美国、加拿大、奥地利、瑞典、中国等国家在锂离子电池电动汽车全尺寸火灾试验及火灾防控方面的科研成果进行综述。根据国内外研究成果,对不同电池容量的锂离子电池电动汽车的热释放速率进行汇总,重点总结燃烧总热释放量、热释放速率峰值和释放有毒氟化氢气体与电池容量的关系。旨在为我国锂离子电池电动汽车火灾防控和火灾风险评估技术研究提供必要的数据参考。

热辐射触发锂离子电池热失效行为及其射流热特性

实验研究了辐射加热器非接触式触发动力锂离子电池热失效过程中的温度特性、质量损失、产热行为变化等特性及其空间射流温度与热流分布特性。以50 Ah的Li(Ni_(0.6)Co_(0.2)Mn_(0.2))O_(2)电池为对象,基于锂离子电池燃烧实验平台进行。结果表明:电池热失控实验过程中发生了2次喷发现象,电池表面最高温度为489.2℃;最高温升速率为27.7 K·s^(-1);最大质量损失速率为32.7 g·s^(-1);电池本体总产热量为1.05 MJ;环境最高温度为705.3℃;烟气总释放热为6.56 MJ·m^(-2);射流空间环境最高温度比电池表面最高温度高。这表明,高温高速的易燃气体会加剧热失控危害的风险。本结果有助于电池失效初期预警、热失控抑制、火灾风险控制。

适用于无人水下潜航器电池管理系统的SOC-SOH联合估计

为了提高无人水下潜航器(UUV)电池管理系统状态的估计精度,提出荷电状态-健康状态(SOC-SOH)联合估计方法.搭建测试台架,采用4组锂离子电池进行全寿命周期下的充放电测试,获取不同老化程度下的特性数据.经理论推导和实验分析设计四维表征因子,建立基于改进支持向量回归(SVR)的SOH估计模型.探究电池状态的耦合关系,建立基于扩展卡尔曼滤波(EKF)的SOC估计模型,采用遗忘因子递推最小二乘算法(RLS)更新模型参数,利用SOH对SOC估计结果进行修正.通过不同工况的实验进行验证,结果表明:四维表征因子和电池容量相关性好,SOH估计模型精度高,SOC估计模型精度在联合修正后得到提升.所提的联合估计方法具有较高的通用性和可靠性,可以作为有效的嵌入式电池管理系统状态估计算法.

基于数据驱动的锂离子电池健康状态估计研究进展综述

锂离子电池(LIBs)在电气化交通、电化学储能和移动电子产品等领域广泛使用,精准评估其健康状态(SOH)是确保安全可靠应用的基础。数据驱动法是当前评估SOH的主流方法,该方法无需考虑电池内部复杂的物理化学反应,依赖于直接的数据分析,且具有较高的精度。本文从锂离子电池SOH影响因素入手分析了基于数据驱动的电池SOH估计方法的研究现状,着重比较了机器学习、滤波器和时间序列等方法实施SOH估计的原理、优缺点。最后,针对电动汽车实际应用场景,对SOH估计方法的未来发展趋势进行了展望。

GB/T 31467—2023《电动汽车用锂离子动力电池包和系统电性能试验方法》标准解读与分析

近年来,我国新能源汽车和动力蓄电池产业快速发展,相关标准的部分内容已不能适应产业发展需要,面向当前我国新能源汽车和动力蓄电池的使用场景需求,结合我国动力蓄电池电性能测试经验,充分参考相关国际标准,GB/T 31467—2023经修订后发布,为电动汽车用锂离子动力电池包和系统的电性能测试提供了方法。本文详细对比了GB/T 31467—2023与GB/T 31467.1—2015、GB/T 31467.2—2015以及ISO 12405-4:2018的测试项目与技术内容,并对通用测试条件、通用测试、基本性能测试等部分的修订内容进行了解释说明,可为相关动力电池产品研发和验证提供参考。标准在修订过程中,一方面考虑国内技术水平及整车对动力电池包和系统电性能的需求,增加了外观、极性、能量密度、充电性能以及工况放电的测试方法;另一方面,结合整车实际运行过程中的充放电电流以及运行环境,对所有测试项目的充放电电流进行修改,并对无负载容量损失、能量效率、高低温启动功率等测试项目的测试温度进行协调统一,有利于电动汽车用锂离子动力电池包和系统的研发和测试。

锂离子电池及其电解液发展状况及市场预测

锂离子电池由于工作电压高、循环寿命长、安全性能好、成本低、环境友好等特点,近年来在移动电话、笔记本电脑、电动汽车等领域得到了巨大发展。对锂离子电池工作原理进行了简介,对锂离子电池及其电解液的发展历程及过去5年的发展规模、产量、市场销售等进行了综述,对未来3年锂离子电池的发展趋势进行了预测,为锂离子电池和电动汽车等行业的进一步发展及其他新能源二次电池的研发和生产提供参考和借鉴。

新能源汽车锂离子动力电池碳足迹削减策略

本研究以磷酸铁锂、三元材料(NCM622)锂离子动力电池作为研究对象。在收集到磷酸铁锂、(NCM622)清单的基础上,计算得到生产1 kWh磷酸铁锂、三元材料电池(NCM622)产生的碳足迹;根据电力结构、汽车百公里能耗,计算得到新能源汽车行驶过程中锂离子动力电池运行所产生的碳足迹。结合未来燃油车、新能源汽车发展趋势,以2020年为基准年,采用情景分析法,通过改变电力结构及汽车百公里能耗,对2030年碳达峰情况进行分析。最终给出削减动力电池碳足迹、实现2030年碳达峰目标的各项策略,为我国动力电池行业绿色发展提供了政策辅助。

基于实体火试验的新能源轿车库防火设计问题探讨

新能源汽车产业发展迅猛,对完善汽车库防火设计提出新需求。对典型的建筑内新能源轿车火灾进行案例剖析,开展首例单库存新能源轿车实体火试验并探讨车库防火设计对策要点。研究结果表明:电池包热失控挥发灰色可燃气体但持续时间不等且库内受限空间易发生爆燃;库内空间壁面热反馈可能加速车体燃烧;试验轿车猛烈燃烧阶段持续时间占总燃烧时间约20%。建议新能源汽车库防火设计注重早期热失控征兆探测和后期燃烧范围控制及被动安全技术措施,库内设置带有拾音功能的摄录装置及耐火极限不低于2.00 h的分隔构件。

低速电动汽车锂离子电池组结构的设计

在对锂离子电池充放电原理进行分析的基础上,设计了低速电动汽车锂离子电池组结构。介绍了低速电动汽车锂离子电池组箱体的具体结构,以及箱体与电芯的装配,并给出了电芯、叠片电芯、正极片与上盖的结构。