Heat transfer enhanced inorganic phase change material compositing carbon nanotubes for battery thermal management and thermal runaway propagation mitigation

Developing technologies that can be applied simultaneously in battery thermal management(BTM)and thermal runaway(TR)mitigation is significant to improving the safety of lithium-ion battery systems.Inorganic phase change material(PCM)with nonflammability has the potential to achieve this dual function.This study proposed an encapsulated inorganic phase change material(EPCM)with a heat transfer enhancement for battery systems,where Na_(2)HPO_(4)·12H_(2)O was used as the core PCM encapsulated by silica and the additive of carbon nanotube(CNT)was applied to enhance the thermal conductivity.The microstructure and thermal properties of the EPCM/CNT were analyzed by a series of characterization tests.Two different incorporating methods of CNT were compared and the proper CNT adding amount was also studied.After preparation,the battery thermal management performance and TR propagation mitigation effects of EPCM/CNT were further investigated on the battery modules.The experimental results of thermal management tests showed that EPCM/CNT not only slowed down the temperature rising of the module but also improved the temperature uniformity during normal operation.The peak battery temperature decreased from 76℃to 61.2℃at 2 C discharge rate and the temperature difference was controlled below 3℃.Moreover,the results of TR propagation tests demonstrated that nonflammable EPCM/CNT with good heat absorption could work as a TR barrier,which exhibited effective mitigation on TR and TR propagation.The trigger time of three cells was successfully delayed by 129,474 and 551 s,respectively and the propagation intervals were greatly extended as well.

Adaptive battery thermal management systems in unsteady thermal application contexts

With the increasing attention paid to battery technology,the microscopic reaction mechanism and macroscopic heat transfer process of lithium-ion batteries have been further studied and understood from both academic and industrial perspectives.Temperature,as one of the key parameters in the physical fra mework of batteries,affects the performa nce of the multi-physical fields within the battery,a nd its effective control is crucial.Since the heat generation in the battery is determined by the real-time operating conditions,the battery temperature is essentially controlled by the real-time heat dissipation conditions provided by the battery thermal management system.Conventional battery thermal management systems have basic temperature control capabilities for most conventional application scenarios.However,with the current development of la rge-scale,integrated,and intelligent battery technology,the adva ncement of battery thermal management technology will pay more attention to the effective control of battery temperature under sophisticated situations,such as high power and widely varied operating conditions.In this context,this paper presents the latest advances and representative research related to battery thermal management system.Firstly,starting from battery thermal profile,the mechanism of battery heat generation is discussed in detail.Secondly,the static characteristics of the traditional battery thermal management system are summarized.Then,considering the dynamic requirements of battery heat dissipation under complex operating conditions,the concept of adaptive battery thermal management system is proposed based on specific research cases.Finally,the main challenges for battery thermal management system in practice are identified,and potential future developments to overcome these challenges are presented and discussed.

Functional thermal fluids and their applications in battery thermal management:A comprehensive review

With the increasing requirements for fast charging and discharging,higher requirements have been put forward for the thermal management of power batteries.Therefore,there is an urgent need to develop efficient heat transfer fluids.As a new type of heat transfer fluids,functional thermal fluids mainly includ-ing nanofluids(NFs)and phase change fluids(PCFs),have the advantages of high heat carrying density,high heat transfer rate,and broad operational temperature range.However,challenges that hinder their practical applications remain.In this paper,we firstly overview the classification,thermophysical prop-erties,drawbacks,and corresponding modifications of functional thermal fluids.For NFs,the high ther-mal conductivity and high convective heat transfer performance were mainly elaborated,while the stability and viscosity issues were also analyzed.And then for PCFs,the high heat carrying density was mainly elaborated,while the problems of supercooling,stability,and viscosity were also analyzed.On this basis,the composite fluids combined NFs and PCFs technology,has been summarized.Furthermore,the thermal properties of traditional fluids,NFs,PCFs,and composite fluids are compared,which proves that functional thermal fluids are a good choice to replace traditional fluids as coolants.Then,battery thermal management system(BTMS)based on functional thermal fluids is summarized in detail,and the thermal management effects and pump consumption are compared with that of water-based BTMS.Finally,the current technical challenges that parameters optimization of functional thermal fluids and structures optimization of BTMS systematically are presented.In the future,it is necessary to pay more attention to using machine learning to predict thermophysical properties of functional thermal fluids and their applications for BTMS under actual vehicle conditions.

State of Health Estimation of LiFePO_(4) Batteries for Battery Management Systems

When considering the mechanism of the batteries,the capacity reduction at storage(when not in use)and cycling(during use)and increase of internal resistance is because of degradation in the chemical composition inside the batteries.To optimize battery usage,a battery management system(BMS)is used to estimate possible aging effects while different load profiles are requested from the grid.This is specifically seen in a case when the vehicle is connected to the net(online through BMS).During this process,the BMS chooses the optimized load profiles based on the least aging effects on the battery pack.The major focus of this paper is to design an algorithm/model for lithium iron phosphate(LiFePO4)batteries.The model of the batteries is based on the accelerated aging test data(data from the beginning of life till the end of life).The objective is to develop an algorithm based on the actual battery trend during the whole life of the battery.By the analysis of the test data,the complete trend of the battery aging and the factors on which the aging is depending on is identified,the aging model can then be recalibrated to avoid any differences in the production process during cell manufacturing.The validation of the model was carried out at the end by utilizing different driving profiles at different C-rates and different ambient temperatures.A Linear and non-linear model-based approach is used based on statistical data.The parameterization was carried out by dividing the data into small chunks and estimating the parameters for the individual chunks.Self-adaptive characteristic map using a lookup table was also used.The nonlinear model was chosen as the best candidate among all other approaches for longer validation of 8-month data with real driving data set.

Battery Management System with State ofCharge Indicator for Electric Vehicles

Aim To research and develop a battery management system(BMS)with the state of charge(SOC)indicator for electric vehicles (EVs).Methods On the basis of analyzing the electro-chemical characteristics of lead-acid. battery, the state of charge indicator for lead-acid battery was developed by means of an algorithm based on combination of ampere-hour, Peukert's equation and open-voltage method with the compensation of temperature,aging,self- discharging,etc..Results The BMS based on this method can attain an accurate surplus capa- city whose error is less than 5% in static experiments.It is proved by experiments that the BMS is reliable and can give the driver an accurate surplus capacity,precisely monitor the individual battery modules as the same time,even detect and warn the problems early,and so on. Conclusion A BMS can make the energy of the storage batteries used efficiently, develop the batteries cycle life,and increase the driving distance of EVs.

New battery management system for multi-cell li-ion battery packs

This paper proposes a new battery management system （BMS） based on a master-slave control mode for multi-cell li-ion battery packs. The proposed BMS can be applied in li-ion battery packs with any cell number. The whole system is composed of a master processor and a string of slave manager cells （SMCs）. Each battery cell corresponds to an SMC. Unlike the conventional BMS, the proposed one has a novel method for communication, and it collects the battery status information in a direct and simple way. An SMC communicates with its adjacent counterparts to transfer the battery information as well as the commands from the master processor. The nethermost SMC communicates with the master processor directly. This method allows the battery management chips to be implemented in a standard CMOS （ complementary metal-oxide-semiconductor transistor） process. A testing chip is fabricated in the CSMC 0.5 μm 5 V N-well CMOS process. The testing results verify that the proposed method for data communication and the battery management system can protect and manage multi-cell li-ion battery packs.

BMS电路板多模块协同热-力耦合建模及仿真分析

针对现有电动汽车电池管理系统(BMS)电路板研究仅仅考虑单一功能模块的温度场及其散热效果,缺乏考虑BMS多个功能模块在温度场和力场下的相互影响及协同效应的研究的情况,以某商用BMS电路板为研究对象,采用ANSYS构建了表征BMS多模块协同作用下的热-力耦合数值仿真分析模型并验证了其有效性.在此基础上,针对BMS电路板各功能模块温度场及热变形行为开展了数值仿真研究.结果表明:BMS电路板温度分布不均,最大温差达20.5℃.均衡模块存在积热,温度高达54.4℃.高温导致电路板组件发生热膨胀变形,同时电路板约束诱发均衡模块及供电模块边缘的贴片电阻出现热应力集中,两者共同作用致使BMS均衡模块、供电模块产生凸起翘曲变形,且Z轴热变形量随着温度升高而增大,最大变形量达9.5μm,应针对BMS电路板上积热模块开展散热优化设计.

Managing the surge:A comprehensive review of the entire disposal framework for retired lithium-ion batteries from electric vehicles

Anticipating the imminent surge of retired lithium-ion batteries(R-LIBs)from electric vehicles,the need for safe,cost-effective and environmentally friendly disposal technologies has escalated.This paper seeks to offer a comprehensive overview of the entire disposal framework for R-LIBs,encompassing a broad spectrum of activities,including screening,repurposing and recycling.Firstly,we delve deeply into a thorough examination of current screening technologies,shifting the focus from a mere enumeration of screening methods to the exploration of the strategies for enhancing screening efficiency.Secondly,we outline battery repurposing with associated key factors,summarizing stationary applications and sizing methods for R-LIBs in their second life.A particular light is shed on available reconditioning solutions,demonstrating their great potential in facilitating battery safety and lifetime in repurposing scenarios and identifying their techno-economic issues.In the realm of battery recycling,we present an extensive survey of pre-treatment options and subsequent material recovery technologies.Particularly,we introduce several global leading recyclers to illustrate their industrial processes and technical intricacies.Furthermore,relevant challenges and evolving trends are investigated in pursuit of a sustainable end-of-life management and disposal framework.We hope that this study can serve as a valuable resource for researchers,industry professionals and policymakers in this field,ultimately facilitating the adoption of proper disposal practices.

面向BMS应用的锂离子电池析锂诊断方法综述

锂离子电池在低温充电或快速充电时,负极与电解液的界面处容易发生析锂副反应,使得电池容量快速衰减且增加热失控风险。对实际运行的锂离子电池进行析锂诊断,判断其是否发生析锂副反应,是下一代电池管理系统(battery management system,BMS)需要具备的重要功能,对锂离子电池系统的安全稳定运行具有重要意义。根据当前领域发展情况,该文系统总结可在线应用于BMS的析锂诊断方法,根据不同方法的特点,归纳为基于模型驱动、基于数据驱动以及基于先进传感器的3大类方法;并从5个维度详细分析每一类析锂诊断方法的原理、应用特点和局限性。最后,面向未来BMS应用提出析锂诊断方法的发展方向。

Optimal Constrained Self-learning Battery Sequential Management in Microgrid Via Adaptive Dynamic Programming

This paper concerns a novel optimal self-learning battery sequential control scheme for smart home energy systems. The main idea is to use the adaptive dynamic programming U+0028 ADP U+0029 technique to obtain the optimal battery sequential control iteratively. First, the battery energy management system model is established, where the power efficiency of the battery is considered. Next, considering the power constraints of the battery, a new non-quadratic form performance index function is established, which guarantees that the value of the iterative control law cannot exceed the maximum charging/discharging power of the battery to extend the service life of the battery. Then, the convergence properties of the iterative ADP algorithm are analyzed, which guarantees that the iterative value function and the iterative control law both reach the optimums. Finally, simulation and comparison results are given to illustrate the performance of the presented method. © 2017 Chinese Association of Automation.

Towards Long Lifetime Battery:AI-Based Manufacturing and Management

Technologies that accelerate the delivery of reliable battery-based energy storage will not only contribute to decarbonization such as transportation electrification,smart grid,but also strengthen the battery supply chain.As battery inevitably ages with time,losing its capacity to store charge and deliver it efficiently.This directly affects battery safety and efficiency,making related health management necessary.Recent advancements in automation science and engineering raised interest in AI-based solutions to prolong battery lifetime from both manufacturing and management perspectives.This paper aims at presenting a critical review of the state-of-the-art AI-based manufacturing and management strategies towards long lifetime battery.First,AI-based battery manufacturing and smart battery to benefit battery health are showcased.Then the most adopted AI solutions for battery life diagnostic including state-of-health estimation and ageing prediction are reviewed with a discussion of their advantages and drawbacks.Efforts through designing suitable AI solutions to enhance battery longevity are also presented.Finally,the main challenges involved and potential strategies in this field are suggested.This work will inform insights into the feasible,advanced AI for the health-conscious manufacturing,control and optimization of battery on different technology readiness levels.

Application of Digital Twin in Smart Battery Management Systems

Lithium-ion batteries have always been a focus of research on new energy vehicles,however,their internal reactions are complex,and problems such as battery aging and safety have not been fully understood.In view of the research and preliminary application of the digital twin in complex systems such as aerospace,we will have the opportunity to use the digital twin to solve the bottleneck of current battery research.Firstly,this paper arranges the development history,basic concepts and key technologies of the digital twin,and summarizes current research methods and challenges in battery modeling,state estimation,remaining useful life prediction,battery safety and control.Furthermore,based on digital twin we describe the solutions for battery digital modeling,real-time state estimation,dynamic charging control,dynamic thermal management,and dynamic equalization control in the intelligent battery management system.We also give development opportunities for digital twin in the battery field.Finally we summarize the development trends and challenges of smart battery management.

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.

A new state of charge determination method for battery management system

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 in turn reduces the risk of over-voltage and gassing, which degrade the chemical composition of the electrolyte and plates. This paper describes a new approach to SOC determination for the lead-acid battery management system by combining Ah-balance with an EMF estimation algorithm, which predicts the battery’s EMF value while it is under load. The EMF estimation algorithm is based on an equivalent-circuit representation of the battery, with the parameters determined from a pulse test performed on the battery and a curve-fitting algorithm by means of least-square regression. The whole battery cycle is classified into seven states where the SOC is estimated with the Ah-balance method and the proposed EMF based algorithm. Laboratory tests and results are described in detail in the paper.

Design and management of lithium-ion batteries:A perspective from modeling,simulation,and optimization

Although the lithium-ion batteries(LIBs) have been increasingly applied in consumer electronics, electric vehicles,and smart grid, they still face great challenges from the continuously improving requirements of energy density, power density, service life, and safety. To solve these issues, various studies have been conducted surrounding the battery design and management methods in recent decades. In the hope of providing some inspirations to the research in this field, the state of the art of design and management methods for LIBs are reviewed here from the perspective of process systems engineering. First, different types of battery models are summarized extensively, including electrical model and multi-physics coupled model, and the parameter identification methods are introduced correspondingly. Next, the model based battery design methods are reviewed briefly on three different scales, namely, electrode scale, cell scale, and pack scale. Then, the battery model based battery management methods, especially the state estimation methods with different model types are thoroughly compared. The key science and technology challenges for the development of battery systems engineering are clarified finally.

Design and parametric optimization of thermal management of lithium-ion battery module with reciprocating air-flow

Single cell temperature difference of lithium-ion battery(LIB) module will significantly affect the safety and cycle life of the battery. The reciprocating air-flow module created by a periodic reversal of the air flow was investigated in an effort to mitigate the inherent temperature gradient problem of the conventional battery system with a unidirectional coolant flow with computational fluid dynamics(CFD). Orthogonal experiment and optimization design method based on computational fluid dynamics virtual experiments were developed. A set of optimized design factors for the cooling of reciprocating air flow of LIB thermal management was determined. The simulation experiments show that the reciprocating flow can achieve good heat dissipation, reduce the temperature difference, improve the temperature homogeneity and effectively lower the maximal temperature of the modular battery. The reciprocating flow improves the safety, long-term performance and life span of LIB.

Design of Real Time Battery Management Unit for PV-Hybrid System by Application of Coulomb Counting Method

This paper presents a real-time battery management unit designed by applying the Coulomb counting method and intended for use in an integrated renewable energy system for PV-Hybrid power supply. Battery management is required to stabilize hybrid systems and extend battery lifetimes. The battery management unit is divided into three main stages. Firstly, analysis of the basic components of the battery type used in the system is considered. Secondly, the state of charge (SOC) estimation method and the deterioration factor of the battery are analyzed. Finally, the overall battery management system, including a computer-based measurement and control unit, is constructed. The control system displays real-time information through LabVIEW 8.5 by estimating the state of charge through various measurements. The system will issue alerts when malfunctions are detected, and the operator can analyze and react to the system in real time to stabilize the system and extend the battery lifetime.

Thermal Management of Air-Cooling Lithium-Ion Battery Pack

Lithium-ion battery packs are made by many batteries, and the difficulty in heat transfer can cause many safety issues. It is important to evaluate thermal performance of a battery pack in designing process. Here, a multiscale method combining a pseudo-two-dimensional model of individual battery and three-dimensional computational fluid dynamics is employed to describe heat generation and transfer in a battery pack. The effect of battery arrangement on the thermal performance of battery packs is investigated. We discuss the air-cooling effect of the pack with four battery arrangements which include one square arrangement, one stagger arrangement and two trapezoid arrangements. In addition, the air-cooling strategy is studied by observing temperature distribution of the battery pack. It is found that the square arrangement is the structure with the best air-cooling effect, and the cooling effect is best when the cold air inlet is at the top of the battery pack. We hope that this work can provide theoretical guidance for thermal management of lithium-ion battery packs.

电动汽车BMS从控板热分析及散热优化

针对电动汽车电池管理系统从控板服役过程中因温度过高和不均影响整车动力性、安全性问题,本文基于CFD理论,采用Icepak软件建立并验证了某商用BMS从控板热分析模型。首次在车载服役条件下,基于热分析模型开展了温度场分析和热均匀性优化研究。BMS从控板热仿真分析表明,均衡模块及供电模块因局部积热温度均超过BMS的设计温度限值60℃,整个BMS从控板最大温差为21.0℃。为此,进一步开展了BMS从控板散热路径分析,并通过改变均衡电阻间距、布局、PCB基材以及增设导热硅胶垫进行散热优化设计。提高了BMS从控板的散热能力,使BMS从控板的最高温度控制在设计规定值60℃以下,同时整个电路板的温差降为6.9℃,提高了BMS从控板在实际车载服役条件下的安全性和可靠性,可望为BMS从控板热设计与优化提供理论方法。

Battery Modeling: A Versatile Tool to Design Advanced Battery Management Systems

Fundamental physical and (electro) chemical principles of rechargeable battery operation form the basis of the electronic network models developed for Nickel-based aqueous battery systems, including Nickel Metal Hydride (NiMH), and non-aqueous battery systems, such as the well-known Li-ion. Refined equivalent network circuits for both systems represent the main contribution of this paper. These electronic network models describe the behavior of batteries during normal operation and during over (dis) charging in the case of the aqueous battery systems. This makes it possible to visualize the various reaction pathways, including convention and pulse (dis) charge behavior and for example, the self-discharge performance.