Optimizing Average Electric Power During the Charging of Lithium-Ion Batteries Through the Taguchi Method

In recent times, lithium-ion batteries have been widely used owing to their high energy density, extended cycle lifespan, and minimal self-discharge rate. The design of high-speed rechargeable lithium-ion batteries faces a significant challenge owing to the need to increase average electric power during charging. This challenge results from the direct influence of the power level on the rate of chemical reactions occurring in the battery electrodes. In this study, the Taguchi optimization method was used to enhance the average electric power during the charging process of lithium-ion batteries. The Taguchi technique is a statistical strategy that facilitates the systematic and efficient evaluation of numerous experimental variables. The proposed method involved varying seven input factors, including positive electrode thickness, positive electrode material, positive electrode active material volume fraction, negative electrode active material volume fraction, separator thickness, positive current collector thickness, and negative current collector thickness. Three levels were assigned to each control factor to identify the optimal conditions and maximize the average electric power during charging. Moreover, a variance assessment analysis was conducted to validate the results obtained from the Taguchi analysis. The results revealed that the Taguchi method was an eff ective approach for optimizing the average electric power during the charging of lithium-ion batteries. This indicates that the positive electrode material, followed by the separator thickness and the negative electrode active material volume fraction, was key factors significantly infl uencing the average electric power during the charging of lithium-ion batteries response. The identification of optimal conditions resulted in the improved performance of lithium-ion batteries, extending their potential in various applications. Particularly, lithium-ion batteries with average electric power of 16 W and 17 W during charging were designed and simulated in the range of 0-12000 s using COMSOL Multiphysics software. This study efficiently employs the Taguchi optimization technique to develop lithium-ion batteries capable of storing a predetermined average electric power during the charging phase. Therefore, this method enables the battery to achieve complete charging within a specific timeframe tailored to a specificapplication. The implementation of this method can save costs, time, and materials compared with other alternative methods, such as the trial-and-error approach.

Strategies for Rational Design of High-Power Lithium-ion Batteries

Lithium-ion batteries(LIBs)have shown considerable promise as an energy storage system due to their high conversion efficiency,size options(from coin cell to grid storage),and free of gaseous exhaust.For LIBs,power density and energy density are two of the most important parameters for their practical use,and the power density is the key factor for applications such as fast-charging electric vehicles,high-power portable tools,and power grid stabilization.A high rate of performance is also required for devices that store electrical energy from seasonal or irregular energy sources,such as wind energy and wave energy.Significant efforts have been made over the last several years to improve the power density of LIBs through anodes,cathodes,and electrolytes,and much progress has been made.To provide a comprehensive picture of these recent achievements,this review discusses the progress made in high-power LIBs from 2013 to the present,including general and fundamental principles of high-power LIBs,challenges facing LIB development today,and an outlook for future LIB development.

Applications of Lithium-Ion Batteries in Grid-Scale Energy Storage Systems

In the electrical energy transformation process,the grid-level energy storage system plays an essential role in balancing power generation and utilization.Batteries have considerable potential for application to grid-level energy storage systems because of their rapid response,modularization,and flexible installation.Among several battery technologies,lithium-ion batteries(LIBs)exhibit high energy efficiency,long cycle life,and relatively high energy density.In this perspective,the properties of LIBs,including their operation mechanism,battery design and construction,and advantages and disadvantages,have been analyzed in detail.Moreover,the performance of LIBs applied to grid-level energy storage systems is analyzed in terms of the following grid services:(1)frequency regulation;(2)peak shifting;(3)integration with renewable energy sources;and(4)power management.In addition,the challenges encountered in the application of LIBs are discussed and possible research directions aimed at overcoming these challenges are proposed to provide insight into the development of grid-level energy storage systems.

Unlock the potential of Li4Ti5O(12) for high-voltage/long-cycling-life and high-safety batteries: Dual-ion architecture superior to lithium-ion storage

Li4Ti5O(12)(LTO)has drawn great attention due to its safety and stability in lithium-ion batteries(LIBs).However,high potential plateau at 1.5 V vs.Li reduces the cell voltage,leading to a limited use of LTO.Dual-ion batteries(DIBs)can achieve high working voltage due to high intercalation potential of cathode.Herein,we propose a DIB configuration in which LTO is used as anode and the working voltage was 3.5 V.This DIB achieves a maximum specific energy of 140 Wh/kg at a specific power of 35 W/kg,and the specific power of 2933 W/kg can be obtained with a remaining specific energy of 11 Wh/kg.Traditional LIB material shows greatly improved properties in the DIB configuration.Thus,reversing its disadvantage leads to upgraded performance of batteries.Our configuration has also widened the horizon of materials for DIBs.

Enhanced Roles of Carbon Architectures in High-Performance Lithium-Ion Batteries

Lithium?ion batteries(LIBs), which are high?energy?density and low?safety?risk secondary batteries, are underpinned to the rise in electrochemical energy storage devices that satisfy the urgent demands of the global energy storage market. With the aim of achiev?ing high energy density and fast?charging performance, the exploitation of simple and low?cost approaches for the production of high capacity, high density, high mass loading, and kinetically ion?accessible electrodes that maximize charge storage and transport in LIBs, is a critical need. Toward the construction of high?performance electrodes, carbons are promisingly used in the enhanced roles of active materials, electrochemi?cal reaction frameworks for high?capacity noncarbons, and lightweight current collectors. Here, we review recent advances in the carbon engi?neering of electrodes for excellent electrochemical performance and structural stability, which is enabled by assembled carbon architectures that guarantee su cient charge delivery and volume fluctuation bu ering inside the electrode during cycling. Some specific feasible assem?bly methods, synergism between structural design components of carbon assemblies, and electrochemical performance enhancement are highlighted. The precise design of carbon cages by the assembly of graphene units is potentially useful for the controlled preparation of high?capacity carbon?caged noncarbon anodes with volumetric capacities over 2100 mAh cm^(-3). Finally, insights are given on the prospects and challenges for designing carbon architectures for practical LIBs that simultaneously provide high energy densities(both gravimetric and volumetric) and high rate performance.

Abnormal State Detection in Lithium-ion Battery Using Dynamic Frequency Memory and Correlation Attention LSTM Autoencoder

This paper addresses the challenge of identifying abnormal states in Lithium-ion Battery(LiB)time series data.As the energy sector increasingly focuses on integrating distributed energy resources,Virtual Power Plants(VPP)have become a vital new framework for energy management.LiBs are key in this context,owing to their high-efficiency energy storage capabilities essential for VPP operations.However,LiBs are prone to various abnormal states like overcharging,over-discharging,and internal short circuits,which impede power transmission efficiency.Traditional methods for detecting such abnormalities in LiB are too broad and lack precision for the dynamic and irregular nature of LiB data.In response,we introduce an innovative method:a Long Short-Term Memory(LSTM)autoencoder based on Dynamic Frequency Memory and Correlation Attention(DFMCA-LSTM-AE).This unsupervised,end-to-end approach is specifically designed for dynamically monitoring abnormal states in LiB data.The method starts with a Dynamic Frequency Fourier Transform module,which dynamically captures the frequency characteristics of time series data across three scales,incorporating a memory mechanism to reduce overgeneralization of abnormal frequencies.This is followed by integrating LSTM into both the encoder and decoder,enabling the model to effectively encode and decode the temporal relationships in the time series.Empirical tests on a real-world LiB dataset demonstrate that DFMCA-LSTM-AE outperforms existing models,achieving an average Area Under the Curve(AUC)of 90.73%and an F1 score of 83.83%.These results mark significant improvements over existing models,ranging from 2.4%–45.3%for AUC and 1.6%–28.9%for F1 score,showcasing the model’s enhanced accuracy and reliability in detecting abnormal states in LiB data.

SOC estimation of lithium-ion power battery for HEV based on advanced wavelet neural network

In order to improve the estimation accuracy of the battery＇s state of charge（SOC） for the hybrid electric vehicle（HEV）,the SOC estimation algorithm based on advanced wavelet neural network（WNN） is presented.Based on advanced WNN,the SOC estimation model of a lithium-ion power battery for the HEV is first established.Then,the convergence of the advanced WNN algorithm is proved by mathematical deduction.Finally,using an adequate data sample of various charging and discharging of HEV batteries,the neural network is trained.The simulation results indicate that the proposed algorithm can effectively decrease the estimation errors of the lithium-ion power battery SOC from the range of ±8% to ±1.5%,compared with the traditional SOC estimation methods.

Three-dimensionalization via control of laser-structuring parameters for high energy and high power lithium-ion battery under various operating con ditions

Laser-structuring is an effective method to promote ion diffusion and improve the performance of lithium-ion battery(LIB)electrodes.In this work,the effects of laser structuring parameters(groove pitch and depth)on the fundamental characteristics of LIB electrode,such as interfacial area,internal resistances,material loss and electrochemical performance,are investigated,LiNi_(0.5)Co_(0.2)Mn_(0.3)O_(2) cathodes were structured by a femtosecond laser by varying groove depth and pitch,which resulted in a material loss of 5%-14%and an increase of 140%-260%in the in terfacial area between electrode surface and electrolyte.It is shown that the importance of groove depth and pitch on the electrochemical performance(specific capacity and areal discharge capacity)of laser-structured electrode varies with current rates.Groove pitch is more im porta nt at low current rate but groove depth is at high curre nt rate.From the mapping of lithium concentration within the electrodes of varying groove depth and pitch by laser-induced breakdown spectroscopy,it is verified that the groove functions as a diffusion path for lithium ions.The ionic,electronic,and charge transfer resistances measured with symmetric and half cells showed that these internal resistances are differently affected by laser structuring parameters and the changes in porosity,ionic diffusion and electronic pathways.It is demonstrated that the laser structuring parameters for maximum electrode performance and minimum capacity loss should be determined in consideration of the main operating conditions of LIBs.

High-Voltage and Fast-Charging Lithium Cobalt Oxide Cathodes: From Key Challenges and Strategies to Future Perspectives

Lithium-ion batteries(LIBs)with the“double-high”characteristics of high energy density and high power density are in urgent demand for facilitating the development of advanced portable electronics.However,the lithium ion(Li+)-storage performance of the most commercialized lithium cobalt oxide(LiCoO_(2),LCO)cathodes is still far from satisfactory in terms of high-voltage and fast-charging capabilities for reaching the double-high target.Herein,we systematically summarize and discuss high-voltage and fast-charging LCO cathodes,covering in depth the key fundamental challenges,latest advancements in modification strategies,and future perspectives in this field.Comprehensive and elaborated discussions are first presented on key fundamental challenges related to structural degradation,interfacial instability,the inhomogeneity reactions,and sluggish interfacial kinetics.We provide an instructive summary of deep insights into promising modification strategies and underlying mechanisms,categorized into element doping(Li-site,cobalt-/oxygen-site,and multi-site doping)for improved Li+diffusivity and bulkstructure stability;surface coating(dielectrics,ionic/electronic conductors,and their combination)for surface stability and conductivity;nanosizing;combinations of these strategies;and other strategies(i.e.,optimization of the electrolyte,binder,tortuosity of electrodes,charging protocols,and prelithiation methods).Finally,forward-looking perspectives and promising directions are sketched out and insightfully elucidated,providing constructive suggestions and instructions for designing and realizing high-voltage and fast-charging LCO cathodes for next-generation double-high LIBs.

Challenges and recent progress in thermal management with heat pipes for lithium-ion power batteries in electric vehicles

Electric vehicles(EVs)are globally undergoing rapid developments,and have great potentials to replace the traditional vehicles based on fossil fuels.Power-type lithium-ion batteries(LIBs)have been widely used for EVs,owing to high power densities,good charge/discharge stability,and long cycle life.The driving ranges and acceleration performances are gaining increasing concerns from customers,which depend highly on the power level of LIBs.With the increase in power outputs,rising heat generation significantly affects the battery performances,and in particular operation safety.Meanwhile,the cold-start performance is still an intractable problem under extreme conditions.These challenges put forward higher requirements for a dedicated battery thermal management system(BTMS).Compared to traditional BTMSs in EVs,the heat pipe-based BTMS has great application prospects owing to its compact structure,flexibility,low cost,and especially high thermal conductivity.Encompassing this topic,this review first introduces heat generation phenomena and temperature characteristics of LIBs.Multiple abuse conditions and thermal runaway issues are described afterward.Typical cooling and preheating methods for designing a BTMS are also discussed.More emphasis on this review is put on the use of various heat pipes for BTMSs to enhance the thermal performances of LIBs.For lack of wide application in actual EVs,more efforts should be made to extend the use of heat pipes for constructing an energy-efficient,cost-effective,and reliable BTMS to improve the performances and safety of EVs.

Research and Application of High-Voltage Power Supply and Distribution on Launch Vehicle

High-power electric actuators are generally used on solid propellant motors,which further enhances the requirement on onboard supply voltage and output power of a launch vehicle.In this paper,combined with the electrical demand of China’s new generation solid-liquid bundled launch vehicle(LM-6 A),high-voltage battery technology,high-power switch control technology,insulation protection technology under low pressure are studied,and the key technologies and schemes are presented.The flight test of LM-6 A shows that the high-voltage power supply and distribution technology adopted is reasonable and feasible,and can be used as a reference for the designs of other launch vehicles or spacecrafts.

The Power-Energy Coupling Effect of Mixed Hard-Carbon/Graphite Anode

As the anode materials of lithium-ion battery, the hard carbon has the higher power performance while the graphite has the higher energy performance, respectively. In this work, novel mixed hard carbon/graphite anodes are presented showing the coupling effect of power and mixed anodes was investigated at the varying charging rates, showing the tunable behaviors dependent on the hard carbon/graphite ratios. By studying the specific capacity evolution in different split potential ranges, we found that the mixed anodes with a higher proportion of hard carbon were advantageous when working in the cut-off potential greater than 0.10 V. The electrochemical impedance spectroscopy was measured at various anode potentials, which depicted the evolution of cell resistance with the state of charge. With the aid of electrochemical impedance spectroscopy, we found that the capacity evolution with mixed ratio is attributed to the lithiation-level induced difference of charge transfer resistance and Warburg resistance. A coupling effect was discovered showing a great potential in balancing the power-energy performance of mixed anode by simply controlling the ratio of hard-carbon/graphite.

Comparison between SiC- and Si-Based Inverters for Photovoltaic Power Generation Systems

100-W class power storage systems were developed, which comprised spherical Si solar cells, a maximum power point tracking charge control-ler, a lithium-ion battery, and one of two different types of direct current (DC)-alter- nating current (AC) converters. One inverter used SiC met-al-oxide-semicon-ductor field-effect transistors (MOSFETs) as switching devices while the other used Si MOSFETs. In these 100-W class inverters, the ON resistance was considered to have little influence on the efficiency. Nevertheless, the SiC-based inverter exhibited an approximately 3% higher DC-AC conversion efficiency than the Si-based inverter. Power loss analysis indicated that the higher efficiency resulted predominantly from lower switching and reverse recovery losses in the SiC MOSFETs compared with in the Si MOSFETs.

A Passive Circuit of Battery Management Without Power Supply Designed for Commercial Space

Recently for lithium-ion batteries in satellites and spaceships,the Battery Management System(BMS)has become essential to enhance life and guarantee safety.However,most of the balance management circuits need complicated cell sensing and duty control modules.Such circuits are too costly to commercialize.In order to reduce the cost,weight,volume and energy consumption of BMS,this paper proposes a new battery management circuit.The designed circuit is passive and small in size.The charge voltage is regulated by increasing the bypass current through an adjustable reference chip.Experimental results show that the bypass current increases linearly if the charging voltage is in the range of 4.05 V to 4.2 V Also after several charge-discharge cycles,the differences between batteries visibly decrease.The proposed circuit is small in size,low in power con sumption and econo mical,making it ideal for commercial space.

Machine learning modeling for fuel cell-battery hybrid power system dynamics in a Toyota Mirai 2 vehicle under various drive cycles

Electrification is considered essential for the decarbonization of mobility sector, and understanding and modeling the complex behavior of modern fuel cell-battery electric-electric hybrid power systems is challenging, especially for product development and diagnostics requiring quick turnaround and fast computation. In this study, a novel modeling approach is developed, utilizing supervised machine learning algorithms, to replicate the dynamic characteristics of the fuel cell-battery hybrid power system in a 2021 Toyota Mirai 2nd generation (Mirai 2) vehicle under various drive cycles. The entire data for this study is collected by instrumenting the Mirai vehicle with in-house data acquisition devices and tapping into the Mirai controller area network bus during chassis dynamometer tests. A multi-input - multi-output, feed-forward artificial neural network architecture is designed to predict not only the fuel cell attributes, such as average minimum cell voltage, coolant and cathode air outlet temperatures, but also the battery hybrid system attributes, including lithium-ion battery pack voltage and temperature with the help of 15 system operating parameters. Over 21,0000 data points on various drive cycles having combinations of transient and near steady-state driving conditions are collected, out of which around 15,000 points are used for training the network and 6,000 for the evaluation of the model performance. Various data filtration techniques and neural network calibration processes are explored to condition the data and understand the impact on model performance. The calibrated neural network accurately predicts the hybrid power system dynamics with an R-squared value greater than 0.98, demonstrating the potential of machine learning algorithms for system development and diagnostics.

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.

High power and stable P-doped yolk-shell structured Si@C anode simultaneously enhancing conductivity and Li^(+)diffusion kinetics

Silicon is a low price and high capacity ancxje material for lithium-ion batteries.The yolk-shell structure can effectively accommodate Si expansion to improve stability.However,the limited rate performance of Si anodes can't meet people's growing demand for high power density.Herein,the phosphorus-doped yolk-shell Si@C materials(P-doped Si@C)were prepared through carbon coating on P-doped Si/SiO_(x)matrix to obtain high power and stable devices.Therefore,the as-prepared P-doped Si@C electrodes delivered a rapid increase in Coulombic efficiency from 74.4%to 99.6%after only 6 cycles,high capacity retention of-95%over 800 cycles at 4 A·g^(-1),and great rate capability(510 mAh·g^(-1)at 35 A·g^(-1)).As a result,P-doped Si@C anodes paired with commercial activated carbon and LiFePO_(4)cathode to assemble lithium-ion capacitor(high power density of〜61,080 W·kg^(-1)at 20 A·g^(-1))and lithium-ion full cell(good rate performance with 68.3 mAh·g^(-1)at 5 C),respectively.This work can provide an effective way tofurther improve power density and stability for energy storage devices.

Remaining useful life prediction of lithium-ion battery based on auto-regression and particle filter

Purpose-With the rapid development and stable operated application of lithium-ion batteries used in uninterruptible power supply(UPS),the prediction of remaining useful life(RUL)for lithium-ion battery played an important role.More and more researchers paid more attentions on the reliability and safety for lithium-ion batteries based on prediction of RUL.The purpose of this paper is to predict the life of lithium-ion battery based on auto regression and particle filter method.Design/methodology/approach-In this paper,a simple and effective RUL prediction method based on the combination method of auto-regression(AR)time-series model and particle filter(PF)was proposed for lithiumion battery.The proposed method deformed the double-exponential empirical degradation model and reduced the number of parameters for such model to improve the efficiency of training.By using the PF algorithm to track the process of lithium-ion battery capacity decline and modified observations of the state space equations,the proposed PF t AR model fully considered the declined process of batteries to meet more accurate prediction of RUL.Findings-Experiments on CALCE dataset have fully compared the conventional PF algorithm and the AR t PF algorithm both on original exponential empirical degradation model and the deformed doubleexponential one.Experimental results have shown that the proposed PFtAR method improved the prediction accuracy,decreases the error rate and reduces the uncertainty ranges of RUL,which was more suitable for the deformed double-exponential empirical degradation model.Originality/value-In the running of UPS device based on lithium-ion battery,the proposed AR t PF combination algorithm will quickly,accurately and robustly predict the RUL of lithium-ion batteries,which had a strong application value in the stable operation of laboratory and other application scenarios.

Design a Hybrid Energy-Supply for the Electrically Driven Heavy-Duty Hexapod Vehicle

Increasing the power density and overload capability of the energy-supply units(ESUs)is always one of the most challenging tasks in developing and deploying legged vehicles,especially for heavy-duty legged vehicles,in which significant power fluctuations in energy supply exist with peak power several times surpassing the average value.Applying ESUs with high power density and high overload can compactly ensure fluctuating power source supply on demand.It can avoid the ultra-high configuration issue,which usually exists in the conventional lithium-ion battery-based or engine-generator-based ESUs.Moreover,it dramatically reduces weight and significantly increases the loading and endurance capabilities of the legged vehicles.In this paper,we present a hybrid energy-supply unit for a heavy-duty legged vehicle combining the discharge characteristics of lithium-ion batteries and peak energy release/absorption characteristics of supercapacitors to adapt the ESU to high overload power fluctuations.The parameters of the lithium-ion battery pack and supercapacitor pack inside the ESU are optimally matched using the genetic algorithm based on the energy consumption model of the heavy-duty legged vehicle.The experiment results exhibit that the legged vehicle with a weight of 4.2 tons can walk at the speed of 5 km/h in a tripod gait under a reduction of 35.39%in weight of the ESU compared to the conventional lithium-ion battery-based solution.