Fractional‐order modeling and SOC estimation of lithium‐ion battery considering capacity loss

For state‐of‐charge (SOC) estimation, the resistance deterioration and continuous capacity loss can lead to erroneous estimation results. In this paper, an SOC estimator of lithium‐ion battery based on the fractional‐order model and adaptive dual Kalman filtering algorithm is proposed first. Then, to improve the accuracy of SOC estimation considering capacity loss, the particle filter algorithm is applied to update capacity online in real time. Then, an SOC estimation method is proposed considering battery capacity loss. The simulation results show that the accuracy of battery capacity prediction based on particle filter is high under the condition of capacity loss.     

An alternating current heating method for lithium‐ion batteries from subzero temperatures

An alternating current (AC) heating method for lithium‐ion batteries is proposed in the paper. Effects of current frequency, amplitudes and waveforms on the temperature evolution and battery performance degradation are respectively investigated. First, a thermal model is established to depict the heat generation rate and temperature status, whose parameters are calibrated from the AC impedance measurements under different current amplitudes and considering battery safe operating voltage limits. Further experiments with different current amplitudes, frequencies and waveforms on the 18650 batteries are conducted to validate the effectiveness of the AC heating. The experimental data recorded by appropriate measurement instrument are of great consistence with simulation results from the thermal model. At high frequency, the temperature rises prominently as the current increases, and high frequency serves as a good innovation to reduce the battery degradation. However, efficient temperature rise can be obtained from high impedance at low frequencies. Typically, 600 s is needed to heat up the battery from ?24 °C to 7.79 °C with sinusoidal waveform and approximately from ?24 °C to 25.6 °C with rectangular pulse waveform at 10A and 30 Hz. The model and experiments presented have shown potential value in battery thermal management studies for electric vehicle (EV)/hybrid electric vehicle (HEV) applications at subzero temperatures. Copyright © 2016 John Wiley & Sons, Ltd.     

A novel multiobjective charging optimization method of power lithium‐ion batteries based on charging time and temperature rise

Power lithium‐ion batteries have been widely utilized in energy storage system and electric vehicles, because these batteries are characterized by high energy density and power density, long cycle life, and low self‐discharge rate. However, battery charging always takes a long time, and the high current rate inevitably causes great temperature rises, which is the bottleneck for practical applications. This paper presents a multiobjective charging optimization strategy for power lithium‐ion battery multistage charging. The Pareto front is obtained using multiobjective particle swarm optimization (MOPSO) method, and the optimal solution is selected using technique for order of preference by similarity to ideal solution (TOPSIS) method. This strategy aims to achieve fast charging with a relatively low temperature rise. The MOPSO algorithm searches the potential feasible solutions that satisfy two objectives, and the TOPSIS method determines the optimal solution. The one‐order resistor‐capacitor (RC) equivalent circuit model is utilized to describe the model parameter variation with different current rates and state of charges (SOCs) as well as temperature rises during charging. And battery temperature variations are estimated using thermal model. Then a PSO‐based multiobjective optimization method for power lithium‐ion battery multistage charging is proposed to balance charging speed and temperature rise, and the best charging stage currents are obtained using the TOPSIS method. Finally, the optimal results are experimentally verified with a power lithium‐ion battery, and fast charging is achieved within 1534 s with a 4.1°C temperature rise.     

Experimental and optimization of material synthesis process parameters for improving capacity of lithium‐ion battery

New methods for synthesis of active materials have been developed to improve capacity and cycle life performance of lithium‐ion batteries. Past studies have focused on routes of development of materials and new processes, which might not be economical for large‐scale production. In this regard, this study examines a widely employed carbothermal reduction technology for the synthesis of lithium‐iron phosphate (LiFePO₄/C) and investigates effects of process conditions during this synthesis on final battery performance. An experimental combined genetic programming approach is used to model the effects of crucial process conditions (sintering time, the carbon content, and the sintering temperature) on the discharge capacity of the assembled battery. Experiments are conducted to collect the discharge capacity data based on varying LiFePO₄/C synthesis conditions, and genetic programming is employed to develop a suitable functional relationship between them. The results show that the battery discharge capacity is controlled significantly by adjusting sintering temperature and carbon content, while the effect of sintering time is found to be insignificant. Further, the interaction effect of the sintering time and carbon content is much more obvious than that of the sintering time and the sintering temperature. The findings from the study pave the way for the optimum design of the synthesis process of LiFePO₄/C for a higher battery performance.     

Thermal management of lithium‐ion batteries for electric vehicles

Thermal issues associated with electric vehicle battery packs can significantly affect performance and life cycle. Fundamental heat transfer principles and performance characteristics of commercial lithium‐ion battery are used to predict the temperature distributions in a typical battery pack under a range of discharge conditions. Various cooling strategies are implemented to examine the relationship between battery thermal behavior and design parameters. By studying the effect of cooling conditions and pack configuration on battery temperature, information is obtained as to how to maintain operating temperature by designing proper battery configuration and choosing proper cooling systems. It was found that a cooling strategy based on distributed forced convection is an efficient, cost‐effective method which can provide uniform temperature and voltage distributions within the battery pack at various discharge rates. Copyright © 2012 John Wiley & Sons, Ltd.     

Introducing the energy efficiency map of lithium‐ion batteries

The charge, discharge, and total energy efficiencies of lithium‐ion batteries (LIBs) are formulated based on the irreversible heat generated in LIBs, and the basics of the energy efficiency map of these batteries are established. This map consists of several constant energy efficiency curves in a graph, where the x‐axis is the battery capacity and the y‐axis is the battery charge/discharge rate (C‐rate). In order to introduce the energy efficiency map, the efficiency maps of typical LIB families with graphite/LiCoO₂, graphite/LiFePO₄, and graphite/LiMn₂O₄ anode/cathode are generated and illustrated in this paper. The methods of usage and applications of the developed efficiency map are also described. To show the application of the efficiency map, the effects of fast charging, nominal capacity, and chemistry of typical LIB families on their energy efficiency are studied using the generated maps. It is shown how energy saving can be achieved via energy efficiency maps. Overall, the energy efficiency map is introduced as a useful tool for engineers and researchers to choose LIBs with higher energy efficiency for any targeted applications. The developed map can be also used by energy systems designers to obtain accurate efficiency of LIBs when they incorporate these batteries into their energy systems.     

Subspace‐based modeling and parameter identification of lithium‐ion batteries

For reliable and safe operation of lithium‐ion batteries in electric vehicles, the monitoring of state‐of‐charge and state‐of‐health is necessary. However, these internal states cannot be measured directly, which are usually estimated through model‐based techniques. Therefore, an accurate application‐oriented battery model is of significant importance. The purpose of this paper is to present a novel method on battery modeling and parameter identification. In this work, a state‐space model with clear mathematical and electrochemical meanings is proposed on the basis of the electrochemical basics of lithium‐ion batteries. The frequency‐domain characteristics of the lithium‐ion batteries are also investigated. On the basis of the frequency analysis, an identification test profile that can excite the dynamic characteristics of the battery fully and persistently is proposed. A subspace‐based algorithm is then adopted to identify the parameters of the battery model. The performance and robustness of the estimated model are validated through some experiments and simulations. The validation results show that the proposed method can achieve an acceptable accuracy with the maximum error being less than 2%. Copyright © 2013 John Wiley & Sons, Ltd.     

Computational study about the effect of electrode morphology on the performance of lithium‐ion batteries

Electrode morphology has significant influence on the performance of lithium‐ion batteries in that it controls electrical conductivity and electrode utilization by establishing electrical connectivity in the electrode. The present study investigates the effect of the electrode morphology on battery performance by combining two different mathematical models. First, a two‐dimensional, direct numerical simulation (DNS) model is introduced, which stochastically generates electrode morphology and calculates electrical conduction and electrode utilization. Various simulations are conducted to evaluate the effect of the active particle coating, conductive agent loading, particle size, and electrode compression by using the DNS model. Second, data acquired from the DNS model are applied to the blended‐electrode model to evaluate battery performance. Calculation result confirms that electrode morphologies have significant effects on both capacity and power of lithium‐ion batteries. Copyright © 2016 John Wiley & Sons, Ltd.     

Performance assessment of a passive core cooling design for cylindrical lithium‐ion batteries

Battery thermal management (BTM) system is an indispensable component for large‐sized lithium‐ion battery packs used in aerospace and automotive applications. Besides providing a proper temperature range for batteries to operate, thus improving their efficiency, lifespan, and safety, the BTM system also needs to be well designed with considering the cost, weight, and practicability. In this paper, an internal passive BTM system is proposed for the cylindrical Li‐ion batteries. The design embeds a phase change material (PCM) filled mandrel inside the battery to achieve the cooling effect. A thermal test cell is first fabricated and tested in a wind tunnel under different cooling scenarios, and it is also used to verify a numerical thermal model. The proposed BTM system is further examined through the model and found to be able to create a preferable environment for batteries to operate. Specifically, the core BTM system consumes less PCM and achieves lower temperature rises and more uniform temperature distributions than an external BTM system. The proposed design can also exert its full latent heat to manage the heat generated from the battery without having a thermally conductive matrix, which is usually composite with PCM in external BTM systems. In addition, experiments show that the battery equipped with the proposed BTM system is ready for intensive cycling tests.     

Resistance exterior force property of lithium‐ion pouch batteries with different positive materials

Lithium‐ion pouch battery (LIPB) is widely applied in different engineering fields, such as electric vehicles, aeronautics, astronautics, and among others. However, few complete mechanical models with deformation field are presented to predict internal short circuit (ISC) and resistance exterior force property of LIPB under exterior loading. In the present research, the indentation theoretical models with sinusoidal shape function are established to investigate resistance exterior force property of batteries with different positive materials under different punch shapes loading. The effects of indentation displacement and deformation region on indentation force are carried out. By the comparison of indentation force, present theoretical and numerical results are consistent with previous experimental results. The indentation force increases with the punch radius increase, but decreases with the indentation displacement increase. On the basis of energy conservation law, it is concluded that LIPB is more likely to produce mechanical failure and ISC when normalized deformation region is greater than or equal to 0.4 and plastic strain energy ratio is greater than or equal to 1.5. In addition, from resistance exterior force property point of view, LIPB has a better property to resist external force when LiMnNiCoO₂, rather than LiCoO₂ and Nanophosphate, is used as positive material. The research provides a reference for assessing the safety of LIPB and selecting suitable positive material, which possesses high energy capacity and resistance exterior force property.     

A graphical model for evaluating the status of series‐connected lithium‐ion battery pack

State evaluation of battery pack is essential for battery management but laborious when dealing with massive information of cells within the pack. A graphical model for evaluating the status of series‐connected Li‐ion battery pack is established to release the burden. The model is founded by a 2D diagram, with the electric quantity “E” and the capacity “Q” as its axes, therefore called by the “E‐Q diagram.” The new graphical diagram presents the dynamics of cell variations in a linear way, thereby benefiting the design and management of battery pack, including (1) quantifying the cell variations by region, (2) illustrating the evolution of cell variations during aging, (3) guiding the estimation of pack states considering algorithm error in cell states, and (4) solving the balancing problem. The experimental results conform to the theoretical analysis, indicating that the E‐Q diagram will be pervasively applied in the design and management of series‐connected battery pack. Moreover, the E‐Q diagram is suitable for education on the basics of a battery pack, because it is a graphical model.     

A hybrid lithium‐ion battery model for system‐level analyses

We describe an advanced lithium‐ion battery model for system‐level analyses such as electric vehicle fleet simulation or distributed energy storage applications. The model combines an empirical multi‐parameter model and an artificial neural network with particular emphasis on thermal effects such as battery internal heating. The model is fast and can accurately describe constant current charging and discharging of a battery cell at a variety of ambient temperatures. Comparison to a commonly used linear kilowatt‐hour counter battery model indicates that a linear model overestimates the usable capacity of a battery at low temperatures. We highlight the importance of including internal heating in a battery model at low temperatures, as more capacity is available when internal heating is taken into account. Copyright © 2016 John Wiley & Sons, Ltd.     

Optimal charging strategy design for lithium‐ion batteries considering minimization of temperature rise and energy loss

Battery charging techniques are critical to enhance battery operation performance. Charging temperature rise, energy loss, and charging time are three key indicators to evaluate charging performance. It is imperative to decrease temperature rise and energy loss without extending the charging time during the charging process. To this end, an equivalent circuit electrical model, a power loss model, and a thermal model are built in this study for lithium‐ion batteries. Then, an integrated objective function is formulated to minimize energy loss and temperature increment during battery charging. To further validate the generality and feasibility of the proposed charging strategy, experiments are conducted with respect to different current, operating temperatures, battery types, and aging status. Comparison results demonstrate that the devised charging strategy is capable of achieving the intended effect under any operating temperature and with different aging status.     

Using high‐HFP‐content cathode binder for mitigation of heat generation of lithium‐ion battery

We investigate the effects of thermally sensitive binder (TSB) on the temperature increase of lithium‐ion battery (LIB) coin cell subjected to severe mechanical abuse. The TSB is poly(vinylidenefluoride‐co‐hexafluoropropylene) (PVDF‐HFP), similar to conventional poly(vinylidenefluoride) (PVDF) binder but with a significant hexafluoropropylene (HFP) content. The testing data show that by using TSB, the peak temperature increase of nail‐penetrated LIB coin cell can be reduced by 20% to 40%, attributed to the softening of TSB that begins from ~80°C. The cycling performance of the LIB cells is also characterized. This research sheds light on the development of thermal‐runaway mitigation techniques.     

A validation study of lithium‐ion cell constant c‐rate discharge simulation with Battery Design Studio®

We compare battery performance simulations from a commercial lithium‐ion battery modeling software package against manufacturer performance specifications and laboratory tests to assess model validity. A set of commercially manufactured spiral wound lithium‐ion cells were electrochemically tested and then disassembled and physically characterized. The Battery Design Studio® (BDS) software was then used to create a mathematical model of each battery, and discharge simulations at constant C‐rates ranging from C/5 to 2C were compared against laboratory tests and manufacturer performance specifications. Results indicate that BDS predictions of total energy delivered under our constant C‐rate battery discharge tests are within 6.5% of laboratory measurements for a full discharge and within 2.8% when a 60% state of charge window is considered. Average discrepancy is substantially lower. In all cases, the discrepancy in simulated vs. manufacturer specifications or laboratory results of energy and capacity delivered was comparable to the discrepancy between manufacturer specifications and laboratory results. Results suggest that BDS can provide sufficient accuracy in discharge performance simulations for many applications. Copyright © 2012 John Wiley & Sons, Ltd.     

Model‐based unscented Kalman filter observer design for lithium‐ion battery state of charge estimation

Accurate battery state‐of‐charge is essential for both driver notification and battery management units reliability in electric vehicle/hybrid electric vehicle. It is necessary to develop a robust state of charge (SOC) estimation approach to cope with nonlinear dynamic battery systems. This paper proposed an estimation method to identify the SOC online based on equivalent circuit battery model and unscented Kalman filter technique. Firstly, the parameters of dynamic battery model are identified offline and validated through typical electric vehicle road operation to guarantee its precision. Then the performance with respect to converge time, observer accuracy, robustness against system modeling errors, and mismatched initial SOC guess values is investigated. The accuracy of proposed estimation algorithm is validated under improved hybrid power pulse characterization test and New European Driving Cycle. Experiment and numerical simulation results clearly demonstrate that the proposed method is highly reliable with good robustness to different operating conditions and battery aging.     

Magnetic tubular carbon nanofibers as anode electrodes for high‐performance lithium‐ion batteries

Novel magnetic tubular carbon nanofibers (MTCFs) are prepared through the combination technique of hypercrosslinking, control extraction, and carbonization. The diameter of MTCFs is mainly concentrated between 90 and 120 nm, and the average tube diameter is about 30 nm. A trace amount of Fe₃O₄ exists inside the MTCFs with a particle size of 3 nm, which is formed by in situ conversion of the catalyst (FeCl₃) for the hypercrosslinking reaction. The MTCFs with high surface area (448.74 m² g^?1) and porous wall are used as anode material for lithium‐ion batteries. The electrochemical properties of MTCFs are compared, and tubular carbon nanofibers (TCFs) prepared by the complete extraction. Electrochemical analysis shows that the introduction of Fe₃O₄ nanoparticles makes MTCFs have higher reversible capacity and better rate performance. MTCFs exhibit high reversible specific capacity of 1011.7 mAh g^?1 after 150 cycles at current density of 100 mA g^?1. Even at high current density of 3000 mA g^?1, a remarkable reversible capacity of 270.0 mAh g^?1 is still delivered. Thus, the novel MTCFs show potential application value in anode material for high‐performance lithium‐ion battery.     

Effect of electrode physical and chemical properties on lithium‐ion battery performance

The effect of physical and chemical properties on the performance of both positive and negative electrodes is studied for lithium‐ion (Li‐ion) batteries. These properties include the lithium diffusivity in the active electrode material, the electrical conductivity of the electrode, and the reaction rate constant at electrode active sites. The specific energy and power of the cells are determined at various discharge rates for electrodes with different properties. In addition, this study is conducted across various cell design cases. The results reveal that at moderate discharge rates, lithium diffusivity in the active negative‐electrode material has the highest impact on cell performance. The specific energy and power of the cell are improved ~11% by increasing the lithium diffusivity in the active negative‐electrode material by one order of magnitude. Around 4% improvement in the cell performance is achieved by increasing the reaction rate constant at the active sites of either electrodes by one order of magnitude. Copyright © 2013 John Wiley & Sons, Ltd.     

Correlating uncertainties of a lithium‐ion battery – A Monte Carlo simulation

Safety issues raised from a lithium‐ion battery during operation can be attributed to the variation of its temperature, which is, in turn, associated with the uncertainties in the parameters such as material properties and operating conditions. In this study, a Monte Carlo simulation of a mechanistic lithium‐ion battery model is conducted to capture the probabilistic nature of uncertainties in the parameters and their relative importance to the temperature of a lithium‐ion battery cell. Sensitivity analysis is statistically performed, and the varied parameters are ranked according to their contributions to the variation of the battery temperature. Statistical analysis is also conducted on the distribution of the temperature and deviation from its normality has been identified. These analyses can provide valuable information for manufactures in the area of resource partitioning for quality and safety control. Copyright © 2015 John Wiley & Sons, Ltd.     

Numerical optimization of the spatial conductivity distribution within cathode microstructures of lithium‐ion batteries considering the cell performance

A numerical approach targeting the optimization of the spatial conductivity distribution within a three‐dimensional electrode microstructure of lithium‐ion batteries is presented. Its methodology is based on a spatially resolved three‐dimensional electrochemical model of a lithium‐ion battery half cell on the particle scale. Although being independent of the underlying electrode microstructure, the method is exemplarily applied on a computer‐generated periodic electrode structure consisting of smooth spherical particles. In the first step, parameter variations are performed to investigate the influence of the electrical conductivity on the simulated half‐cell performance. The simulations show that the performance‐limiting effect of low electrical conductivity values can be attributed to a through‐plane directed inhomogeneity of the local intercalation flux density. Furthermore, it is shown that if a homogenous surface intercalation flux density is reached, a further increase of the spatially uniform conductivity would not result in better half‐cell performance. In the second step, the determined optimum spatially uniform conductivity value is taken as a basis for the spatial optimization approach. The resulting conductive structure within the electrode shows gradient‐like behavior directed perpendicular to the electrode surface, while highest conductivity values are to be expected in the region close to the current collector. Therefore, multiple layer coating is suggested as a suitable practical manufacturing approach. Due to the proposed two‐stage optimization approach, the resulting conductive structure reveals conductivity saving potential without altering the macroscopic cell performance.