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Interest towards electric vehicle adoption is on the rise due to the lower running and maintenance cost it offers, along with zero tailpipe emissions. Range anxiety is one of the only concern that affects the adoption of electric vehicles. The state of charge of the traction battery pack has to be accurately determined and provided to the user to avoid range anxiety. Minute battery parameters has to be considered to improve the accuracy of the state of charge determination. In order to overcome the problem of range anxiety, an innovative strategy that takes into account how vibrations affect the performance of EV batteries is developed in this research. By doing this, the state of charge estimation precision is improved and thereby raises the driver's faith in electric vehicles. The impacts and vibrations felt on the traction battery pack during driving would lead to heat generation. The heat generated is found to be highest when the vibrations resonate at the natural frequencies of the traction battery pack. The natural frequency of the battery pack is considered when the battery is kept in the battery chamber of the two-wheeler electric vehicle. The vibrations at natural frequency produces heat which is accounted for when the state of charge is determined. To obtain accurate state of charge estimation, a Kalman filter-based approach is used. The Kalman filter-based estimation uses the conventional methods which are the open circuit voltage method and the Coulomb counting method to improve the estimation process along with the consideration of the heat component due to vibrations and impact. The vibration analysis is performed using MATLAB, while the state of charge determination is implemented in hardware and the Kalman estimation done using Python. The system is modelled on an electric two-wheeler platform and the testing is done to compare the state of charge accuracy of the open circuit voltage method, the Coulomb counting method and the Kalman filter-based estimation approach. The inclusion of the vibrational heat analysis for State of Charge estimation in the hardware testing of the electric two-wheeler provides an accurate state of charge value. [ABSTRACT FROM AUTHOR]

Lithium‐ion cell chemistries are favored in the automotive sector, as they enable electric vehicles (EVs) to compete with traditional gasoline‐powered vehicles in terms of performance, range, and cost. The life and performance of these packs depend upon the Battery management system which monitors and controls the pack. The modeling, simulation, and analysis of a lithium‐ion battery pack that closely resembles an actual automobile battery are the focus of this paper. Real cells that are commercially available and specifically developed for automotive applications are modeled in the simulation environment. The cell characterization and formation of pack topology with heat exchange are addressed. A commercial electric car's power train model and EV dynamics are used in the simulation environment to test the modeled battery pack over various drive cycles. The performance analysis is upscaled by considering different aspects like resistive forces while driving, ambient temperature, initial conditions while the vehicle starts, etc. The battery manufacturer can verify the battery's performance under different load conditions, with a high degree of similarity to real‐world scenarios. The simulations are conducted on MATLAB/Simulink 2021b software. [ABSTRACT FROM AUTHOR]

In this paper, the temperature response of a lithium‐ion type 18650 battery pack cooled by a thermoelectric air‐cooling module is presented. The effects of the airflow rate, on‐off cooling fan position, charging and discharging rate and cooling by the thermoelectric air‐cooling module are investigated. The charging and discharging procedures with different current rates of 2 A (0.06 C), 3 A (0.09 C), and 4 A (0.12 C) are investigated. The results showed that different test conditions of the thermoelectric air‐cooling module have a substantial effect on the temperature of the battery pack. It was demonstrated that a thermoelectric air‐cooling module has a decreased battery temperature of lower than 40°C. The operating conditions of the cooling fans have a substantial effect on battery temperature. The experiment in which all the cooling fans are turned on shows a higher cooling capacity than natural air cooling by approximately 16%–57%. However, when setting the on‐off position of the fans that are installed in different positions, the cooling capacity when the fans at the inlet and thermoelectric cooling heat sink are turned on and the fan at the outlet battery pack is turned off is slightly less than that when all the cooling fans are turned on by approximately 25%–57%. Therefore, it can be selected as an optimum for cooling the battery pack due to less power consumption and noise issues. The proposed research can be implemented as a guideline for the cooling system of energy storage, such as small electric vehicle platforms, ground batteries, and solar energy storage. [ABSTRACT FROM AUTHOR]

Academic research in the battery field frequently remains limited to small coin or pouch cells, especially for new materials that are still rather far from commercialization, which renders a meaningful evaluation at an early stage of development challenging. Here, the realization of large lab‐scale pouch cells comprising Sn0.9Mn0.1O2 (SMO), prepared via an easily scalable hydrothermal synthesis method, as an alternative active material for the negative electrode and LiNi0.6Mn0.2Co0.2O2 (NMC622) as a commercially available active material for the positive electrode is reported. Nine double‐layer pouch cells are connected in series and parallel, suitable for powering a remote‐controlled vehicle. Subsequently, these SMO‖NMC622 cells are critically evaluated by means of an early‐stage life cycle assessment and compared to graphite‖NMC622 cells, in order to get first insights into the potential advantages and challenges of such lithium‐ion chemistry. [ABSTRACT FROM AUTHOR]

• The heat generation model for cylindrical Li-ion battery was built. • A liquid immersion cooling battery pack containing 60 batteries were established. • At 2C discharge rate, 0.5 L/min flow rate was recommended. • The battery pack can address localized high-rate discharge events (4.5C or 6.5C). • Liquid immersion cooling BTMSs have great heat dissipation performance. With the increasingly severe challenges of the thermal management of battery packs for electric vehicles, the liquid immersion cooling technology has gradually attracted more attention due to its superior characteristics such as high heat dissipation efficiency, well temperature uniformity and low risk of thermal runaway. To investigate the heat transfer characteristics of the liquid immersion cooling BTMSs, the 3D model of the 60-cell immersion cooling battery pack was established, and a well-established heat generation model that leveraged parameters derived from theoretical analysis and experiments was incorporated into the 3D simulation to analyze the thermal characteristics of battery pack. The simulation results showed that under the discharging rate of 2C, even with the lowest coolant flow rate in this work (0.2 L/min), no localized abnormal overheating within the battery pack was observed, and the highest temperature was 34.22 °C. The temperature uniformity within the battery pack improved with the increase of the coolant flow rate. It was recommended to maintain a flow rate above 0.5 L/min to ensure a temperature difference below 5 °C. The experimental apparatus of the immersion cooling battery pack was also developed to explore the heat dissipation and temperature uniformity at 2C discharge rate. The simulation results were in well agreement with the experimental results, with the deviation less than 0.43 °C when the flow rate exceeded 0.6 L/min. The effect of the localized high-rate discharge events (4.5C and 6.5C) at different battery pack locations on temperature distribution and uniformity was further discussed based on the verified 3D model. The results suggested that liquid immersion cooling systems offered promising potential for achieving both efficient heat dissipation and preventing thermal runaway in battery packs. [ABSTRACT FROM AUTHOR]

This comprehensive study delves deeply into the realm of electric vehicle (EV) battery temperature management, with a central focus on optimizing cooling systems using ethylene glycol solutions. The research rigorously examines the interplay between ethylene glycol concentrations and cooling methods on EV battery performance. ANSYS and MATLAB along with analytical methods were used for this project. Key findings reveal a consistent inverse relationship between ethylene glycol concentration and cooling efficiency, favoring lower concentrations. Indirect cooling, achieved with a 30% ethylene glycol solution, emerges as the most effective method, while direct cooling proves less efficient. Notably, mineral oil cooling at 0.04 m/s outperforms air cooling, albeit with higher energy consumption. Consequently, air cooling is recommended for smaller battery packs due to its lower power demand. The study also underscores the importance of selecting ethylene glycol concentrations based on environmental conditions, advocating lower concentrations for warmer climates and higher concentrations for colder regions. In summary, this research significantly advances EV technology by advocating for customized cooling system designs that consider environmental factors, battery specifications, and practical implementation. It provides a critical roadmap for enhancing EV thermal management systems' efficiency and sustainability. Further research is needed to explore the long-term effects of diverse cooling methodologies on battery longevity and performance within the practical constraints of EV integration. • Cooling effectiveness increases with lower concentration. • Indirect cooling outperforms direct methods. • Higher coolant flowrate enhances heat extraction but requires more energy. • A 50% ethylene glycol solution is suitable for most weather conditions. [ABSTRACT FROM AUTHOR]

Electric vehicles are a clean energy transportation option recently emerged as an alternative to the conventional engine powered vehicles. These vehicles are using Lithium ion battery as energy storage for their propulsion because of its energy density. Due to the chemical reaction of battery elements and internal resistance, the battery releases heat during charging and discharging. Unless this heat is controlled to be within the battery optimum operating temperature, the battery performance and life will be seriously affected. This paper is dedicated to conduct fundamental studies on the battery cooling. A three dimensional numerical analysis is made using PHOENICS version 2018. Cylindrical type battery cell is used in this study. The study gives insight to thermal response, flow field and temperature profiles in the battery module with air flow direction relative to battery cell orientation and cell arrangement. Temperature variation along the flow, and transverse direction of the battery pack is discussed. With a 5 mm inter cell spacing and symmetric arrangement, maximum cell to cell temperature variation in the axial flow type is observed to be 0.2 °C, while in the radial flow type about 3.5 °C for same arrangement. Quantitative and qualitative results obtained from the numerical test are presented. Furthermore, this work is believed to contribute to the improvement of battery air cooling system design in such a way the associated cost and efficiency is compromised. [ABSTRACT FROM AUTHOR]

The safety of battery system is compromised by the abusive operation and aging, potentially resulting in the abnormal voltage levels. Rapid detection and accurate diagnosis of voltage fault are crucial for ensuring the safety of battery packs. A battery voltage fault diagnosis method is proposed by using the mutual information in this work, which can identify faulty cells timely. Specifically, the voltage of battery pack in an electric vehicle is collected, and the mutual information of voltages between each paired-cells is calculated. The presence of faulty cells disturbs the original distribution of mutual information. Therefore, the Ryan Joiner (RJ) test is used to judge whether the normal distribution of calculated mutual information or not. The interquartile test is used to detect the outliers. The faulty cell is diagnosed by matching the cell corresponding to the outliers. The defaults resulting from an internal short circuit and mechanical vibration are analyzed and diagnosed. The method can avoid misdiagnosis caused by the mutual influence between different faults. Furthermore, the fault diagnosis capability of presented method is discussed under various states of aged cells. The experimental results verify the effectiveness, robustness, model-free, and easiest-to-implement of the presented method. • A battery voltage fault diagnosis method using the mutual information. • Ryan Joiner test is used for the normality test. • The interquartile test is used for outlier detection. • The proposed scheme is verified under several faults. • The method exhibits robustness under different aging states. [ABSTRACT FROM AUTHOR]

The electric vehicles are not completely emission-free. The vehicles consume power and the power generation processes involve carbon emissions, resulting in indirect vehicle usage carbon emissions. A use-phase carbon emissions assessment can help electric vehicle designers and manufacturers analyze the onboard carbon footprint and mitigate vehicle-related carbon emissions through energy consumption optimization. In this article, we focus on the use-phase carbon footprint based on the energy losses in electric vehicle battery packs. A battery pack energy loss model is established to examine the carbon footprint of four main subsystems of the battery pack, including the energy storage system, thermal management system, and battery junction box. We use the proposed method to evaluate the battery pack use-phase carbon emissions in four different cities from four main continents. The results show that the highest emissions appear in Tokyo (436.2 kgCO 2) due to the relatively high greenhouse gas factor on the grid, the London has the lowest 207.5 kgCO 2 emissions due to the massive adoption of sustainable energy during power generation. With a similar high greenhouse gas factor, but Sydney shows lower emissions (347.5 kgCO 2) compared to Tokyo, which illustrates the closer the annual average temperature to the battery suitable operation range, the lower energy loss happens inside the battery pack due to the low thermal management load and resistance energy loss in the cells. This electric vehicle has the highest energy loss rate (20.8%) in New York, 343.6 kgCO 2 emissions, and the highest thermal management system energy losses show the high seasonal temperature difference causing the high thermal management load to maintain the battery temperature. The proposed method can be used for different battery pack configurations and vehicle uses, providing researchers with a robust and versatile use-phase carbon emissions assessment strategy. • A battery pack use-phase carbon footprint assessment strategy is proposed. • The carbon emissions for four battery pack subsystems are calculated. • Temperature has the greatest impact on the battery pack carbon emissions. [ABSTRACT FROM AUTHOR]

With the increasing scale of battery systems, the impact of battery inconsistency due to aging on battery pack performance becomes increasingly significant. To achieve high-precision battery pack modeling, we propose an in-situ estimation method for battery inconsistency parameters. The proposed method utilizes current and voltage data recorded by the battery management system (BMS). The respective terminal voltage errors are used as the loss function, and the equivalent circuit model and the fully connected neural network are combined to realize the estimation of inconsistency parameters. Through optimization algorithm, the inconsistency parameters of all cells in the battery pack are simultaneously estimated. The estimation results of full capacity, high-end capacity, and internal resistance exhibit high accuracy with root-mean-square error (RMSE) values of 0.82% (0.393 Ah), 0.70% (0.336 Ah), and 3.34% (0.097 m Ω), respectively. The battery pack model constructed using the estimation results maintains high accuracy across various operating conditions, demonstrating the effectiveness of the proposed method for inconsistency estimation and battery pack modeling. • Estimate the battery inconsistency parameters based on the similarity of the battery SOC-OCV curves with the BMS data. • Combine the neural network and equivalent circuit model to simultaneously estimate the capacity, internal resistance and SOC parameters of each cell in the battery pack. • The accuracy of the proposed method was demonstrated by comparing measured parameters with estimated parameters, and the effectiveness was further demonstrated by battery pack model simulation results. [ABSTRACT FROM AUTHOR]

Summary: As an energy storage component of an electric vehicle, the battery pack is subject to continuous vibration when working. It is very important to analyze the dynamic characteristics of the battery pack through finite element method (FEM) for safety concerns. However, because of the complication of structure and the number of parts in a battery pack, it is impractical to develop an accurate FEM model. Thus, simplified methods are always applied for modeling. Because battery modules are the most complicated parts and make up the majority of proportion in a battery pack, it is the key to simplification. Using multibody models, this research proposes a simplified method for soft‐connected battery modules, which can be applied to the battery pack FEM model, accurately calculate the dynamic characteristics of a battery pack, and use less computing resources compared with traditional simplified methods. A practical battery pack structure is modeled using this method. Compared with the traditional ones, this method reduces 90% nodes and 97% meshes, excluding the influence of battery pack enclosure, and consumes 40% less memory during calculation. This method also has higher computing efficiency for larger battery packs with more battery modules. The simulation results are well matched with experimental results, which indicate the universality of the simplified model. [ABSTRACT FROM AUTHOR]

Summary: The parallel air‐cooled system is commonly applied in electric vehicles to cool the battery pack, in which flow pattern significantly influences the system cooling performance. In this paper, the curved divergence and convergence plenums are used to design the flow pattern in the parallel air‐cooled system for battery thermal management. The computational fluid dynamics (CFD) method is used for performance evaluation of the cooling system. The height distribution of control points is used to describe the plenum shape. During the optimization process, flow resistance network model is employed to obtain the velocity distribution of the system. An effective strategy is developed to adjust the height distribution of the control points for flow pattern design. Experiments are conducted to verify the CFD method and calculation model. Then typical cases are adopted to evaluate the proposed strategy for flow pattern design. The numerical results show that the strategy can effectively control the system flow pattern by designing the plenum shape. The cell temperature difference of the optimized system achieves an 86% reduction with the pressure drop only increased by 26%. Furthermore, compared with the optimized system with linear plenums in the reference, the optimized system with curved plenums achieves 48% reduction for the cell temperature difference without the pressure drop increased. Finally, experiments are conducted for the optimized system to verify the effectiveness of the developed strategy. The present study can provide a guide for the design of efficient parallel air‐cooled BTMS. Highlights: Shape optimization of the curved plenums for air‐cooled BTMSs is conducted.Effective strategy is developed to optimize the shape of curved plenums.ΔTmax of the optimized BTMS is reduced by 86% with ΔP only increased by 26%.Optimized BTMS with curved plenums performs better than that with linear plenums.Experiments are done to verify the calculation models and optimization strategy. [ABSTRACT FROM AUTHOR]

Most scholars use atomic force microscopy (AFM) to analyze battery pack materials. Because of the defects of low resolution and limited application of AFM, an atomic force microscopy system based on IPC is designed. The atomic force microscopy is constructed by the system, and the tunnel effect of quantum theory is used to construct AFM. The atomic linearity probe and battery material surface should be used as two electrodes. A certain voltage is applied between battery material and needle tip. When the distance between battery material and needle tip is very close, the tunnel current will be generated. The piezoelectric ceramic material is used to control the needle tip to scan the battery material surface. The probe is in the vertical direction of battery material. The variation of the current in the upper tunnel reflects the fluctuation of material characteristics. The characteristics of battery pack materials can be analyzed by atomic force microscopy based on IPC. The experimental results show that the average accuracy and analysis time of this method are 98.89% and 5.81ms, and the analysis effect is good. [ABSTRACT FROM AUTHOR]

Energy policy of EU promotes electro-mobility, especially the use of bicycles and electric bicycles. PEDELEC is a form of an electric bicycle that does not require a registry plate, and with a battery power 250 W electric motor helps the driver to overcome the altitude differences and influence of the wind. Batteries for electric bicycles are based on Li-Ion technology. Battery packs are made of standard cells that have a lifecycle of 1000 cycles. In realistic exploration conditions, the lifecycle is four years and up to a third of the declared cycle of use. The reason for this is the climatic conditions which lead to increased temperatures in usage and charging temperatures, which significantly reduce their life cycle. Paper on a practical example shows the dynamics of PEDELEC usage, energy needs for specific route characteristics, as well as changes in the thermal pattern of the battery and its condition after 4 years of use. The analysis was performed with Non-Destructive Testing (NDT) using infrared thermography, which confirmed the inhomogeneity of thermal patterns and the moment of final battery failure. [ABSTRACT FROM AUTHOR]

In this paper, an active equalization method based on redundant battery is proposed. A redundant battery is added to a battery pack consisting of several series batteries. According to the capacity and SOC (state-of-charge) of series batteries in the battery pack, one of these batteries is in parallel with the redundant battery in a certain time period. On the one hand, the energy is transferred between the redundant battery and the equalized batteries. On the other hand, during the charging or discharging process, the redundant battery acts as a power source, which reduces the current of the equalized battery. By adjusting the length of time that redundant battery and series batteries are connected in parallel, the purpose of battery equalization will be achieved. The balance current is limited only by the maximum charge–discharge ratio of the batteries. As long as the sum of the difference of series batteries capacity is less than the redundant battery capacity, the balance of all batteries can be achieved. Compared with other active equalization methods, the energy storage element (redundant battery) is used to be the main component of the equalization circuit in this method. It not only has the advantages of simple equalization circuit and large equalization current, but also has higher energy density of battery pack. In this paper, the equalization circuit is given, and the equalization strategy with accurate battery parameters and uncertain battery parameters is proposed. The experimental results also verify the correctness of the theoretical analysis and modeling. [ABSTRACT FROM AUTHOR]

A pack of batteries is one of the most important and expensive assemblies for an electric vehicle. A pack of batteries is comprised of several batteries connected in series. The number of the batteries connected depends on the operating voltage of the vehicle's on-board system as well as on the individual characteristics of the batteries used, e.g. the operating voltage of a single cell. One or several cells of a pack of batteries could be damaged if improperly exploiting an electric vehicle- excessively discharging the batteries or overloading the electric vehicle. If a self-converted vehicle does not use an intellectual BMS (battery management system) that can identify and register voltage drop for any individual cell in the high-load regime, e.g. when accelerating, it is difficult to identify and change the cells damaged. In case a cell does not demonstrate a complete failure, it is almost impossible to identify a defect in any regime other than the load regime. The research developed and compared three different methods for identifying defective battery cells. The methods were approbated on a converted Renault Clio. The experiment involved making voltage measurements in road tests, running the electric vehicle on a roll test bench and making voltage measurements of maximally discharged batteries in the no-load regime. A comparison of the measurement results revealed that the measurements made in the road tests were the most accurate and useful. After the experiment, the defective battery cells were replaced, thereby restoring the performance of the battery pack. [ABSTRACT FROM AUTHOR]

• The predicted results agree with the experimental results an average error of 1.28%. • Coolant-improved flow direction and thermophysical properties significantly affect the decreasing maximum operating temperature and temperature gradient across a cell. • The highest temperatures of the battery module are 30.06 °C, 30.00 °C, 29.91 °C, 29.89 °C, and 29.49 °C for models II, IV, III, I, and V. • The maximum temperature gradient across a cell, models I, II, and III give the highest value [0.42 °C], and consequently, models [0.40 °C] and model v [0.15 °C]. The operating battery temperature significantly affects electric vehicle performance, reliability, and safety. Therefore, batteries need to keep within the operating temperature design. The 3D Eulerian model is applied to determine battery thermal behavior with five different flow directions of coolant throughout the battery pack jacket. The computational domain consists of sixty cylindrical Li-ion cells inserted into the cooling module socket with constant power input conditions. The predicted results are consistent with the experimental results, with an average error of 1.28%. Coolant-improved flow direction and thermophysical properties significantly affect the decreasing maximum operating temperature and temperature gradient across a cell. The highest temperatures of the battery module are 30.06 °C, 30.00 °C, 29.91 °C, 29.89 °C, and 29.49 °C for models II, IV, III, I, and V, respectively. In addition, for the maximum temperature gradient across a cell, models I, II, and III yield the highest value [0.42 °C], followed by models IV [0.40 °C] and model V [0.15 °C], respectively. The proposed battery nanofluid cooling pack can therefore optimize the thermal management system of the EV pack. [ABSTRACT FROM AUTHOR]

• Proposed a Fuzzy FMEA for risk assessment of an immersion-cooled battery pack in EV. • Provide a detailed assessment of the probable causes and effects of failure to the design engineers. • An analysis of battery pack functions, failure modes, causes, and effects concerning their severity, occurrences, and detection ranks. • The most important causes of failure are sealing, BMS, structure design and assembly of mechanical components. • Using fuzzy inference engine, the RPN values are modified to improve the FMEA. Vehicle electrification is one of the changes in the modern-day car enterprise trend. The battery pack is the most vital and precarious part of a battery-powered electric vehicle, which necessitates accurate and reliable designs to ensure acceptable safety. To this end, one of the tried and tested methods that help identify problems and make products more reliable is Failure Modes and Effect Analysis (FMEA). This paper presents a Fuzzy FMEA for risk assessment of an immersion-cooled battery pack (ICBP) in electric vehicles. As a new technology, immersion cooling can facilitate high-rate fast charging and a longer battery life cycle for lithium-ion batteries. Different failure modes and relevant causes and effects are investigated in this vein. Each failure's severity, occurrence, and detection rank are extracted and displayed as a standard FMEA table. The monitoring results of all stages of design, manufacture, and initial tests indicate that the most important causes of failure in an ICBP are the sealing method, BMS function, cell temperature control, structure, and assembly of mechanical components. To some extent, it was attempted to reduce the occurrence of failures by recommending actions to reduce the occurrence of those failures. Consequently, a significant improvement was achieved, and the production and installation of problematic parts were managed efficiently and effectively with the help of an FMEA control plan table. [ABSTRACT FROM AUTHOR]

The studies on an integrated approach for the battery (cell level), battery pack (system level) and battery pack enclosure (system level) are nascent till date. The present work proposes a combined approach for studying the coupled electrochemical-mechanical performance of the battery (cell level), battery pack and enclosure (system level). In this context, five research problems are undertaken involving the design parameters for the performance evaluation of batteries. The first issue undertaken is battery performance under stress conditions and for that varying initial stress and real-time stresses were applied, and variation in the capacity of the battery packs was studied. Initial stress was found to be in negative relation with the battery capacity. For understanding the mechanical damage (leakage, deformation, etc.), characterization of the battery cell under impact loading was done by subjecting battery cells to different impact loads and impact analysis was done using six statistical features extracted from the impact force processed signal of each test, namely: peak value, mean value, variance, skewness, kurtosis and pulse width. The third issue regards the manufacturing defects in the cell, which can potentially lead to inconsistency of cells performance in a pack and thus lower its total cycle life. Support vector classification clustering methods were applied to form a battery pack with similar performing cells and performance of the pack was compared with industrial packs in which earlier one was found to be better. The fourth research challenge involved the mechanical performance parameters such as strength, deformation, and natural frequency, which, in addition to temperature, are also critical to battery pack safety in the event of impact and vibrations under driving conditions. ANSIS and NSGA-II based approaches were used to optimize the battery design and resultant device shown maximum deformation reduced by 22.2%, the value of minimum inherent frequency improved by 3.2% and the value of mass decreased by 11.6%. The fifth research problem highlighted how, due to the enormous production of electric vehicles, by 2020, there will be 250,000 tons of batteries that need to be recycled. A combined experimental-numerical framework has been thereby suggested to mitigate it. The study resulted in the formation of an online monitoring system and safety design of batteries at both cell and system level (pack and enclosure). [ABSTRACT FROM AUTHOR]

The application of lithium‐ion batteries especially for electric vehicles has been limited by the factors of safety, lifetime, charging time, and cost. One of the principal limitations is that the performance of Li‐ion batteries drops intensely in a cold environment. Cold environment dramatically reduces the available capacity of the batteries and increases its internal impedance at the same time. Therefore, the estimation of state‐of‐health is of great importance in battery performance evaluation and lifetime prediction. Furthermore, the heating methods need to be developed to ensure that batteries work in abnormal temperature conditions. This paper conducts a comprehensive review specifically on the poor performance of lithium‐ion cells under severe conditions. The content contains three sections. First, a comprehensive study on the aging mechanisms of lithium‐ion batteries at cold temperatures is undertaken. Second, the estimation methods of the health state of the batteries are conducted, which is vital to understand the fundamentals and quantify the performance and aging effects for lithium‐ion batteries. Third, the heating methods are classified and studied in detail to reduce the degradation mechanism and promote the performance of lithium‐ion batteries under sub‐zero conditions. [ABSTRACT FROM AUTHOR]

Abstract The reliability assessment of battery packs is an important topic in the reliability design of electric vehicles. To improve the accuracy of the reliability analysis, a modified reliability model for lithium-ion battery packs is developed that couples multiphysics models, degradation models, and a multistate system reliability model. For the degradation models, a stochastic capacity degradation model and a dynamic response impedance (DRI) model are established based on experimental data: a) the stochastic capacity degradation characteristics of cells are investigated, and b) the dynamic response characteristics of the impedance with degradation and changing temperature are studied. It is found that Weibull distribution is slightly more appropriate than normal distribution when the temperature is 25 °C, then reversed with increasing temperature. The algorithm for distribution selection is proposed to describing this concept drift phenomenon. Then, the influence of DRI on the thermal performance is analyzed. Finally, reliability assessment of battery pack and several calculation examples are implemented for comparative analysis. The results show that the fading rate of cells in battery pack are accelerated when DRI is incorporated. Thus, multiphysics-based system reliability model with considering the stochastic capacity degradation and DRI enables more scientific and accurate reliability evaluation of battery pack. Highlights • A modified reliability model for lithium-ion battery packs is developed. • A stochastic degradation model with normal and Weibull distribution is established. • A temperature and capacity dependent dynamic response impedance model is established. • The effect of dynamic response impedance on reliability of battery pack is analyzed. • The simulation results show the fading rate of cells in battery pack are accelerated. [ABSTRACT FROM AUTHOR]

Summary: By year 2020, due to enormous growth of production of electric vehicles, it is estimated that approximately 250 000 tons of battery must be disposed or recycled. Till date, the technology to recycle this much amount of batteries in a single year does not exist. Nor, do the methods for recycling are standardized and regulated because of differences in configurations of battery packs. This article conducts a systematic review on research of recycling methods for battery pack used in various stages such as from the dismantling/ disassembly of the battery pack, the detection of the residual energy of the battery, and the recycling/recovery of materials from the battery. The review summarizes basically the 2 main aspects of recycling of battery pack: the mechanical procedure and the chemical recycling. The work describes the existing recycling technology in these 2 aspects and identifies the important research problems in the process of recycling of battery pack such as (1) complexity of dismantling process of battery pack; (2) diversity of connectors used in battery pack; (3) safety of dismantling of battery pack; (4) instability of chemical materials in battery; (5) the chaos of the recycling market; and (6) emerging battery dismantling technologies. One important direction suggested is the automation of battery pack disassembly, which is a main factor towards formulation of generic framework for recycling of battery pack in an efficient manner. Based on these gaps, the present work also proposes a framework for the recycling of battery pack by combining the semi‐automation mechanical procedure of battery pack and enhanced chemical recycling of battery for recovery of vital materials. Future work for authors is to work on establishing and validation of proposed framework. The advantages of the proposed framework are compared with that obtained from the existing framework. The proposed framework when used shall result in efficient and effective recycling of battery module and promote greener environment. [ABSTRACT FROM AUTHOR]

A battery pack is the main energy storage element, and directly affects the performance of an electric vehicle. Battery thermal management system research and its development for a modern electric vehicle is required. This paper selects the forced air cooling of battery pack as the research object, and uses simulation methods to research the heat dissipation performance with different structures of battery packs. The results indicate that according to the four types of transient state conditions, the rising temperature of both battery packs are significantly higher than the temperature difference, the maximum temperature rise and temperature difference of a horizontal battery pack are lower than a longitudinal battery pack. When an electric vehicle begins to decrease speed, the curves of temperature rising and temperature difference increase. This shows the internal heat is continuously rising, so even in a electric vehicle beginning to decrease speed, the fan must work. The reference basis for choosing battery pack type and an analysis of heat flow field characteristics, including fan run-time control, are offered. [ABSTRACT FROM AUTHOR]

In this paper, the development of a three-dimensional (3D) lithium titanium oxide (LTO) pouch cell is presented to first better comprehend its thermal behavior within electrified vehicle applications, but also to propose a strong modeling base for future thermal management system. Current 3D-thermal models are based on electrochemical reactions which are in need for elaborated meshing effort and long computational time. There lacks a fast electro-thermal model which can capture voltage, current and thermal distribution variation during the whole process. The proposed thermal model is a reduce-effort temperature simulation approach involving a 0D-electrical model accommodating a 3D-thermal model to exclude electrochemical processes. The thermal model is based on heat-transfer theory and its temperature distribution prediction incorporates internal conduction and heat generation effect as well as convection. In addition, experimental tests are conducted to validate the model. Results show that both the heat dissipation rate and surface temperature uniformity data are in agreement with simulation results, which satisfies the application requirements for electrified vehicles. Additionally, a LTO battery pack sizing and modeling is also designed, applied and displays a non-uniformity of the cells under driving operation. Ultimately, the model will serve as a basis for the future development of a thermal strategy for LTO cells that operate in a large temperature range, which is a strong contribution to the existing body of scientific literature. [ABSTRACT FROM AUTHOR]

Serially connected batteries present a cell-to-cell variation in their electrochemical behavior that tends to increase over the lifetime. The decision for the best circular economy option for aged or defective battery packs – i.e., repair, remanufacturing, or recycling – requires comprehensive testing, analysis, and an according data basis. Remanufacturing of battery packs refers to the replacement of individual (sub-)modules or cells which are defective or show a diverging aging behavior to the rest of the battery units. A detection algorithm is required to decide if a significant inhomogeneity in a serial connection of batteries is present. For this reason, virtual battery packs are built based on the measurement of 12 individual batteries of the same type. Cell-to-cell variations are determined at the begin of life and a novel representation for the quantitative and qualitative analysis is given. This work extracts impedance-based features of different serial battery pack configurations through a novel comparative analysis approach. The features are extracted from Bode and Nyquist plots and the real and imaginary parts of the impedance itself. The detectability is analyzed depending on the number of cells and the underlying effects are discussed. A detailed sensitivity analysis is carried out for the most promising features, in which the influence of the cell-to-cell variations, the aging condition, and the aging mechanism are analyzed. The feature that shows the highest sensitivity, the so called low-frequency minimum, is able to detect single outliers within a high number of serially connected cells. [Display omitted] • Detection of inhomogeneities in serially connected lithium-ion batteries. • Novel representation of cell-to-cell variations for analysis of Nyquist plots. • Comprehensive analysis of multiple features for the detection of inhomogeneities. • Sensitivity analysis of the studied features concerning the detection accuracy. [ABSTRACT FROM AUTHOR]

As a key factor for the safety of electric vehicles, electric vehicles are focused on battery pack stability rather than vehicle dynamics. The stability of battery pack depends on the performance of suspensions and battery supporting system. Automobile suspensions can reduce the bumps and vibrations that come from road unevenness. Its purposes are to prevent the shock and vibration from transferring to the body, and reduce the vibration of the battery pack. To improve the performance of suspension systems of the electric vehicle and the stability of battery pack, the paper proposes a study on the interaction of electric vehicle roll and battery pack stability. 9-DOF vehicle vibration and roll model was established based on analysis of movement of the battery pack. Then simulation model was established to check the result to get the reasonable suspension stiffness by using Matlab/Simulink. The results show that the stiffness of the suspension is increased by configuring a high performance shock absorber and a short spring. Although it will inhibit roll, simply increasing the hardness of the shock absorber and the spring will cause a lot of negative effects. [ABSTRACT FROM AUTHOR]

This paper established the three degree of freedom mathematical model, based on the two degree of freedom linear model with two wheel steering. Then the dynamics differential equation is obtained. With a step input of the front wheel, observing and analyzing the yaw rate response and the side slip angle response in the whole process based on MATLAB/Simulink. Finally, by changing the position of the battery pack to transform the location of the gravity center of the whole vehicle, analyzing the impact on the electric vehicle's steering characteristic while the location of battery pack changed. [ABSTRACT FROM AUTHOR]

Vehicle battery systems are usually designed with a high number of cells connected in parallel to meet the stringent requirements of power and energy. The self-balancing characteristic of parallel cells allows a battery management system (BMS) to approximate the cells as one equivalent cell with a single state of health (SoH) value, estimated either as capacity fade (SoH E ) or resistance increase (SoH P ). A single SoH value is however not applicable if the initial SoH of each cell is different, which can occur when cell properties change due to inconsistent manufacturing processes or in-homogeneous operating environments. As such this work quantifies the convergence of SoH E and SoH P due to initial differences in cell SoH and examines the convergence factors. Four 3 Ah 18650 cells connected in parallel at 25 °C are aged by charging and discharging for 500 cycles. For an initial SoH E difference of 40% and SoH P difference of 45%, SoH E converge to 10% and SoH P to 30% by the end of the experiment. From this, a strong linear correlation between ΔSoH E and ΔSoH P is also observed. The results therefore imply that a BMS should consider a calibration strategy to accurately estimate the SoH of parallel cells until convergence is reached. [ABSTRACT FROM AUTHOR]

Due to the importance of examining the temperature of battery packs (BYP), a study on the temperature of a lithium-ion BYP with 9 cylindrical cells is performed in this article. The BYP is filled with phase change material (PCM) to better temperature uniformity on the battery cells. The batteries and the PCM pack are placed in an air channel with two inlets. At the inlets, 4 arc blades are supposed to guide the airflow to enhance the uniformity of cooling in the BYP. By changing the horizontal and vertical distance (VD) of the batteries inside the pack, this study is carried out in 2500 s for the charging and discharging times of the batteries (1.5C rate). The thermal analysis is done on the batteries using COMSOL software. The results show that an increment in the horizontal distance (HD) of batteries has less effect on battery temperature (T-BT) and PCM phase change compared to their VD. By enhancing the horizontal and VDs of the batteries, the value of the PCM phase change during the maximum T-BT is higher. The heat transfer coefficient (HTCT) between the PCM and the air is also decreased by increasing the distance between the batteries. The T-BTs is not significantly impacted by changing the distance between them. • Study thermal management of a lithium-ion BYP with 9 cylindrical cells is performed. • BYP is filled with PCM to better temperature uniformity on the battery cells. • T-BTs is not significantly impacted by changing the distance between them. • HTCT between the PCM and air is also decreased by increasing the distance. [ABSTRACT FROM AUTHOR]

In this investigation, a systematic surrogate-based optimization design framework for a battery pack is presented. An air-cooling battery pack equipped on electric vehicles is first designed. Finite element analysis (FEA) results of the baseline design show that global maximum stresses under x-axis and y-axis transient acceleration shock condition are both above the tensile limit of material. Selecting the panel and beam thickness of battery pack as design variables, with global maximum stress constraints in shock cases, a multi-objective optimization problem is implemented using metamodel technique and multi-objective particle-swarm-optimization (MOPSO) algorithm to simultaneously minimize the total mass and maximize the restrained basic frequency. It is found that 2nd order polynomial response surface (PRS), 3rd order PRS and radial basis function (RBF) are the most accurate and appropriate metamodels for restrained basic frequency, global maximum stresses under x-axis and y-axis shock conditions respectively. Results demonstrate that all the optimal solutions in Pareto Frontier have heavier weight and lower frequency compared with baseline design due to the restriction of global maximum stress response. Finally, two optimal schemes, "Knee Point" and "lightest weight", satisfied both of the stress constraint conditions, show great consistency with FEA results and can be selected as alternative improved schemes. [ABSTRACT FROM AUTHOR]

Variations in cell properties are unavoidable and can be caused by manufacturing tolerances and usage conditions. As a result of this, cells connected in series may have different voltages and states of charge that limit the energy and power capability of the complete battery pack. Methods of removing this energy imbalance have been extensively reported within literature. However, there has been little discussion around the effect that such variation has when cells are connected electrically in parallel. This work aims to explore the impact of connecting cells, with varied properties, in parallel and the issues regarding energy imbalance and battery management that may arise. This has been achieved through analysing experimental data and a validated model. The main results from this study highlight that significant differences in current flow can occur between cells within a parallel stack that will affect how the cells age and the temperature distribution within the battery assembly. [ABSTRACT FROM AUTHOR]

• Opportunity and bus garage charging schemes for battery electric buses. • Operating model for charging buses along the whole daily service. • System cost minimization via number of chargers, battery size and charging schemes. • Optimization algorithms to define the start time of electric charging operation. • Model applicability and charging performance tested through numerical instances. This paper analyzes the new operations induced by the energy range limitation in battery electric bus (BEB) systems to ensure the service provision along the whole day. An operating model has been developed to estimate the number of resources to be deployed (extra vehicles and charging facilities) for two charging schemes: charging at bus garage facility and opportunity charging at on-street chargers. Firstly, the model calculates the entrance and exit time of buses in service assuming an unlimited battery capacity, caused by demand and headway variations in different time periods along day. Then, based on the previous results, the model estimates the moment when vehicles will run out of energy and proposes a charging schedule as well as new vehicle movements between chargers, bus garage and routes to maintain the targeted headway. Consequently, the model is able to calculate the number of resources needed and the total cost for a given route and battery size, allowing cost and performance comparison to diesel and hybrid powertrains. The estimated results in two bus routes in Barcelona indicate that the purchasing cost of BEB vehicles (670,000 euros/veh for articulated, 500,000Euros/veh for standard vehicles, both depreciated over a lifetime of 15 years), battery packs (231 Euro/kWh purchased, depreciated over a lifetime of 10 years), as well as the investment in chargers, are still high to clearly justify their cost-competitiveness against diesel or hybrid counterparts. Nevertheless, if the acquisition cost of both vehicles and battery pack are only reduced by 9%, the BEB technology may present cost savings for transit agencies. It only happens if the fleet size is as large as the corresponding to diesel and hybrid technologies. Opportunity charging is resulted to be more cost- efficient than charging at bus garage for small battery packs, routes with acceptable time headway adherence and, specially, when fast chargers are located very close to terminal stops. Nevertheless, when the real bus route design and operation do not fulfill these standards, charging scheme at bus garage is preferable. [ABSTRACT FROM AUTHOR]

Large-scale commercialization of electric vehicles (EVs) seeks to develop battery systems with higher energy efficiency and improved thermal performance. Integrating simulation-based design optimization in battery development process expands the possibilities for novel design exploration. This study presents a dual-stage multiphysics simulation optimization methodology for comprehensive concept design of Lithium-ion (Li-ion) battery packs for EV applications. At the first stage, multi-objective optimization of electrochemical thermally coupled cells is performed using genetic algorithm considering the specific energy and the maximum temperature of the cells as design objectives. At the second stage, the energy efficiency and the thermal performances of each optimally designed cell are evaluated under pack operation to account for cell-to-pack interactions under realistic working scenarios. When operating at 1.5 C discharge current, the battery pack comprising optimally designed cells for which the specific energy and the maximum temperature are equally weighted delivers the highest specific energy with enhanced thermal performance. The most favorable pack design shows 8% reduction in maximum pack temperature and 16.1% reduction in module-to-module temperature variations compared to commercially available pack. The methodology for design optimization presented in this work is generic, providing valuable knowledge for future cell and pack designs that employ different chemistries and configurations. • Novel battery pack design methodology is proposed through a multiphysics simulation optimization framework. • Multi-objective optimization is used for electrochemical thermally coupled battery cells. • Thermal performance of battery cells is essential to improved battery pack performance. • Generic simulation-based optimization methodology for future design of battery cells and packs. [ABSTRACT FROM AUTHOR]

• A 35kWh battery pack with a novel hybrid thermal management system is prototyped. • Phase change material is innovatively integrated with cooling plate. • The battery thermal management at the battery pack level and module level is studied. • Both cooling and thermal insulation performances are investigated. • Desirable control strategies are obtained for battery pack under 0.5C to 1.5C discharge rates. Controlling the temperature of a battery pack within an optimal range and ensuring uniform temperature distribution are the key to improving battery life. With the elevating energy density of batteries, more efficient and energy-saving thermal management system is urgently required for improving electric vehicle (EV) performance in terms of safety and long-term durability. In this work, a novel hybrid thermal management system towards a high-voltage battery pack for EVs is developed. Both passive and active components are integrated into the cooling plate to provide a synergistic function. A 35kWh battery pack incorporated with electrical, mechanical and thermal management components was designed, manufactured and integrated. As the core hardware, a pack-level cooling plate set was innovatively designed by integrating with phase change material (PCM). The results show that the combined passive and active cooling strategy ensured a desirable working temperature below 40˚C and a uniform heat distribution across the entire pack at discharging rates ranging from 0.5C to 1.5C under customized control strategies. Moreover, the cycling performance of air cooling and hybrid cooling, as well as the thermal insulation performance at both battery module level and pack level are compared, demonstrating the superior thermal management capability of the hybrid solution. [ABSTRACT FROM AUTHOR]

A serious issue relative to the construction of electronic devices is proper power source selection. This problem is of particular importance when we are dealing with portable devices operating in varying environmental conditions, such as military equipment. A serious problem in the construction of electronic devices is the correct selection of the power source. In these types of devices, lithium-ion batteries are commonly used nowadays, and in particular their variety—lithium iron phosphate battery—LiFePO4. Apart from the many advantages of this type of battery offers, such as high power and energy density, a high number of charge and discharge cycles, and low self-discharge. They also have a major drawback—a risk of damage due to excessive discharge or overcharge. This article studies the process of charging and discharging a battery pack composed of cells with different initial charge levels. An attempt was made to determine the risk of damage to the cells relative to the differences in the initial charge level of the battery pack cells. It was verified, whether the successive charging and discharging cycles reduce or increase the differences in the amount of energy stored in individual cells of the pack. [ABSTRACT FROM AUTHOR]

Reliability optimization has always been an important topic in the application of lithium-ion batteries in electric vehicles. To optimize the redundancy and layout design of battery packs accurately and efficiently, a novel reliability optimization method based on a multiphysics coupling simulation and a response surface methodology is proposed. An electrochemical-thermal-fluid dynamics model, a temperature-dependent stochastic degradation model and a multistate performance reliability model are developed. A response surface method with the Box-Behnken design method is applied to reduce the number of simulation trials. Then, the redundancy scheme and two layouts of a battery pack are optimized, followed by a sensitivity analysis of the design parameters. The results show that a large spacing in the direction of air flow contributes to improving system reliability. In this case, for the layout of a cross arrangement with equal spacing, the optimal reliability design scheme of a 5 × 5 parallel series with optimal design parameters can improve the cycle life from approximately 1989 to 2933 when taking 90% system reliability as the criterion. The collaborative optimization of redundancy and layout is of great importance to extend the service life and improve the system reliability of battery packs. • A novel reliability optimization method for lithium-ion battery pack is proposed. • This method combines multiphysics simulation and response surface methodology. • Collaborative optimization of redundancy and layout is implemented efficiently. • A optimal redundancy scheme with optimal layout of a battery pack is determined. [ABSTRACT FROM AUTHOR]

Lithium-ion battery packs are widely deployed as power sources in transportation electrification solutions. To ensure safe and reliable operation of battery packs, it is of critical importance to monitor operation status and diagnose the running faults in a timely manner. This study investigates a novel fault diagnosis and abnormality detection method for battery packs of electric scooters based on statistical distribution of operation data that are stored in the cloud monitoring platform. According to the battery current and scooter speed, the operation states of electric scooters are clarified, and the diagnosis coefficient is determined based on the Gaussian distribution to highlight the parameter variation in each state. On this basis, the K-means clustering algorithm, the Z-score method and 3σ screening approach are exploited to detect and locate the abnormal cells. By analyzing the abnormalities hidden beneath the external measurement and calculating the fault frequency of each cell in pack, the proposed algorithm can identify the faulty type and locate the faulty cell in a timely manner. Experimental results validate that the proposed method can accurately diagnose faults and monitor the status of battery packs. This theoretical study with practical implications shows the promising research direction of combining data mining technologies with machine learning methods for fault diagnosis and safety management of complex dynamical systems. • The operation state of electric scooter is classified by current and speed. • A faults diagnosis and state monitoring scheme is proposed for lithium-ion battery. • The outlier screening algorithm is employed to detect and locate abnormal cell. • Fault frequency is imported to quantitatively evaluate healthy status of battery. [ABSTRACT FROM AUTHOR]

• A pack comprising the electro-thermal coupling of individual cells was developed. • Z shape module shows a significant advantage over a ladder configuration. • The correlation between system inhomogeneity and design parameters was quantified. • Contact resistance has the highest impact on the inhomogeneity of a system. • There is not a strong correlation between system inhomogeneity and C-rate. Cell-to-cell variations can originate from manufacturing inconsistency or poor design of the battery pack/thermal management system. The potential impact of such variations may limit the energy capacity of the pack, which for electric vehicle applications leads to reduced range, increased degradation along with state of health dispersion within a pack. The latter is known to reduce the accessible energy and the overcharging/discharging of some of the cells within a system, which may cause safety concerns. This study investigates the short-term impact of such effects, which is highly important for designing of an energy storage system. A generic pack model comprising individual cell models is developed in Simscape and validated for a 1s-15p module architecture. The results highlight that a number of cells and interconnection resistance values between the cells are the dominant factors for cell-to-cell variation. A Z shape module architecture show a significant advantage over a ladder configuration due to the reduced impact of interconnection resistance on differential current flow within the module. Current imbalance is significantly higher for a ladder system and its magnitude is not dependent on the module current. Capacity variation does not have a significant impact on the system. By increasing the capacity variation from 9% to 40% the current inhomogeneity increases from 4% to 13%, whilst 25% resistance variation leads to 22% current dispersion. Further, a linear relationship is observed between the current inhomogeneity and thermal gradient (Δ T). A 30 °C Δ T leads to 24% current variation within the module. [ABSTRACT FROM AUTHOR]

Heat transfer and phase change flow inside a Li-ion battery enclosure filled with a copper metal foam embedded in paraffin wax phase change material (PCM) are studied numerically. For simplicity and due to the axisymmetric of the enclosure geometry, half of the battery cell is considered as the heat source on the right wall. The vertical walls are considered symmetric, while the bottom wall is insulated, and the top wall is subjected to the convective heat transfer. The governing equations of the flow and heat transfer are presented as partial differential equations and then transformed into non-dimensional forms and solved by employing the finite element method. The local thermal equilibrium model was used, which limits the model to metal foams with high pore densities. For validation, results are compared with some of the well-known studies in the literature. The isotherms and streamlines are presented for three levels of heat pulse intensity. Both melting and solidification occur as a result of the unsteady heat pulses induced by the thermal source. The vertical location of the battery inside the enclosure can affect the streamlines and isotherm contours. Results show that for higher heat pulse powers, the melt volume fraction (MVF) increases, and heatsink will have higher efficiency. For a comparatively strong heat pulse, the efficiency was increased about seven times. [ABSTRACT FROM AUTHOR]

With the continuous improvement in battery life requirements, the modeling, analysis and management of battery pack life become an important topic in the design of electric vehicles. A more realistic and generic modeling method coupling the electrochemical, thermal, SEI formation model of cells, fluid dynamics and the series-parallel circuit model is proposed to accurately describe the coupling relationships and quantify the inconsistencies, including temperature and current. A life model including capacity fade and reliability is established to evaluate the life of lithium-ion battery pack system (LIBPs). And a model implementation method is established to raise the computational accuracy and efficiency, then, it is validated from the perspective of electrochemical, degradation, thermal performance and coupling effect using experiments. Moreover, the multiphysical behavior and life of LIBPs in different situations are analyzed and predicted, followed by the analysis of coupling effect, inconsistency, reliability and economy. The results show the degradation rate of LIBPs first decreases and then accelerates in the whole life. Furthermore, adding series cells is uneconomical to extend the life of LIBPs. Finally, a SoH balanced management method of changing the airflow direction is proposed to extend the life of LIBPs, and the optimal strategy for different SoH inconsistency are obtained. • A more realistic and generic model of battery pack is developed. • More comprehensive physical models are coupled for more accurate analysis and design. • Stochastic uncertainty and reliability are described by the percentile life model. • Quantitative analyses of coupling effects and inconsistencies have been carried out. • A SoH balanced management method and optimal strategy for battery pack is studied. [ABSTRACT FROM AUTHOR]

• The thermal and electrical models are developed for the series battery pack. • The multi-feature fault reasoning mechanism is established. • The proposed fault diagnosis scheme can isolate sensor and battery faults. • The residual evaluation method improves the accuracy of sensor fault diagnosis. • The Monte Carlo simulation and studentized residual methods improve robustness. Sensor fault diagnosis is a crucial technology for the battery management system. In this work, a sensor fault diagnosis scheme is proposed for the battery pack using equivalent models and particle filters. The thermal and electrical models of the battery pack are developed based on the Thevenin equivalent circuit model and the radial equivalent thermal model. The model parameters are identified by the recursive least square algorithm. The particle filter estimates the temperature and voltage of the battery pack, which overcomes the problems of system noise and nonlinearity. The studentized residual method based on a sliding window is developed to eliminate the residual outliers caused by uncertainty. Monte Carlo simulation is used to calculate the specific values of distribution function, mean and standard deviation for different sequences. The critical value table of the absolute value method of studentized residuals is obtained by interpolating. The cumulative sum of residual log-likelihood ratio method based on sliding windows is developed to calculate residuals. By multiple residual assessments, faults of voltage, current, temperature sensors, and batteries are detected and isolated. Different fault cases are simulated to verify the proposed scheme. The results of the experiment and simulation results verify the effectiveness of the proposed sensor fault diagnosis scheme. [ABSTRACT FROM AUTHOR]

Large-scale introduction of electric vehicles (EVs) to the market sets outstanding requirements for battery performance to extend vehicle driving range, prolong battery service life, and reduce battery costs. There is a growing need to accurately and robustly model the performance of both individual cells and their aggregated behavior when integrated into battery packs. This paper presents a novel methodology for Lithium-ion (Li-ion) battery pack simulations under actual operating conditions of an electric mining vehicle. The validated electrochemical-thermal models of Li-ion battery cells are scaled up into battery modules to emulate cell-to-cell variations within the battery pack while considering the random variability of battery cells, as well as electrical topology and thermal management of the pack. The performance of the battery pack model is evaluated using transient experimental data for the pack operating conditions within the mining environment. The simulation results show that the relative root mean square error for the voltage prediction is 0.7–1.7% and for the battery pack temperature 2–12%. The proposed methodology is general and it can be applied to other battery chemistries and electric vehicle types to perform multi-objective optimization to predict the performance of large battery packs. [ABSTRACT FROM AUTHOR]

Aiming at some models of electric vehicles without battery pack cooling device recently appeared on vehicle market, a feasibility analysis on electric vehicles without battery pack cooling device is conducted in this paper by both measurement test and model simulation on an EV with lithium iron phosphate battery but no cooling device currently in operation. The analysis leads to a conclusion that at the early operation stage of EV, due to small internal resistance and large heat capacity there is not much temperature rise in battery pack so if suitable initial temperature is assured (in particular with battery pack exchange mode) the battery pack can work without cooling device; However with the aging of battery, the internal resistance of battery greatly increases resulting in significant temperature rise, the heat dissipation of battery pack should be considered. [ABSTRACT FROM AUTHOR]

The consistency of battery cells directly influences the maximum available energy and the efficiency of the battery pack, and the energy utilization efficiency (EUE) is a key parameter for the balancing of batteries. Therefore, this paper focuses on the consistency modeling and state estimation of battery packs. In this study, a Copula-based battery pack consistency modeling method is developed. The proposed method shows superiority compared with two existing methods, because it can describe the statistical characteristics of the battery consistency parameters, and the dependence structure between parameters. The squared Euclidean distances between the marginal empirical cumulative distribution functions of the test data and that of the proposed model for capacity, resistance, and SOC are 0.029, 0.169, and 0.025, respectively. The errors of the correlation coefficients between the proposed model and the test data are within 0.12. Then the framework of battery pack EUE estimation using the consistency model is proposed. The accuracy of the proposed method is verified based on the test results of a battery pack with 95 cells connected in-series. The EUE estimation error is within 0.6% at various discharge current rates. The EUE estimation results could provide support for the performance evaluation and balancing of battery packs. • A Copula-based lithium-ion battery pack consistency modeling method is proposed. • Comparisons between proposed modeling method and traditional methods are performed. • A framework to estimate the battery pack energy utilization efficiency is proposed. • The estimation error of battery pack energy utilization efficiency is within 0.6%. [ABSTRACT FROM AUTHOR]

Various battery thermal management systems have been proposed in the literature to keep the battery operating temperature within the optimum operating range of 15 °C to 35 °C. Doing so leads to increased battery pack service life, safer operation, and reduced costs. Here, a comparative assessment of battery thermal management systems is presented, focusing on the development of the most recent proposed category of battery thermal management systems, liquid-to-vapor phase change cooling systems, and a competitive assessment is performed among these systems and with other battery thermal management systems. It is found that for prismatic battery packs it is best to use the tube based system, where the coolant fills tubes that are embedded within a metallic cold plate that separates the batteries. However, for cylindrical battery packs only one configuration of the cooling system has been proposed in the literature and it is determined that the best coolant among the possible options is ammonia. Ammonia performs the best for both cylindrical and prismatic battery packs. Further research is recommended to adapt tube based systems for cylindrical battery packs, and to investigate other integrations between conventional cooling systems and liquid-to-vapor phase change systems. • Comparative assessment of recently developed categories of battery thermal management systems. • Focus on liquid-to-vapor phase change cooling systems. • Compares the liquid-to-vapor phase change cooling systems with conventional systems. [ABSTRACT FROM AUTHOR]