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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]

With the booming development of the modem vehicle industry, the safety problem caused by heat generation of battery pack is more and more obvious, an effective heat transfer system needs to be developed. Based on analyzing the average heat generation rate of a battery pack, a heat transfer simplified model of battery pack is established using a lumped-parameter method. This model is used to analyze the following parameters of an actual battery pack: time interval, fluid temperature, battery pack average temperature, transient heat transfer power, and total heat. The calculated results can be used to evaluate whether the heat transfer system is effective, or make the heat transfer system reasonable by choosing the optimum heat transfer parameters. The results also indicate that the strategy of applying fluid with constant temperature in the heat transfer system is not the best. [ABSTRACT FROM AUTHOR]

Abstract: Because of the inevitable inconsistency during manufacture and use of battery cells, cell variations in battery packs have significant impacts on battery pack capacities, durability and safety for electric vehicles (EVs). To reduce cell variations and increase pack capacity, cell equalization is essentially required. In the series of two papers, we discover that dissipative cell equalization (DCE) using dissipative resistances is a feasible on-line equalization method for battery packs in EVs. We subsequently propose on-line equalization algorithms for lithium-ion battery packs based on charging cell voltage curves (CCVCs). The objective of these algorithms is to maximize pack capacities by conditioning CCVCs. As the first paper of the series, we first briefly review equalization topologies and algorithms. We discover cell remaining charging capacity (RCC) can be on-line estimated and further propose DCE algorithm based on remaining charging capacity estimation (RCCE). We establish a pack model with 8 cells in series and simulate 4 scenes with different cell variations. RCCE–DCE algorithm is proved to be effective by comparing pack capacities with/without RCCE–DCE algorithm. The equalization capability and over-equalization prevention are further examined, and the result shows that RCCE–DCE algorithm is suitable for on-line equalization in EVs. [Copyright &y& Elsevier]

Abstract: In the first part of this work, we propose dissipative cell equalization (DCE) algorithm based on remaining charging capacity estimation (RCCE) and establish a pack model with 8 cells in series. The results show that RCCE-DCE algorithm is suitable for on-line equalization in electric vehicles (EVs) and no over-equalization happens. However, 1% pack capacity difference from the DCE theoretical pack capacity is observed with RCCE-DCE algorithm. Therefore, as the second part of the series, we propose fuzzy logic (FL) DCE algorithm based on charging cell voltage curves (CCVCs). Cell capacities and SOCs are fuzzily identified in FL-DCE algorithm by comparing cell voltages at the beginning and end of charging. Adaptive FL-DCE is further improved to prevent over-equalization and maintain the equalization capability. The simulation results show that pack capacity difference from the DCE theoretical pack capacity with the adaptive FL-DCE is smaller than that with RCCE-DCE algorithm, and the duration of the infant stage is also shorter. The proposed adaptive FL-DCE is suitable for on-line equalization in EVs and well prevents over-equalization. [Copyright &y& Elsevier]

This paper reviews the heat dissipation performance of battery pack with different structures (including: longitudinal battery pack, horizontal battery pack, and changing the position of air-inlet and air-outlet) and operation conditions (including: SOC state, charge and discharge rate, and practical operation condition), and finally arrives at the conclusions as follows: the average thermal power of 55Ah lithium-ion battery monomer decreases along with environment temperature rising, SOC state decreasing and charge and discharge rate falling; the maximum temperature rising and temperature difference of battery pack are not only relevant to the flow rate, but also related to the airflow duct structure, the battery pack with air-inlets on both sides is more conducive to the forced air cooling; the flow rate of battery pack at 70% SOC state is maximum, the maximum temperature rising and temperature difference of battery pack at 70% SOC state are minimum, and that of 90% SOC state are maximum; the flow rate and the average pressure drop between air-inlet and air-outlet both decrease along with charge and discharge rate increasing, but the maximum temperature rising and temperature difference of battery pack increase; as considering the practical operation condition of battery pack, the charge and discharge rate is between 0.5C and 0.8C, and the maximum temperature rising and maximum temperature difference of battery pack are 7.61°C and 4.29°C. Then the reference basis for heat flow field characteristic analysis and structure design of battery pack are offered. [ABSTRACT FROM AUTHOR]

Abstract: In battery packs with cells in parallel, the inter-cell connection resistances can cause unequal loads due to non-uniform interconnect overpotentials and consequentially lead to non-uniform heating. This article explores how load imbalances are generated in automotive applications, by describing a battery pack with finite interconnect resistances. Each cell inside the pack is represented by a pseudo 2D electrochemical model coupled with a lumped thermal model. Increasing the number of cells in parallel results in a linear increase in load non-uniformity, whilst increasing the ratio of interconnect to battery impedance results in a logarithmic increase in load non-uniformity, with cells closest to the load points experiencing the largest currents. Therefore, interconnect resistances of the order of mΩ can have a significant detrimental impact. Under steady state discharge the cell impedance changes until the loads balance. This process, however, can take hundreds of seconds and therefore may never happen under dynamic load cycles. Cycling within a narrow state-of-charge range and pulse loading are shown to be the most detrimental situations. Upon load removal, re-balancing can occur causing further heating. Simulation of a 12P7S pack under a real world load cycle shows that these effects could cause localised thermal runaway. [Copyright &y& Elsevier]

Abstract: A fuzzy logic-based energy management strategy for a hybrid power system used in electric vehicles was developed and verified in this paper. First, the topology structure of a hybrid power system was put forward that the ultracapacitors connected with the battery pack in parallel after a bidirectional DC/DC converter. To improve the systematic efficiency, a fuzzy logic-based energy management strategy was designed and the control model was built. We proposed an active electricity management module for the ultracapacitors on the basis of the real-time vehicle velocity. Then, the vehicle model, the interface model of the electrical load and the xPC Target were built with the Simulink/State flow soft. Finally, the hybrid power/energy system-in-loop simulation experiment was carried out to verify the energy management strategy under the Urban Dynamometer Driving Schedule (UDDS) dynamic driving cycle. The results show the proposed fuzzy logic-based energy management strategy can ensure the battery pack working in high efficiency range and show better performance than the traditional logic threshold-based control strategy. The hybrid power system’s electricity economy was improved by 4.1% and the bad influences of the high-current discharging and charging on battery pack were avoided successfully. [Copyright &y& Elsevier]

Abstract: Due to cell-to-cell variations in battery pack, it is hard to model the behavior of the battery pack accurately; as a result, accurate State of Charge (SoC) estimation of battery pack remains very challenging and problematic. This paper tries to put effort on estimating the SoC of cells series lithium-ion battery pack for electric vehicles with adaptive data-driven based SoC estimator. First, a lumped parameter equivalent circuit model is developed. Second, to avoid the drawbacks of cell-to-cell variations in battery pack, a filtering approach for ensuring the performance of capacity/resistance conformity in battery pack has been proposed. The multi-cells “pack model” can be simplified by the unit model. Third, the adaptive extended Kalman filter algorithm has been used to achieve accurate SoC estimates for battery packs. Last, to analyze the robustness and the reliability of the proposed approach for cells and battery pack, the federal urban driving schedule and dynamic stress test have been conducted respectively. The results indicate that the proposed approach not only ensures higher voltage and SoC estimation accuracy for cells, but also achieves desirable prediction precision for battery pack, both the pack's voltage and SoC estimation error are less than 2%. [Copyright &y& Elsevier]

Highlights: [•] Characterized two novel high capacity electrode materials for Li-ion batteries. [•] A numerical discharge model was run to characterize Li-ion cell behavior. [•] Engineering model of Li-ion battery pack developed from cell fundamentals. [•] ESP-r model integrated micro-cogeneration and high capacity Li-ion storage. [•] Higher capacity batteries shown to improve micro-cogeneration systems. [Copyright &y& Elsevier]

Highlights: [•] We propose a Mean-plus-Difference Model (M+D Model) for battery pack. [•] Mean model represents the whole pack and difference model investigates inconsistency. [•] OCV differences are estimated using cell difference model for LiFePO4 pack. [•] SOC strategy is proposed to identify SOC inconsistency by lowering pack SOC in HEV. [•] SOC differences are determined using SOC-difference/OCV-difference curve. [Copyright &y& Elsevier]

Abstract: Electric vehicle cooling modes are divided into air cooling, liquid cooling and phase change material cooling, the air cooling is divided into natural air cooling and forced air cooling. This paper selects the forced air cooling as the study object, and researches the heat dissipation performance of different airflow duct modes, the results indicated that: as considering that changing the longitudinal battery pack into horizontal battery pack, it could improve the heat dissipation performance by shorting airflow path; it increases the contact area for thermal conduction by adding bottom duct, and the area of battery pack top exists natural convection, so the heat dissipation performance of bottom duct mode is more superior; for battery pack with bottom duct mode, it uses the double “U” type duct instead of double “1” type duct in order to improve the heat dissipation performance; when the heat dissipation condition is poor, it could reduce the SOC state or charge & discharge rate to satisfy the heat dissipation performance requirements; as considering the practical operation condition of battery pack with double “U” type duct, it has a large margin of high charge and discharge rate to meet the needs of electric vehicle acceleration or deceleration operation. [Copyright &y& Elsevier]

• 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]

Power batteries are treated as heart of the electrical vehicles and they release huge amount of heat throughout both charging and discharging processes. Hence Battery Thermal Management System (BTMS) is designed in order to control maximum temperature rise within a battery pack and to maintain even temperature distribution among the cells for increasing life span, efficiency and safety of the batteries. With an enticing characteristic feature such as low parasitic power, low weight, uniform temperature distribution among cells, passive thermal management system namely Phase Change Material (PCM) is justified as an efficient BTMS in recent years. The current work begins with the introduction of Hybrid Thermal Management System combined with PCM for enhancing cooling performance of BTMS. In addition to that, some of the thermal conductivity enrichment techniques for PCM (i.e. the usage of thermal conductive particles, cellular foams, encapsulation) are summarized. Research studies which involves various key parameters such as cell spacing, mass of PCM, thickness of PCM, specific heat capacity and thermal conductivity influencing the performance of systems are reviewed. Eventually, the results of several studies on PCM cooling are proposed in the conclusion part based on analysis of previous works. • Battery thermal management system of PCM assisted liquid cooling provides uniform temperature distribution among the cells. • Addition of high thermal conductive particles into the PCM helps in enhancing thermal conductivity of PCM. • Metal foams have a continuous skeleton structure with large thermal conductivity, and high structural strength. • Addition of high thermal conductive particles into PCM,CPCM which incorporates porous foams to PCM exhibits more conductivity. [ABSTRACT FROM AUTHOR]

Depending on the level of electrification ([PH]EV, [M]HEV) and cell format (pouch, prismatic, cylindrical), the number of individual cells in a vehicle's battery pack can span several orders of magnitude (from tens to thousands). In this paper, we develop a novel analytical framework to investigate the impact of cell-level manufacturing variability on pack performance. Statistical distributions of pack energy and pack power are derived for any NsMp pack configurations and any level of cell-to-cell variability. These distributions are used to develop vehicle-dependent cell-level manufacturing requirements. The degree to which the series direction negatively affects pack statistics, and the degree to which the parallel direction improves pack statistics, is first quantified under a random sampling scenario. PHEV packs (96s1p) are found to have the highest pack-level statistical penalty, while EV packs made of small-format cylindrical cells (96s74p) incur virtually no statistical penalty. Pack-level statistics for Ns1p packs are shown to greatly benefit from the clustering of low-performing cells. Cell binning strategies for NsMp packs present both advantages and disadvantages. The impacts of cell aging and pack-level voltage limits are further discussed. The results of this study apply even in the presence of cell balancing and under partial SOC usage. [Display omitted] • A novel analytical model is developed to relate cell variability and pack statistics. • The model is valid for any level of cell variability and any pack configuration. • Pack distribution of energy and power is derived for different vehicle segments. • Cell binning strategies to optimize pack-level statistics are presented. • The effect of cell balancing, cell aging and pack-level voltage limits are discussed. [ABSTRACT FROM AUTHOR]

Abstract: Systems integration issues, such as electrical and thermal design and management of full battery packs – often containing hundreds of cells – have been rarely explored in the academic literature. In this paper we discuss the design and construction of a 9kWh battery pack for a motorsports application. The pack contained 504 lithium cells arranged into 2 sidepods, each containing 3 modules, with each module in a 12P7S configuration. This paper focuses particularly on testing the full battery pack and diagnosing subsequent problems related to cells being connected in parallel. We demonstrate how a full vehicle test can be used to identify malfunctioning strings of cells for further investigation. After individual cell testing it was concluded that a single high inter-cell contact resistance was causing currents to flow unevenly within the pack, leading to cells being unequally worked. This is supported by a Matlab/Simulink model of one battery module, including contact resistances. Over time the unequal current flowing through cells can lead to significant differences in cells’ state of charge and open circuit voltages, large currents flowing between cells even when the load is disconnected, cells discharging and aging more quickly than others, and jeopardise capacity and lifetime of the pack. [Copyright &y& Elsevier]

Abstract: A three-dimensional thermal model has been developed to gain better understanding of thermal behavior of battery cells in a pack under simulated driving cycles. The numerical approach incorporates a three-dimensional CFD pack-level sub-model, a one-dimensional battery pack network sub-model, and a three-dimensional thermal and electrochemical coupled cell/module level sub-model so that the battery non-uniform heat generation rate, the battery temperature distribution as well as battery temperature variation across a pack can be quickly predicted. In particular, the flow profiles of each individual battery cooling channel are calculated using the three-dimensional CFD sub-model. Using the predicted flow profiles of the cooling channel as flow boundary conditions the thermal behavior of battery cells is predicted using the one-dimensional battery pack network sub-model and the cell/module level thermal sub-model, in which both electrochemical reaction and double layer effect of battery cells are considered. The thermal behavior of battery cells is correlated through physical tests. Finally, the effects of the cooling flow of battery pack and the design of battery pack cooling system on non-uniformity of individual battery cell temperature and battery cell temperature variation across the pack under simulated US06 driving cycles are studied and discussed. [Copyright &y& Elsevier]

Abstract: Extended Kalman filtering is an intelligent and optimal means for estimating the state of a dynamic system. In order to use extended Kalman filtering to estimate the state of charge (SOC), we require a mathematical model that can accurately capture the dynamics of battery pack. In this paper, we propose a stochastic fuzzy neural network (SFNN) instead of the traditional neural network that has filtering effect on noisy input to model the battery nonlinear dynamic. Then, the paper studies the extended Kalman filtering SOC estimation method based on a SFNN model. The modeling test is realized on an 80Ah Ni/MH battery pack and the Federal Urban Driving Schedule (FUDS) cycle is used to verify the SOC estimation method. The maximum SOC estimation error is 0.6% compared with the real SOC obtained from the discharging test. [Copyright &y& Elsevier]

Lithium-ion (Li-ion) batteries are nowadays the best tradeoff between performance, cost, and lifetime to store electric power and energy effectively. The reliable determination of the batteries’ instantaneous power capability and energy content is mandatory for many mobile high-energy and power-consuming applications. Herein, the battery impedance and state of charge (\SOC) are the relevant values. In energy storage systems, these values are to be considered for each battery cell individually, due to arising limitations caused by cell-specific variations. Simple algorithms to determine the battery system’s impedance and \SOC are presented including parameter and state-estimation techniques. Furthermore, methods are derived making the impedance and \SOC determination possible for a large number of particular cells in a battery system. The applicability of the demonstrated algorithms for battery control unit implementation is proved incorporating data achieved from load scenarios applied to a cell stack Li-ion battery module. Cell impedance and \SOC variations could be detected precisely. Moreover, a combination of impedance and \SOC spread was identified during typical battery operation. [ABSTRACT FROM PUBLISHER]

Rechargeable battery industry will see significant growth in the use of battery systems for portable devices and power electronics, renewable energy storage, power systems for transportation, and telecom backup power applications. Despite such promising market sentiment, the battery system management remains as a challenging issue to be resolved in order to provide a safe and reliable power and energy storage system. Here we report advancement in the battery management approach by providing a solution to analyze battery performance variations in a lot of batteries produced from the same manufacturing process. A lot of 100 Li-ion cells were analyzed in order to quantify the inherent cell variations associated with cell manufacturing process and test protocol. Both statistical and electrochemical analyses were used to characterize and quantify the capacity variations among the cells along with other parameters that can be readily derived from the test results. Information extracted from a minimal testing of the cells in the lot and more intensive characterizations on a few cells including one as the nominal sample cell allows the establishment of a single cell model (SCM), based on a generic equivalent circuit, with high accuracy in predicting cell performance. The analyses also permit a carefully crafted logic development of how to separate the origins that cause the cell variations in performance. Such separation of the attributes enable a proper tuning of the cell parameters in the model, which allows the accommodation of cell variations in a battery pack model to handle most of the imbalance issues. A careful validation of the SCM to predict performance of any arbitrary cell in the lot with high accuracy was demonstrated. Copyright © 2009 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

State-of-health (SOH) monitoring of lithium-ion batteries plays a key role in the reliable and safe operation of battery systems. Influenced by multiple factors, SOH is an aging path-dependent parameter, which challenges its accurate estimation and prediction. Numerous methods have been proposed for lithium-ion batteries SOH diagnostics and prognostics, but there is little discussion on how to characterize SOH. In this paper, we first review the existing characteristic parameters in defining battery SOH at cell-level and pack-level, and then propose some suggestions for SOH definitions. The impact of external influencing factors on battery degradation is introduced to lay a foundation for SOH estimation. SOH estimation methods are categorized by the parameters used to define SOH, i.e. capacity, impedance and aging-mechanism parameters. We discuss the goals of SOH monitoring and summarize its applications from short- and long-term perspectives accordingly. Finally, the challenges and future trends of battery SOH diagnostics and prognostics are thoroughly analyzed and discussed, in order to provide a comprehensive understanding for researchers and technologists. • Discuss how to comprehensively characterize battery SOH at cell-level and pack-level. • Analyze the strengths and weaknesses of the SOH estimation methods from the perspective of data acquisition sources. • Present the gaps between existing research on SOH estimations and SOH applications. • Summarize the challenges and prospects for SOH characterizations, estimations and applications. [ABSTRACT FROM AUTHOR]

The cooling structure of a battery pack and coupled liquid cooling and phase change material (PCM) were designed in a thermal management system to enhance the cooling performance and extend the service life of lithium-ion battery packs. Numerical simulations were conducted based on the finite volume method. This study focuses on factors such as the layout of the terminal, flow rate of the coolant, different sections of the cooling pipe, position of the cooling pipe, and coupled liquid cooling, and investigates their influences on the operating temperature. The results show that a reasonable terminal layout can reduce heat generation inside the batteries. The appropriate flow rate and position of the cooling pipe effectively reduced the maximum temperature and minimized energy consumption. Then, the PCM was placed between the adjacent batteries near the outlet to enhance the uniformity of the battery pack. The temperature difference was reduced to near 5 K. This study provides a clear direction for improving the cooling performance and extending the service life of battery packs. [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]

Abstract: A simple approach for using accelerating rate calorimetry data to simulate the thermal abuse resistance of battery packs is described. The thermal abuse tolerance of battery packs is estimated based on the exothermic behavior of a single cell and an energy balance than accounts for radiative, conductive, and convective heat transfer modes of the pack. For the specific example of a notebook computer pack containing eight 18650-size cells, the effects of cell position, heat of reaction, and heat-transfer coefficient are explored. Thermal runaway of the pack is more likely to be induced by thermal runaway of a single cell when that cell is in good contact with other cells and is close to the pack wall. [Copyright &y& Elsevier]

Abstract: Battery packs of multi-batteries supply high voltage when batteries are connected in series and high capacity when connected in parallel, which provides a new substitution of power supply for portable electronic device. A simulation method is, therefore, proposed to simulate the discharge behaviors of battery system with parallel and/or series connection. Using the simulation proposed, voltage, discharging capacity and residual capacity of the pack and individual battery at every time unit may be calculated at a given discharge current. When one of the batteries in the series-connection has a distinctly lower capacity, this battery reaches its fully discharged state sooner than the others during discharge. The simulated current distribution of a battery pack of two different-capacity batteries in parallel shows that although the pack is discharged at constant current, current through each battery is neither a constant nor proportional to its capacity. A battery of higher capacity carries a larger current. A pronounced change in current is observed near the end of the discharge process where voltage is near the cut-off value. We believe the proposed simulation method may be extended to a battery pack of multiple batteries of any capacity in any number and connections. [Copyright &y& Elsevier]

We discuss a rapid testing of capacity in Li-ion battery packs with impedance-measuring technology to evaluate their capability in mobile phones. Our measurements of the capacity and impedance at 1 kHz for various kinds of battery packs conclusively proved that there is a strong correlation between capacity and impedance. It can be applied even when the pack consists of not only a Li-ion battery but also a Positive Temperature Coefficient (PTC) device and a protection circuit in-series, and this correlation is largely unaffected by the degree of charge. The results we obtained from measuring impedance revealed the possibility of quickly assessing degradation in Li-ion battery packs. [Copyright &y& Elsevier]

A campaign of experiments was conducted in a previously designed bench-scale wind tunnel to determine the effectiveness of suppression of lithium ion battery fires with a clean agent, Novec 1230 (CF 3 CF 2 C(O)CF(CF 3) 2). The experiments were performed on twelve 18650 form factor, fully charged, lithium cobalt oxide cells arranged in a rectangular array without intercell spacing. A set of baseline experiments performed at 640 l min−1 of air flow, 320 l min−1 of air flow, and 186 l min−1 of nitrogen flow indicated that, while flaming combustion had a significant impact on the speed of thermal runaway propagation through the array, fully preventing combustion did not prevent propagation. Addition of gaseous Novec 1230 to 640 l min−1 air flow immediately after the thermal runaway of the first cell produced 8.5 vol% concentration of the agent. At this concentration, which is above that recommended for suppression of traditional fires, the agent failed to suppress flaming combustion and did not prevent propagation of thermal runaway through the array. Increasing the concentration of Novec 1230 to 15.2 vol% by reducing the air flow rate to 320 l min−1 reduced the flaming combustion efficiency below 18% and prevented complete thermal runaway propagation in 67% of tests. • Suppression of lithium ion battery fires with clean agent was investigated. • Thermal runaway propagation was induced in 18650 cell arrays mounted in wind tunnel. • Effects of purge flow composition on propagation dynamics and heat release were quantified. • Addition of 8.5 vol% of Novec 1230 to air flow failed to suppress propagation. • Addition of 15.2 vol% of Novec 1230 to air prevented full propagation in 67% of tests. [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]

In this article, analysis of average Nusselt number (Nu avg), which indicates the heat removal from the battery pack cooled by flowing fluid is carried out considering coupled heat transfer condition at the pack and coolant interface. Five categories of coolant, mainly gases, common oils, thermal oils, nanofluids, and liquid metals, are selected. In each coolant category, five fluids (having different Prandtl number Pr) are selected and passed over the Li-ion battery pack. The analysis is made for different conductivity ratio (Cr), heat generation term (Q gen), Reynolds number (Re), and Pr. Pr varying in the range 0.0208–511.5 (25 coolants) and Cr for each category of coolant having its own upper and lower limit are used to analyze the heat removed from the battery pack. Using single feed-forward network and integrating two feed-forward networks having multi-layers with back-propagation is employed for artificial neural network (ANN) modelling. In this modelling, the concept of the main network and space network is devised for multiple back propagation (MBP). The numerical analysis revealed that the temperature distribution in battery and fluid is greatly affected by increasing Cr. The maximum temperature located close to the upper edge of battery is found to get reduced significantly with the increase of Cr , but upto a certain limit above which reduction is marginal. The analysis carried out reveals that Cr and Q gen have no role in improving Nu avg while Pr and Re vary it significantly in each step. Moreover, Nu avg is found to increase with Re continuously irrespective of any Cr and Q gen. While, for oils with an increase in Pr and Re , Nu avg was found to reduce significantly. Nanofluids are found to be more effective in improving heat transfer from the battery pack when cooled by flowing nano-coolants over it. The MBP networks proposed are successfully trained, and hence they can be used for prediction of Nu avg. • Conjugate numerical analysis of battery cells is carried for several coolants. • Multiple back propagation modelling of Nusselt number is carried. • Nanofluids provide maximum heat transfer. • Multiple feed forward with back propagation predicts Nusselt number properly. [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]

Lithium-ion battery systems are becoming a major component in numerous applications. The thermal behaviour of cells should be monitored for many reasons. In this paper, the investigation of the energy balance for lithium-ion battery system is described. The electrothermal model allows to describe heat generation and heat dissipation processes in all components of a battery pack (BP). Moreover, this model can be easily adapted for bigger, modular battery systems, since the primitive in the proposed model is a single cell. A method to determine the energy balance through experimental investigations and to validate the model is also proposed. Four types of BPs with sixteen cylindrical 18650 lithium-ion cells were tested. The influence of both busbar material and the presence of heatsinks on the BP thermal conditions was investigated. The results show that the heat accumulated in cells can be decreased by 20% and the cell temperature lowered by 8 °C if additional elements are used in a BP. [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]

Since a battery pack consists of hundreds of cells in series and parallel, inconsistencies between cells make it difficult to create an explicit model to simulate its behaviors effectively. Therefore, the widely used and sophisticated model-based methods (such as Kalman filters) are difficult to apply to SOC (state of charge) estimation of battery packs. In this paper, a data-driven method based on Gaussian process regression (GPR) is proposed to provide a feasible solution. Its superiority includes the ability to approximate nonlinearity accurately, nonparametric modeling, and probabilistic predictions. First, a feature extraction strategy, including data preprocessing, correlation analysis, and principal component analysis, is employed to obtain a compacted input set with a high correlation with SOC. Second, the squared exponential kernel function is used, and the automatic relevance determination is applied to optimize the weights of features. Third, besides the regular GPR model, an autoregressive GPR model is also constructed to further improve estimation accuracy and confidence. The experimental results verify that the autoregressive model has better SOC estimation performance than the regular model, and its estimation error under different dynamic cycles, temperatures, aging conditions, and even extreme conditions is lower than 3.9%, and the confidence interval is also much narrower. • A feature extraction method is employed to obtain a crucial and compacted data set. • Gaussian process regression is used to predict the state of charge of battery pack. • Automatic relevance determination is used to optimize the weights of features. • An autoregressive model is created to improve estimation accuracy and confidence. • The method is verified in different dynamic cycles, temperatures, and aging states. [ABSTRACT FROM AUTHOR]

CubeSats and small satellite solutions are increasing in popularity as they enable a fast, cheap, and agile way for satellite applications. An essential component of nearly every satellite is the energy storage device, which is practically equal to a battery. Consequently, an overview of past, present, and future battery technologies for CubeSats is presented. CubeSats use typically commercial off-the-shelf (COTS) batteries. They are not primarily dedicated to space, so their suitability to the space environment needs to be evaluated. Batteries are also considered as potentially dangerous goods. Thus, there are guidelines and standards that specify safety criteria and tests for the batteries in order to be allowed for transportation and launch. Furthermore, the character of satellites' missions determines their demand on batteries in terms of current rates, depth-of-discharge, and lifetime. Thus, these expectations are discussed. A market survey was also carried out to identify currently available commercial battery solutions and their parameters. This work summarizes the status, requirements, and the market situation of batteries for CubeSats. [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]

• Adaptive federated Kalman filter is used for enhanced battery pack SOC estimation. • A fuzzy system is used to adapt to various cell SOC inconsistency distributions. • Accuracy is evaluated under SOC inconsistencies against conventional methods. • Fault tolerance is evaluated under the influence of measurement errors. Inconsistencies among battery cells and measurement errors have significant impacts on the accuracy and reliability of state of charge (SOC) estimations for series-connected battery packs. The aim of this paper is to propose a novel SOC estimation method for series-connected battery packs based on the fuzzy adaptive federated filtering. The mean-plus-difference model is employed to characterize the inconsistencies among battery cells. The fuzzy system is designed to improve the accuracy and adaptability of SOC estimation under cell inconsistencies. The SOC estimation value from a cell mean model and the standard deviation of SOC estimation are combined with a fuzzy system to determine their fusion weights. The master filter adaptively adjusts the information distribution coefficient according to the local filter estimation accuracy to improve reliability. Through simulation and experimentation on series-connected battery packs with different SOC distributions, the estimation accuracy of the proposed method is compared between the proposed method and the conventional methods. The SOC estimation accuracy of each battery cell is evaluated. The results show that, over the full SOC range, the root-mean-square error (RMSE) of the battery pack SOC estimation is less than 0.6% and 1.5% using online and offline parameters, respectively. The SOC estimation RMSEs of the battery cells using online and offline parameters are less than 0.4% and 1%, respectively. The fault tolerance is verified by artificially adding measurement errors. These accurate and reliable results show a strong prospect for the design and optimization of future clean and sustainable mobility. [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]

There is not much research carried out on factors such as temperature differences in different regions of battery pack, which is highly important and poses a great challenge. Temperature changes across batteries affect the battery pack performance and its life span largely. Thus, the present work proposes the Integrated Finite Element‐Meta‐Optimization Framework for solving this problem. The integrated framework includes the formulation of Finite Element Model of a battery pack and Meta‐Optimization Framework for multi‐objective minimization of three objectives such as the inter‐cell temperature differences, temperature standard deviation and the total volume of the cell. In this framework, firstly Support Vector Regression (SVR) model is formulated based on the data and the SVR parameters are optimized using a genetic algorithm. It can conclude that the resulting model has a coefficient of correlation metric of 99%. The simulated annealing algorithm is then applied to find the optimal values of inter‐cell and cell‐enclosure distances for minimization of inter‐cell temperature differences and the total volume of the cell. Optimization analysis concluded that the volume of the battery pack was decreased by 29%, temperature difference (K) by 42% and SD of the temperature over the entire pack decreased by 55%. [ABSTRACT FROM AUTHOR]

The utility of a single-point impedance-based technique to monitor the state-of-health of a pack of four 18650 lithium-ion cells wired in series (4S) was demonstrated in a previous publication. This work broadens the applicability of the single-point monitoring technique to identify temperature induced faults within 4S packs at 0 °C by two distinct discharge cut-off thresholds: individual cell cut-off and pack voltage cut-off. The results show how the single-point technique applied to a 4S pack can identify cell faults induced by low temperature degradation when plotted on a unique state-of-health map. Cell degradation is validated through an extensive incremental capacity technique to quantify capacity loss due to low temperature cycling and investigate the underpinnings of cell failure. [ABSTRACT FROM AUTHOR]