Browse Topic: Battery packs

Items (1,204)
Hybrid electric vehicles rely heavily on battery pack power capability, which is often compromised by non-uniform aging and thermal gradients. Conventional battery models typically use bulk state-of-health metrics, failing to capture localized degradation that leads to current imbalances and reduced pack utility. This paper presents a multi-scale modelling framework that integrates Electrochemical Impedance Spectroscopy data into a fractional-order equivalent circuit model to simulate localized degradation in Lithium Iron Phosphate cells. Results show that the terminal voltage of LFP cells can be accurately modelled using the proposed fractional-order equivalent circuit with a discrete transfer-function implementation, maintaining root-mean-square errors below 20 mV across most state-of-health and state-of-charge conditions. The validated cell model is then extended to a degradation-aware battery pack representation. The battery pack in this work utilizes a 200-kWh, 800 V architecture consisting of five modules connected in parallel, each module composed of 13 parallel strings of 250 series cells, evaluated under multiple degradation scenarios. By integrating this pack model into a Class-8 series hybrid powertrain simulation, this study quantifies how cell-to-cell heterogeneity impacts vehicle performance under the VECTO regional delivery drive cycle. At the vehicle level, these battery constraints influence engine duty cycles and battery pack stress metrics. When localized degradation reaches up to 40% in one module while the remaining modules degrade up to 20% to 30%, such inhomogeneous degradation reduces the minimum pack terminal voltage by approximately 27% and increases peak discharge current by more than 30%, resulting in more rapid degradation. These battery-level limitations translate into higher fuel consumption by up to 6% in a charge-sustaining scenario.
Safavi, Seyed RezaHomayouni, HoomanShoa, TinaWang, JasonMcTaggart-Cowan, Gordon
Current lithium-ion batteries should generally only be charged above 0 °C, as charging below this temperature can promote lithium plating and irreversible degradation. However, conventional pack-level heating elements increase system mass and design complexity. In addition, heat is transferred from outside into the cell, causing the temperature inside the cell to rise slowly. This study evaluates internal Joule heating of cylindrical Li-ion cells using a zero-mean square-wave current excitation and quantifies the associated aging impact. LG INR21700-M50L cells were tested at 0 °C, −10 °C, and −20 °C with three excitation frequencies (50 Hz, 1 Hz, 10 mHz) at 5 A amplitude. Each cycle consisted of 30 min heating followed by 60 min cooling; reference capacity-based state of health (SOH) was assessed every 50 cycles up to 400 cycles. A maximum surface temperature rise of 14.3 K was achieved, with larger temperature rise at lower ambient temperature and lower excitation frequency. Capacity fade remained below approximately 1% for most conditions; however, at −20 °C and 10 mHz a pronounced SOH decrease to 87% was observed, indicating a critical operating regime. The results provide practical guidance for pulse-heating parameter selection and highlight the need for safeguards and further diagnostics in extreme low-frequency excitation at very low temperatures. This heating approach is particularly suitable for simpler battery-electric applications without thermal management, such as e-bikes or power tools. However, it may also be relevant for applications with existing thermal management systems, as it simplifies battery pack design.
Raiber, StefanAllmendinger, FrankDegler, DavidParschau, Anke
With the continued expansion of electric mobility, liquid-cooled thermal management systems have become indispensable for ensuring the performance, durability, and safety of automotive battery packs. This work presents a novel cooling-plate design that integrates offset strip-fin turbulators to enhance convective heat transfer between lithium-ion cells and the circulating coolant. A comprehensive multi-region CFD model of the full battery pack is developed, incorporating an implicit lumped-parameter representation of cell heat generation. The numerical predictions are validated against dedicated experimental measurements available in the literature. Subsequently, a parametric study is conducted in which the number of hydraulic sub-modules and the inlet/outlet configurations are systematically varied to generate all feasible design permutations. The resulting configurations are compared to assess thermal performance and to quantify the benefits—as well as the potential penalties—introduced by the turbulators relative to the experimentally validated baseline.
Montenegro, GianlucaOnorati, AngeloDella Torre, AugustoTariq, Muhammad HasnainBonetti, Elisa
This paper presents Stochastic Gradient Pulse Adaptation (SGPA), a real-time adaptive pulse-charging system for rechargeable electrochemical batteries that dynamically adjusts charging aggressiveness based on the battery's internal response, as opposed to predetermined CC–CV or fixed pulse profiles. SGPA is different from traditional charging methods that use static current de-rating and conservative voltage limits. Instead, SGPA uses gradient-based feedback from terminal voltage behaviour, temperature changes, internal resistance changes, and state of charge to continuously adapt pulse amplitude and duty cycle. This algorithm boosts the charging intensity when the electrochemical circumstances are good. It lowers the pulses slowly when signs of thermal or impedance-related stress show up. Simulation-based proof-of-concept experiments on a heavy-duty multi-battery system show that charging time is less than with multi-CCCV charging, while still keeping the current distribution across packs balanced. The suggested SGPA method adds an adaptive charging algorithm that is easy to understand and ready to use. It makes fast charging more efficient without lowering voltage and thermal safety limits.
Prakashkumar, BalagopalMannar, Vignesh
This document provides recommendations involving BEV battery data retention and battery design that enhance the potential for BEV battery reuse and serviceability and that can improve recyclability. These recommendations have been developed by a group of professionals skilled in the secondary-use of batteries and in the research, development, and manufacture of BEV batteries and battery systems.
Secondary Battery Use Committee
Tire exterior noise has become increasingly critical in vehicle acoustics due to two key developments: updated pass-by noise regulations, which amplify the relative contribution of tire noise, and the rise of Battery Electric Vehicles (BEVs), which lack traditional powertrain noise. Design trends in BEVs—such as increased vehicle mass from battery packs and the widespread use of large-diameter, wide, low-profile tires—further intensify tire noise due to stiffer constructions and altered contact dynamics. A common method for predicting tire noise is the source-transfer-receiver model, where the tire is represented by a set of monopoles with volume velocity Q derived from near-field measurements. Acoustic propagation is modeled via p/Q transfer functions. Despite its simplifications, this approach is practical for vehicle development, enabling clear separation between source and transfer mechanisms and facilitating targeted noise control strategies. In previous work, we proposed a rigorous framework to optimize both the spatial distribution and strength of the monopole sources. Positions were identified using an L1-norm regularization via the Lasso algorithm, promoting sparsity and physical interpretability. Strengths were estimated using an L2-norm Tikhonov regularization, which stabilizes the solution against measurement noise. While the Tikhonov regularization parameter was previously tuned manually through trial and error, we now enhance predictive accuracy by selecting it via a cross-validation technique, ensuring a more robust and data-driven optimization. Besides this, compared to the previous work the approach here is validated for the prediction of both indoor and outdoor pass-by noise, as well as for multiple tire types providing different noise levels. Results demonstrate the method’s robustness, accuracy, and applicability for acoustic development in modern vehicle platforms.
Morin, BenjaminDi Marco, FedericoHorak, JanLafont, ThibaultKim, MinkyuKang, Min KyooYoo, Ji Woo
This paper presents a novel concept for battery electric vehicles (BEVs), referred to as the low-voltage reconfigurable electric vehicle (LVREV). The LVREV is designed to bridge the gap between L- and M-class vehicles by adopting a <60 V multi-phase powertrain combined with a swappable battery system, maintaining the overall vehicle mass below one ton. This configuration enables adaptable driving range, optimized energy consumption in urban environments, and enhanced safety. The LVREV features two distinct operating modes. Frugal mode is intended for urban use and employs a smaller battery pack to maximize efficiency and reduce vehicle mass, while Dual mode is tailored for longer extra-urban trips through the use of a dual-battery configuration. The key innovations of the LVREV concept include a reconfigurable vehicle architecture capable of meeting both urban and extra-urban mobility requirements, thus providing a highly versatile transportation solution. In addition, the low-voltage powertrain improves safety and lowers system costs, facilitating manual battery replacement and compatibility with domestic charging infrastructure. By integrating these technological solutions, the LVREV expands the potential of low-voltage electric vehicles and supports the development of more flexible, efficient, and user-oriented mobility concepts. Experimental and simulation results demonstrate the feasibility of the proposed solution and provide initial validation of the reconfigurable powertrain and battery architecture.
Tramacere, EugenioFavelli, StefanoGalluzzi, RenatoTonoli, Andrea
With new energy vehicles developing rapidly, battery safety, as an important part of the impact on the range of new energy vehicles and vehicle safety, has become the focus of attention. The battery pack protection plate is a core component to protect the battery, its performance needs not only impact resistance, but also lightweight, honeycomb sandwich structure with its excellent energy absorption characteristics and weight reduction performance by the battery pack protection plate performance research. At present, the core-to-face sheet interaction in conventional sandwich structures subjected to impact loads has not been fully elucidated, and the quantitative characterization of damage is insufficient, so this paper aims to optimize the lightweight impact-resistant structure by exploring the synergistic energy dissipation mechanism between the high-strength core material and the steel plate. The study combines theory and simulation, adopting ideal rigid-plastic film theory to establish a critical response model to predict the structural failure threshold, equivalent single-layer theory to simplify the analysis of plywood, and a stiffness matrix model to quantify the structural mechanical contribution of each layer. A two-material synergistic design framework is proposed by fully considering the material properties and adopting the corresponding intrinsic structure and failure criteria for different materials. Analysis reveals that geometric confinement is a key characteristic of the honeycomb sandwich panel’s response and a strain gradient driving mechanism at low impact resistance, and a new energy distribution paradigm is found through the analysis of the energy absorption ratio. The theoretical and simulation results are in great agreement with each other, which just has a difference of 0.7% in the peak force, 1.4% in the critical displacement error, and less than 2% in the impulse integration error. The proposed dual-material co-design framework provides a solution for electric vehicle battery protection systems that balances lightweight and impact resistance.
Zhang, GuanghaoZhang, MingmingLuo, ChangjieZhou, JunZhang, FengqiangYu, WenzeLi, JiongfengGuo, Qingrong
To enhance the safety and efficiency of power batteries for new energy vehicles, a high-fidelity thermal management simulation model for lithium-ion batteries was established using a multi-scale coupled approach encompassing "cell-module-pack" levels. Charge/discharge experiments within the 15–45°C temperature range and under various State of Charge (SOC) conditions were conducted to obtain cell characteristic parameters. A second-order RC equivalent circuit model was constructed and validated. A three-dimensional thermal model of the battery pack was developed using the NX and STAR-CCM+software platforms and validated through high/low-temperature humidity tests. Results indicate that simulation errors for battery pack temperature and cooling line pressure were both below 3%. The model accurately simulates thermal behavior from microscopic cell characteristics to macroscopic battery pack dynamics.
Luo, ZhaoyangSong, Lan
A full lithium-ion battery (LIB) pack has hundreds to thousands of cells, coolant flow lines and channels, and channel bends to control cell temperature within its operating window and minimize cell internal resistance, aging, and fire risk. A 75 kWh LIB pack has four modules, and each has 23–25 bricks. Two challenges in battery state predictions for hot and subzero temperatures are battery temperature (Tbatt ) and coolant flow within the whole pack. In this work, a 1D 75 kWh full-pack model with its thermal management system is developed using a holistic reverse-engineering method, which can predict Tbatt at any bricks/modules and inlet/outlet coolant flow characteristics. A Tesla Model Y equipped with dual e-motors is tested on an in-house state-of-the-art chassis dynamometer. The test data at V = 60–80 km/h, 100–150 A constant discharge, and Tbatt = −10°C to 40°C are used to develop the model. The 75 kWh pack model features 4000+ cylindrical cells (96S46P, Panasonic 21700-format), 20+ coolant lines (or plates, tubes), and 700+ flow channels. The model considers heat exchange from cells to the ambient air via coolant (water-glycol), coolant channel walls, adhesive bonding, trays, and cases. Four forced convective heat transfer coefficient correlations (α) from the coolant to the walls are used to predict coolant outlet temperature (T cool, out ) and Tbatt at different bricks. Three coolant flow losses correlations (K) due to pipe friction, and pipe bends are used to predict the coolant pressure drop ∆Pcool across the pack. Optimal α and K correlations are identified using the fully validated pack model, and the transient temperatures at any cell in bricks and the inlet/outlet coolant flow characteristics are well predicted with over 90% accuracy. This work provides guidelines for selecting optimal α and K correlations to develop any 1D fully liquid-based battery pack models for all-weather driving.
Sok, RatnakKusaka, Jin
The current work presents a methodology to estimate the mission and performance capabilities of a generic rotorcraft configuration, to satisfy the need of evaluating the integration of a full electric powertrain in the aircraft design. To include all the design steps, two different approaches are proposed. For the preliminary phase, the "Analytic Method" is considered, which exploits a purely resistive model. Conversely, a method based on look-up tables called "Table Method" is intended to be used in more advanced phase, when the battery pack is defined. Both approaches are tested by evaluating a reference mission and a hover chart. Finally, a verification of the presented methodology is carried out by comparing the mission results with a commercial software, specialized in the evaluation of the cell discharge when a given power spectrum is provided.
D'Agosto, StefanoNesci, AndreaRovera, EugenioPirrello, RiccardoPace, ChiaraBaldi, Francesco MariaPassarelli D'Onofrio, Anna Sofia
Electric Vertical Take-Off and Landing (eVTOL) aircraft are poised to transform urban and regional mobility by offering zero-emission, congestion-free transportation. As regulatory frameworks evolve and advanced air mobility (AAM) gains traction, manufacturers are exploring propulsion strategies that improve range, power delivery, and overall system efficiency. A key challenge in eVTOL development is balancing range with payload capacity. While larger battery packs can extend range, they also increase system weight, reduce payload, and prolong charging times, limiting operational flexibility and turnaround time. Hydrogen fuel cells, supported by liquid hydrogen (LH₂) present a promising alternative for eVTOL propulsion. This study proposes a methodology for optimizing fuel cell propulsion systems tailored to eVTOL applications. A multi-physics modeling framework for eVTOL flight dynamics and propulsion system was developed, representing the target eVTOL configuration. For a defined flight path including vertical takeoff, hover, cruise, and landing, a Genetic Algorithm (GA) based optimization was conducted on propulsion system. The algorithm down-selected battery size, fuel cell stack specifications, and hydrogen tank capacity to meet mission requirements while minimizing propulsion system weight. The modeling framework was also used to evaluate trade-offs between payload and performance as functions of component sizing, battery chemistry and energy distribution strategy.
Garcia, BrunoPaul, SumitZeigler, SophiaFranke, MichaelJoshi, SatyumAraujo, Joao
This paper demonstrates the sizing and optimization of a hybrid-electric multi-tilt rotor configuration of both conventional and vertical takeoff and landing capabilities. The study uses Parametric Energy-Based Aircraft Configuration Evaluator to design and optimize the aircraft. To explore the design space comprising both discrete and continuous design variables, a genetic algorithm is used for optimization. The design variables are not limited to conventional aero-propulsive parameters such as wing loading, aspect ratio, and disk loading. Battery-related parameters such as the maximum permissible depth of discharge, maximum permissible discharge rate, and the number of parallel strings in a battery pack are also considered in this work to study their impact on aircraft gross weight and fuel consumption. The Non-dominated Sorting Genetic Algorithm-II (NSGA-II) optimization framework is used to solve the multi-objective optimization problem, with objectives to minimize the maximum take-off mass and fuel weight. The sensitivity studies showed that higher wing-loading and lower-aspect-ratio designs resulted in lower gross weight. A higher permissible depth of discharge led to lower fuel consumption, despite a slight increase in gross weight. But increasing the number of parallel strings in a battery pack increased gross weight with negligible change in fuel consumption.
Bhandari, RajanChakraborty, Imon
The present work focuses on the sizing and analysis of a parallel hybrid propulsion architecture for a conventional rotary light Unmanned Aerial Vehicle (UAV) in the 200kg class. First, the design methodology is outlined, with an emphasis on the optimization of the battery pack, which is one of the most crucial component of the whole powertrain. The sizing approach is applied to a wide range of thermal and electric power ratios, as well as two distinct hybridization strategies, to investigate the broad design space and discover possible sweet spots. For this aim, the various design points are then evaluated in terms of impact on aircraft capabilities, considering both extensive and intensive performance. Hence, the results provide the main advantages and disadvantages, performance wise, of the hybrid propulsion in comparison to a conventional full thermal solution.
Rovera, EugenioCorno, MatteoTrivella, AndreaBonini, ValerioNesci, Andrea
From material selection to system-level performance Transportation's shift toward electric power - whether cars, planes, or big trucks - has made battery engineering a pretty wild, multidisciplinary puzzle. It's not just about coming up with a prototype anymore. To hit the right mix of energy density, power, safety, cost, and longevity, teams need to rethink how they design these systems. Enter simulation and modeling tools. Engineers now use these digital tools to blend electrochemistry, thermal management, materials science, and whole-system design. Instead of jumping straight to building, they try out battery ideas in the virtual world first, speeding up how long it takes to figure out what works and what doesn't and boosting the reliability of those batteries in the real world. Today, battery simulation spans multiple scales from the behavior of active materials within electrodes to the thermal dynamics of the entire battery pack as integrated into a vehicle.
Gupta, Pradyumna (Prady)
In a traditional electric vehicle, managing its battery thermal performance is of prime importance. A well-designed battery thermal management system helps in extending its life and avoids safety-related issues like thermal runaways. A critical part of this thermal management is the battery cooling system (BCS), which can be air- or liquid-cooled. Based on the vehicle battery pack size, location, and its design complexity, the original equipment manufacturer can opt for either of the previous two methods. An air-cooled type of BCS system usually involves an active ventilation fan to dissipate the battery heat in the surroundings, which brings symbiotic noise into the picture. In an air-cooled BCS system, the primary source of noise is the cooling airflow over the heat exchanger caused by the fan. The airflow and noise performance characteristics of this fan are typically measured by the supplier in a standalone condition. These performance parameters deviate greatly when the fan is introduced inside a battery cooling module. In the current work, flow-induced noise simulation of a fan placed inside a confined BCS is performed. The simulation has made use of a statistically based tool due to its inherent low dissipative and dispersion properties. The simulation model included all complex interior parts of the BCS, including the mating gaps higher than 1 mm. The simulation results were correlated with the test, and further iterations were performed in simulations to understand the sensitivity of the condenser core location with respect to the fan. Additionally, the changes in noise performance behavior while moving from a standalone fan toward a fan integrated with the BCS system are also studied. The overall noise correlation between the simulation and test is achieved within a 0.4 dBA level. Further, the presence of flow-induced resonance inside the BCS at a lower frequency than the BPF was identified in simulation.
Nomani, MustafaDupatti, DarshanNikam, KrishnaSasikumar, R.Kajagar, SureshPanchare, DattajiAgalawe, Kiran
With the increasing adoption of electric vehicles (EVs) worldwide, ensuring the long-term reliability and performance of the battery systems has become a paramount engineering challenge. Lithium-ion cells exhibit dimensional changes throughout their operational life, characterized by reversible “breathing”—expansion and contraction during charge and discharge cycles—and irreversible swelling due to aging. Compression pads are critical components for ensuring the lifetime performance of battery packs. The primary function of a compression pad is to act as a compliant cushion between cells. It accommodates these volumetric fluctuations by exerting consistent and optimized pressure. By absorbing the stress from cell expansion and maintaining structural integrity within the module, compression pads mitigate degradation mechanisms and ultimately maximize the durability and safety of the battery system over thousands of cycles. This paper highlights the importance of tailoring elastomeric-foam-based compression pads to meet the unique challenges of various battery formats and chemistries. We first characterize the fundamental mechanical properties of these pads under a range of conditions, such as different compression speeds and temperatures, that are directly relevant to realistic battery applications. Additionally, we demonstrate the pad’s long-term mechanical resilience by evaluating their performance over thousands of charge-discharge cycles at different operating temperatures, confirming their ability to maintain consistent pressure over a long time. Finally, we present advanced modeling and simulation approaches for compression pads. These predictive models are crucial tools to accurately forecast mechanical behavior and explore the design space virtually, accelerating the development of optimized solutions of compression pad for battery pack applications.
Deng, WeilinGunashekar, Subhashini
The performance of a full battery pack with its effective thermal management system (BTMS) depends on coolant flow and heat transfer characteristics inside the pack. To develop a full BTMS using model-based design (MBD), the model must capture the coolant pressure drop ∆?? and heat-exchange performance from the cell to ambient air via the coolant, cooling flow channels, air gaps, and pack cases. Predicting battery pack responses (i.e., voltage, SOC, temperature) under all weather conditions is a challenge, as a complete pack contains several hundred to thousands of cells, coolant lines, coolant line bends, and coolant channels. This work presents a detailed approach to identifying heat transfer and ∆P correlations that can capture the real-time thermal-electrical performance of a mass-produced LIB pack under constant speed (in winter) and transient driving (in summer). A vehicle test is conducted using a Tesla Model Y, 2-motor model equipped with a 75-kWh LIB pack. The LIB pack's thermal and electrical performance is recorded at 60 km/h under cold conditions and during transient driving in summer. The pack is based on the 2RC equivalent circuit model, reduced from the P2D-based NCA/Gr-SiOx Li-ion cell, to accelerate simulation times at the pack and vehicle levels. The approach to identifying ∆P and heat transfer correlations are discussed, with pack model validations under coolant temperatures ranging from 0 to 40 °C and coolant flow rates of 4 to 14 L/min. The thermal and electrical performances (voltage, SOC, ∆P, and temperatures of the coolant, bricks, and modules) of the high-fidelity battery pack model are validated against vehicle test data at 60 km/h driving (ambient temperature Ta = -10 °C) and repeated FTP+HWFET cycle (Ta = 30°C). The whole pack model achieves an average accuracy of 90%, and this work can serve as a guideline for designing battery packs with their BTMS using MBD.
Sok, RatnakKusaka, Jin
The global transition towards sustainable transportation is driving the development of efficient, low-emission propulsion systems. Battery-electric solutions are effective in urban contexts, but face limitations in heavy-duty and long-haul applications due to the size and weight of the required energy storage. Hybrid battery/fuel cell powertrains offer a promising alternative for such use cases, reducing vehicle mass and charging times while maintaining high energy efficiency. This study presents an original zero-dimensional MATLAB/Simulink model, named HyPoST (Hydrogen Powertrain Simulation Tool), for a parallel hybrid fuel cell/battery system, here applied to heavy-duty vehicles. The model encompasses the main vehicle sub-systems, including the fuel cell stack with auxiliaries, battery pack, electric drive, transmission and the vehicle longitudinal dynamics, coordinated through a rule-based energy management strategy. Two representative heavy-duty vehicle configurations were analysed: a Group 5 long-haul truck, and a Group 2 urban delivery vehicle. A model-to-model validation strategy was performed using VECTO as a reference, the reference European Union’s tool for estimating energy consumption in heavy-duty vehicles. A graphical user interface (GUI) enables users to modify vehicle parameters and run customized simulations, and the model is made available to the scientific community in open and editable version upon request to the authors. The results demonstrate that HyPoST accurately reproduces heavy-duty vehicle behaviour for both truck models, as revealed by the analysis of gear selection, electric motor, and battery telemetries, providing a scalable and accessible tool for engineers, researchers and students.
Montecchi, GianlucaMartoccia, LorenzoD'Adamo, Alessandro
Battery thermal runaway is a major safety concern in electric vehicles because of the extreme heat and hazardous gases released during cell failure. These venting events can quickly raise the temperature of the battery enclosure and cabin floor, threatening occupant safety. To address this challenge, this study employs the Design for Six Sigma (DFSS) methodology to design and optimize a thermal protection system that delays and limits heat transfer to the cabin. A physics-based transient heat-transfer model was combined with DFSS principles to systematically evaluate insulation materials, shield layouts, surface emissivity, and layer geometry. An L-18 orthogonal array was used to identify key parameters and quantify their influence on thermal robustness. The optimized architecture reduced cabin-floor temperature rise under severe runaway conditions (600–900 °C vent gas), meeting occupant-egress safety requirements. Findings confirm DFSS as an effective framework for developing high-robustness EV thermal protection systems under uncertainty and extreme boundary conditions.
El-Sharkawy, AlaaAsar, MonaTaha, NahlaSheta, Mai
With the rapid advancement of electric vehicle (EV) fast charging technology, battery thermal management faces increasingly critical challenges due to elevated heat generation and stringent safety requirements. Conventional indirect cooling methods often struggle to provide sufficient heat removal under fast charging conditions, leading to potential safety risks. Immersion cooling has emerged as a promising solution because of its superior heat dissipation capability and uniform temperature distribution. In this study, an electrochemical-thermal coupled simulation framework is developed to evaluate indirect and immersion cooling performance under high-power charging conditions. A Pseudo-two-dimensional (P2D) electrochemical EV battery model is developed in GT-SUITE and validated against vehicle charging data. An immersion cooling system is also modeled and integrated into the battery framework to allow comparison with a conventional indirect cooling system under high-power DC fast charging scenarios. Simulation results indicate that immersion cooling achieves a maximum module temperature of 37.5 °C under 250 kW fast charge, which is 4 °C lower than the indirect cooling system. Furthermore, the immersion-cooled pouch cell battery pack can be charged from 10% to 80% SoC within 22 min, 11 min faster than using the indirect cooling system with a temperature limit of 42 °C. These findings demonstrate the potential of immersion cooling to enhance thermal safety, improve charging efficiency, and extend battery life in next-generation EVs.
Guo, YuyangRockstroh, TobyOezdag, ErdalHaenel, PatrickBodemann, BasilToghyani, Somayeh
The high voltage battery junction box (HVJB) controls and protects the high voltage connections of the battery pack to the traction, auxiliary, and charging systems. HVJBs are composed of busbars, contactors, fuses, and other protection systems. The health of the HVJB is paramount to ensure performance of electric vehicles. However, sensing and monitoring in the HVJB are often lacking due to packaging cost, causing limited capability of the vehicle controller to estimate the status and health of the unit. This publication focuses on the experimentation of an automotive HVJB to characterize the operation and build the foundation for the development of prognostic algorithms for HVJB. A production HVJB has been acquired and heavily instrumented. Extensive testings are performed in adiabatic and in ambient conditions at various current levels for various durations of operation. The testing setup was calibrated and iterated based on preliminary results, and the testing conditions were adjusted to increase the accuracy of the data. These results were analyzed to identify patterns in the behavior of the heat generation for each individual component and the heat exchange between them. The analysis of these results allows for the calibration of an electrothermal model of the HVJB using MATLAB Simulink. Upon finalizing model calibration, the model will be able to accurately predict the electrothermal behavior of the HVJB, allowing for critical feedback data that can be used by production engineers to assist in reducing overall pack failures.
Arigo, SamBorgerson, JoeD'Arpino, MatildeZhu, DiZhang, Liwen
The battery is a critical component of electric vehicles (EVs), where high power demands pose significant operational challenges. One such challenge is gas generation within the porous anode layer, which can lead to pressure buildup inside the battery. The complex interfacial dynamics at the microscale play a crucial role in determining the effectiveness of gas venting and the resulting pressure evolution. This study examines the effect of gas generation at two different length scales on the pressure rise and bubble dynamics. First, gas generation within a representative anode microstructure sample is investigated using a Volume of Fluid (VOF) framework that resolves tortuous flow passages. The simulations reveal that gas generation in such microstructures can lead to pressure rises of several thousand Pascals, with interfacial behavior primarily governed by surface tension effects. Second, a high-level single-cell simulation is performed using a porous media approach to evaluate system-scale gas venting and localized pressurization. This multiscale modeling framework provides key insights into the relationship between microscale gas dynamics and overall gas accumulations in the cell.
Mahyawansi, Pratik J.Schlautman, JeffViswanath, PriyankaSrinivasan, Chiranth
Electric Vehicles (EV) have become a major focus in the automotive industry. This paper introduces a propulsion system design, which supports the Wide Torque Band (WTB) concept to boost the power density of PM (permanent magnet) motors in EV Trucks resulting in performance, efficiency, and cost benefits. A selectable 400V/800V battery system has been developed to support the WTB concept and enhance the power density of permanent-magnet motors in electric vehicles. The RESS comprises two 400V battery packs that can be charged at 400V in parallel or at 800V in series via a DC fast-charging (DCFC) connection. In this study, an 800V driving mode was additionally implemented. A prototype battery management system (BMS) along with existing production voltage, current and temperature measurement block hardware are applied to perform mode switching, safety, and cell balancing. The success of this dual pack hardware enables high voltage dynamometer testing of a new 800V DU (Drive Unit) and inverters for EVs. The flexibility of switching between two voltage levels (400/800V) from the battery packs enables testing of both current 400V and future 800V drive systems in the same test cell. The control concepts developed for managing the dual packs were applied to convert a truck to operate at 800V using the native 24-module battery with modifications. Vehicle tests validated the BMS with this new feature.
Zhu, YongjieLee, ChunhaoGopalakrishnan, SureshNamuduri, Chandra
Battery modules consist of battery cells electrically joined at the terminals by conductive busbars. Laser welds are the most consistent and controllable process to create these connections on a large scale due to their control over power, laser width, speed, wobble, and overlap, and their quality is critical to battery pack performance. Tuning these parameters for an application typically requires weld trials to reach desired weld width, penetration, and strength without overheating the battery cell and weakening the dielectric insulators around the terminals. Poorly welded cells in a module can result in increased electrical resistance, causing greater joule heating and accelerated cell aging, and poorly welded modules can lead to uneven aging and unpredictable performance. To better understand the laser welding process, a modelling approach was developed to predict weld properties to reduce production time, costs, and potential cell damage. The 3D finite element model was calibrated using test data gathered using 1 mm thick aluminum busbars being welded onto 25 mm aluminum terminals with varying laser parameters. A volumetric gaussian heat source was used to characterize the modelled laser. Melting and vaporization in the weld were captured without explicitly modelling them by adjusting the model’s material properties to improve computational efficiency. Each simulation’s predicted melt pool cross section was compared to that of each corresponding weld trial. This modeling approach led to the development of a parametric tool that could quickly predict laser melt pool width and depth which can be used to accelerate laser weld process development.
Contreras, LuisHoffmeyer, MatthewAbidin, Zainal
Increased use of Electrical vehicles (EVs) brings in unique structural design challenges particularly in Side Impact scenarios when the battery pack positioned near the sill region elevates the possibility of battery penetration and thermal runway in crash event. Thus, Electric Vehicles require unique structural design solutions. This study focuses on a novel steel tube-in-tube Side Sill reinforcement design and its performance benefits over a traditional aluminum Side Sill reinforcement commonly used for battery protection in EV vehicles body components. The proposed Steel Side Sill design layout mainly focuses on structural rigidity and improved load transfer during side pole impact crash cases and addressing manufacturing complexity and cost reduction opportunity. Multiple Steel Side Sill reinforcement design iterations are carried out by finite element analysis with software like LSDYNA Hyper works [1]. The goal was to develop an optimal tubular design - maximizing load transfer and energy absorption. The study was mainly divided into two stages, 1) CAE Full Vehicle and Component; 2) Component Test Validation. Initial design parameters were derived based on full vehicle and component CAE and then the design was validated using physical testing. The results show that the tube- in-tube Side Sill reinforcement structure has similar performance compared to base Aluminum design and indicated possibility of reduced manufacturing complexity, cost and mass saving options. These findings proved that the proposed novel Side Sill reinforcement in EV specific body in white (BIW) is helpful to design safer vehicles and effectively meet both regulatory and consumer matrix.
Kusnoorkar, HarshaKhutorsky, AlexPenumetsa, VivekKoraddi, Basavaraj
This paper presents a simplified approach to model thermal runaway propagation in a multi-cell battery pack, with the goal of designing a safe and lightweight pack for mass-sensitive applications. The key parameters which characterize single-cell thermal runaway, including heat release profile, apparent cell emissivity and mass loss, were extracted from empirical nail penetration tests. This characterization was used to drive a three-dimensional thermal model of a 19-cell hexagonal sub-pack with a center trigger cell. To enable rapid design exploration, a symmetry-based computationally simplified domain was used for a full-factorial Design of Experiments (DOE) varying cell spacing, epoxy thickness, heat spreader thickness, and cup geometry. The DOE results were used to identify dominant heat-transfer mechanisms, capture main and interaction effects, and determine mass-efficient design levers governing peak-neighbor cell temperature during propagation. Insights from the DOE study informed the design of a physical prototype and the placement of thermocouples for model validation. Measured temperature data showed good agreement with model predictions across multiple initiator locations, with 4–7 °C error in peak temperature and 3–5 s error in time to reach peak temperature. However, accurate reproduction of the observed trends required increasing epoxy thermal conductivity on the initiator cell to represent epoxy carbonization observed during post-test teardown. This simplified modeling approach, paired with targeted testing, can provide practical design guidance, reduce overall testing cost, and enable fast development of mass-optimized, propagation-resistant battery packs.
Kalyankar, ApoorvOwen, ElliotStrohmaier, KyleMardall, Joseph
Thermal runaway in high-voltage lithium-ion battery modules should focus on critical safety and design challenges in electric vehicle applications, which need predictive methods that enhance passenger safety and support regulatory compliance. The primary purpose of a lithium-ion battery in an electric vehicle is to provide reliable energy storage while maintaining safe operation under different operating conditions. This study proposes a Design for Six Sigma (DFSS) methodology to virtually predict and correlate thermal runaway and its propagation in an 800V high-power lithium-ion battery pack module. Conventional propagation analysis relies heavily on physical testing, whereas the DFSS-based virtual framework enables cost-effective evaluation at early design stages. Input factors included are heat transfer pathways, which are sensitive to the temperature changes, as well as thermal propagation time. Control factors are the design or process parameters that engineers use to establish the functional performance of a system. The noise factors capture material variability and manufacturing tolerances affecting thermal properties. Output responses included the maximum cell temperature Versus time, thermal propagation time to adjacent cells, and total propagation duration across the module, measured in minutes. The validated 1D GT-SUITE model shows strong correlation with experimental data, confirming its reliability to predict thermal propagation time and supporting safer, thermally optimized battery pack designs. The validated model can be integrated into system (battery pack) level 1D thermal simulations, offering a calibrated model for future pack level propagation studies and supporting the development of safer, thermally optimized battery architectures.
Dixit, ManishRaja, VinayakGudiyella, Soumya
Battery fires pose a significant risk across a wide range of applications, including electric vehicles, consumer electronics, and grid-scale energy storage systems. Early detection of fire and smoke is critical to preventing catastrophic failures and ensuring human safety. In this study, we developed a synthetic dataset of battery fire and smoke images in the context of a simple battery pack. The primary application of this dataset is to support the development of a machine learning–based visual classification system capable of accurately detecting battery fires and smoke in real time at an early stage. The intended outcome is a deployable classification system that enhances battery safety through rapid visual identification of hazardous conditions.
Govilesh, VidarshanaGunasekaran, AswinChalla, KarthikeyaMaxim, BruceShen, Jie
Improving the energy efficiency of electrified vehicles remains a central objective in modern electric powertrains. Multi-level converters (MLCs) are widely recognised for lowering conversion losses relative to two-level inverters and improving total harmonic distortion (THD) in the sinusoidal supply to motors with a consequent reduction in motor losses. Despite this, sustained production-oriented validation at the integrated system level remains limited. This work introduces a multi-level converter architecture of the Battery Integrated Modular Multi-Level Converter (BIMMC) topology using Cascaded H-Bridge (CHB) architecture. It offers improvements in all key metrics of performance, cost, package size, mass and robustness compared to the current state-of-the-art two-level inverter system with distributed functions for charging available in the market today. The overall solution is highly functionally integrated. It supports four major functions required in electric vehicles without the need for additional hardware. Firstly, supply to and control of a three-phase electric motor without the need for a separate, standalone inverter. Secondly, all usual battery management system (BMS) functionality including energy and State of Charge (SOC) management to module level enabling usable energy and robustness improvements. Thirdly, the ability to charge from both alternating current (AC) (single phase and three-phase) and direct current (DC) sources without the need for separate on-board charger (OBC) hardware whilst also enabling an innovative pulse charging approach which benefits both charging time and battery ageing compared to conventional DC charging. Finally, the ability to deliver a controlled DC supply to non-traction loads on the vehicle with high efficiency and redundancy. The BIMMC topology proposed has been designed, built at prototype level and tested in order to collect performance data to empirically validate empirical study of the performance and functional benefits of the approach for traction motor drive, battery stored energy management and charging. Measured results demonstrate that improved inverter waveform quality correlates with lower motor harmonic losses and measurable drive-cycle efficiency gains, consistent with prior MLC assessments. Battery SOC depletion can be managed actively within the complete battery yielding increased usable energy and further driving range gains. Pulse charging shortens charge time whilst maintaining battery health metrics within acceptable limits, aligning with experimental evidence on pulse-based fast charging. The topology has also demonstrated the ability to pulse charge cells in a complete battery pack whilst consuming incoming DC supply current from a standard commercially available DC charger (Electric Vehicle Supply Equipment - EVSE). This potential to offer the benefits associated with pulse charging without requiring change to existing deployed charging infrastructure. Overall, proposed CHB-BIMMC architecture offers a practical blueprint for next-generation electric vehicles (EVs), and is compatible with ongoing integration trends that converge traction, charging and battery management functions within a unified power electronics and control platform.
Bao, RanKalaiselvan, PrashanthRener, KristofHallam, PhilipShi PhD, KaiYue, WilliamMa, HeGrimshaw, AndrewPatel, Simon
Battery thermal management is crucial for ensuring the safety, efficiency, and longevity of lithium-ion battery packs, particularly in electric vehicles (EVs). The primary purpose of a lithium-ion battery in an electric vehicle is to store and provide electrical energy for vehicle propulsion while maintaining safety under different operating conditions. This work proposes a thermal correlation between 1D CFD simulation and experimental test data under passive environmental heat exchange conditions without active coolant flow of a battery pack comprising four modules. An environmental exchange test was conducted using a 50% state of charge (SOC) battery pack, which is stabilized at 25°C to assess passive heat dissipation, thermal soak behavior, temperature distribution, and potential thermal runaway risks. The simulation predictions correlate well within a 1.5°C range compared to test results using ambient temperature and flow inputs, which confirms the reliability of the modeling approach. The simulation work was carried out using the GT-SUITE software. This study improves battery thermal management strategies by enhancing predictive accuracy and optimizing simulation frameworks for real-world applications. It minimizes overheating risks in practical scenarios, such as prolonged exposure to high ambient temperatures.
Nayaka, Sateesh KumarDixit, ManishGudiyella, Soumya
Electric vehicle (EV) battery packs have undergone substantial advancements in recent years, driven by engineering design improvements, material innovations, and increasingly stringent regulatory enforcement. These developments have enabled battery packs to become more energy-dense, which is essential for extending driving range and improving overall vehicle performance. However, with increased energy density comes a higher severity of thermal events, such as thermal runaway, which continues to raise concerns regarding vehicle safety, reliability, and long-term durability. This review highlights the critical role that thermal insulation materials play in mitigating the impact of such thermal events within EV battery systems. It presents an overview of commonly used thermal insulation materials, emphasizing their chemical composition, thermal resistance, and mechanical integrity under extreme conditions such as high temperatures and physical stress. The ability of these materials to maintain performance during thermal abuse is essential for protecting both the battery and surrounding vehicle components. In addition to material properties, the review compares the methodology and performance metrics of common methods for evaluating flammability, including flame retardance test such as UL 94 and torch and grit flammability tests such as one described in UL 2596. These comparisons are crucial for identifying insulation materials that can withstand severe thermal conditions without compromising safety. Beyond flammability, high temperature, smoke, and other important considerations such as thermal properties, environmental durability, corrosion resistance, and dielectric strength will be discussed with examples. These factors contribute to the overall effectiveness and reliability of insulation materials in EV applications. By understanding and optimizing these properties, engineers can better design battery packs that are not only high-performing but also safe and durable under demanding operating conditions.
Ng, Sze-SzeDhyani, AbhishekGorin, CraigJeon, JunhoNuguri, SravyaRepollet Pedrosa, MiltonRylski, AdrianShete, AbhishekSteinbrecher, JacobThomas, Ryan
Non-uniform temperature distribution within lithium-ion battery cells is a critical challenge that accelerates degradation, compromises safety, and reduces pack-level performance in electric vehicles (EVs). This work focuses on modeling and minimizing these thermal gradients through the structured optimization of a liquid-based Battery Thermal Management System (BTMS). A one-dimensional transient thermal model is developed to capture the axial temperature differentials (ΔT) in a cylindrical cell under dynamic drive-cycle loading, incorporating detailed heat transfer from the cell interior through thermal interface materials (TIM) and an aluminum cooling plate to the coolant. Using a Design for Six Sigma (DFSS) approach with an L18 orthogonal array, key control factors—including coolant flow rate, inlet temperature, TIM properties, and plate geometry—are systematically analyzed to identify configurations that optimally balance low average temperature with minimal internal temperature variation. The results provide a data-driven framework for designing robust cooling systems that mitigate the risks of localized hotspots and thermal runaway, thereby enhancing the durability and safety of EV battery packs.
El-Sharkawy, AlaaAsar, MonaSerpento, StanSheta, Mai
Electric vehicles (EVs) face unique safety challenges under pole side impact conditions, largely due to the presence of floor-mounted battery packs. Existing regulatory test procedures, such as FMVSS 214, primarily address occupant injury using full-height cylindrical obstacles. These procedures were originally developed for internal combustion vehicles (ICVs). However, real-world roadside crashes frequently involve obstacles of varying heights, such as guardrails, curbs, and median bases. While these obstacles pose limited risk to the passenger compartment, they can intrude into the battery pack and trigger thermal runaway. This study investigates the influence of obstacle height on EV pole side impacts. Finite element simulations of a commercially available sedan were conducted against rigid obstacles of different heights. Results reveal a non-monotonic trend of battery intrusion governed by the interplay between rollover dynamics and structural stiffness. Theoretical analyses were conducted to clarify the underlying mechanisms. When the obstacle height falls below the window frame level, rollover effects become more significant. The longer roll moment arm allows part of the impact energy to be dissipated through vehicle roll motion, leading to a reduction in battery intrusion. However, as the obstacle height is further reduced into the threshold beam and battery side beam region, the supporting structural members are bypassed. The equivalent contact stiffness drops sharply, resulting in significant battery intrusion. The findings demonstrate that obstacle height governs EV battery safety through a competition between rollover energy dissipation and reduced contact stiffness. This work provides new insights for extending existing side impact tests to low-height obstacles and offers guidance for vehicle safety design.
Ma, ChenghaoXing, BobinZhou, QingXia, Yong
Achieving the stringent EPA CAFE 2032 standards for light-duty full-size trucks and sport-utility vehicles (SUVs) in North American poses significant challenges. While Battery Electric Vehicles (BEVs) offer a clear path to zero tailpipe emissions, their widespread adoption in this segment faces hurdles including range anxiety, payload/towing capabilities, and traditional truck/SUV use cases. This paper investigates a balanced approach, focusing on optimizing propulsion system design with appropriate hardware content, can effectively meet future fuel economy and emissions standards. This investigation examines advanced BEVs and hybrid electric vehicle architectures, including full hybrids (HEVs), and plug-in hybrids (PHEVs) tailored for full-size trucks and SUVs. Considerations include the optimal sizing of internal combustion engines, electric motors, and battery packs to deliver robust performance while maximizing energy efficiency. This paper analyzes the integration of technologies such as electrified transmissions, electric motor configurations, and battery size. Trade-offs between electric motor capabilities, battery pack sizing and emissions reduction across different hybridization levels are investigated. The AMESim Hybrid Optimization Tool (HOT) is used to evaluate multiple propulsion system configurations and drive cycles for energy efficiency. Vehicle selection was performed by evaluating the payload/towing capabilities, propulsion system architecture, and vehicle model year. Drive cycles were selected from truck standards and real-world driving scenarios. The objective is to demonstrate a balanced approach for electrification pathways that satisfy consumer preferences for capability and range, ensuring CAFE 2032 compliance through a diversified powertrain portfolio.
Babcock, DillonRobinette, Darrell
Accurate modeling of battery temperature rise during fast charging is challenging due to uncertainty around cell heat generation and the thermal characteristics of the materials and interfaces which make up the battery pack. High fidelity thermal models are critical to attaining the best battery pack design, since they enable a multitude of cooling and packaging approaches to be considered prior to building a prototype. In this study, a 3D finite element analysis (FEA) thermal model of a production fast charging battery module is created. A loss model is parameterized as input for the FEA model. A key part of the loss model is the entropic heating coefficient (EHC), which is the change of open circuit voltage with respect to temperature. The EHC is measured by waiting for the cell voltage to reach steady state at various temperatures in 5% and 10% state of charge intervals over its capacity. This is then corrected numerically by accounting for unwanted discharge or rebounds. The EHC is used to calculate reversible loss, and irreversible loss is calculated using terminal voltage measured from the cell. Thermal parameters of the pouch cell are estimated through experimental thermal gradients and comparisons to similar cells. An FEA model of the module, which utilizes edge cooling, is created based on physical measurements. The combined loss and FEA model was found to estimate peak temperature with an error of 3 °C or less for 0.5, 1, and 1.5 C charge rates and 8 °C for a multistep fast charge.
Thornton, JackKollmeyer, PhillipPanchal, SatyamGross, Oliver
Towing imposes substantial efficiency penalties on both battery-electric vehicles (BEVs) and internal combustion engine (ICE) vehicles, reducing range by 30-50%. This paper presents a proof-of-concept embedded control architecture for distributed trailer propulsion that actively regulates drawbar force to reduce towing loads. Unlike proprietary e-trailer systems requiring specialized hardware, the proposed implementation demonstrates feasibility using commercial off-the-shelf (COTS) components and open-source software. The distributed architecture employs dual Raspberry Pi 4B single-board computers communicating via ROS 2 at 20 Hz. The trailer-mounted controller executes a Simulink-generated control node coordinating load cell acquisition (HX711 ADC), motor CAN bus telemetry, and throttle commands to a 5 kW BLDC traction motor powered by a 5 kWh LiFePO4 battery pack. A vehicle-mounted controller logs OBD-II/CAN validation data. The control pipeline implements cascaded EWMA/Hampel digital filtering with intentional phase lag for hitch-force regulation. The system was validated through on-road testing with an ICE towing vehicle pulling a 1,000-lb trailer over standardized 2.1 km segments following SAE J1321 Type II procedures. Preliminary trials demonstrated stable control performance with drawbar force regulation with no oscillatory behavior. Fuel consumption measurements showed promising improvements (9.4% lower fuel consumption in assisted vs. baseline conditions), though limited sample size precludes definitive causal claims. The primary contribution is establishing technical feasibility of cost-effective COTS implementation (USD 5,000 hardware cost) for trailer propulsion control, providing a foundation for expanded validation studies and commercial deployment pathways.
Joshi, GauravAdelman, IanLiu, JunDonnaway, Ruthie
This study presents a distinct methodology for the early detection of faulty cells in electric vehicle (EV) battery systems, leveraging temporal voltage deviation patterns under real-world charging scenarios alongside outputs from a physics-based model. A comparative longitudinal analysis was conducted on a fleet of twelve EVs—six exhibiting stable performance and the other six demonstrating early-stage anomalies characterized by intermittent transitions from drive to neutral mode. These behavioral cues were investigated as precursors to deeper battery degradation. The analysis focused on cell-level voltage dispersion in battery pack during the mid-to-high state-of-charge (SoC) range (approx. 20–30% to full charge). Vehicles in healthy condition consistently displayed minimal voltage deviation between BMS-measured cell voltages and physics-based model predictions, whereas those with latent faults showed markedly higher variance, particularly between the highest battery and model-expected cell voltages. Notably, this voltage divergence was often accompanied by a modest yet recurrent thermal rise of 2–3°C, suggesting early-stage thermal non-uniformity. All vehicles were monitored over extended distances under diverse, real-world driving and environmental conditions, enhancing the robustness and generalizability of the findings. The proposed approach underscores the diagnostic value of tracking voltage deviation trajectories as a non-intrusive, scalable means of forecasting cell-level degradation. This framework could significantly advance predictive maintenance strategies, improving both the reliability and operational lifespan of EV battery packs.
Jawle, Bharat SanjaySelvakumar, AshwinPuttoji Rao, Nagaraj Kumar
Parasitic inductance and capacitance of the battery pack can affect the performance of the electric powertrains. Characterizing these parasitic phenomena in an automotive battery pack is therefore crucial to ensuring performance and reliability. In this work, geometric models of a production automotive battery pack are developed to simulate the parasitic inductance of the busbar system, the parasitic inductance of individual modules, and other critical components. For these simulations, several assumptions and simplifications are introduced to reduce model complexity, while preserving the main electromagnetic behavior of the system. The impact of the different components on the battery pack impedance is investigated to evaluate parasitic capacitances, thereby simulating the worst-case scenario. Laboratory procedures are developed to accurately measure parasitic impedance, providing a reliable comparison between experimental data and analytical models and supporting the overall validity of the simulations.
Misley, MarcoD'Arpino, MatildeZhu, DiZhang, Liwen
As already well-understood/enormous engineering practices, the inverter AC-side NVH phenomena/mechanisms/measures for motor-equipped vehicle, are already pretty clear. In addition to inverter AC side–induced NVH issues, DC ripple induced by PE switching leads to NVH issues manifesting on the capacitor, inductor, and conductor in terms of reverse piezoelectricity, electrostriction, magnetostriction, Laplace force, and so forth. These DC-side NVH issues are already literally analyzed by a couple of literatures, and mechanisms/measures are explored/applied to electric drive development. And yet, the phenomenon that a pulsating magnetic field inside a battery pack induced by DC current ripple off PE switching brings noise at switching frequency inside the vehicle cabin is newly captured/analyzed by our research, and that has been barely searched during the literature survey. This newly discovered phenomenon is the pivotal point in this paper. Although the noise features like the conventional switching noise that originates at the AC side of the inverter, the mechanism/measures are different; hence, this newly found NVH phenomenon is termed as alternative switching noise by the author, distinguishing itself from the conventional switching noise off AC side of the inverter. The mechanisms and measures associated with this phenomenon are innovatively explored/analyzed, which ultimately offer great aid to BEV/HEV/PHEV NVH interpretation/development. First, in this paper the inverter AC-side NVH issues are overviewed including mechanisms/measures, then DC-side NVH issues from capacitor, inductor, and conductor are reviewed in terms of mechanisms/measures, third the extending exploration/study upon alternative switching noise is described in detail. The relevant analysis for alternative switching noise is barely mentioned/involved during literature survey, and that is newly found/studied within the research delineated in this paper. Fourth, two case studies are exemplified to further validate the mechanisms/measures employed during investigation. In the end, the common strategies addressing the alternative switching noise are summarized, which shall be adopted to keep issues from happening at the very beginning of vehicle development stage.
Zhao, QianZhao, YihanNiu, HaolongLi, QiweiZhang, WenchaoXue, HongbinCheng, YananLi, JingKang, Ming
Military tactical vehicles are increasingly incorporating anti-idle kits as a method to reduce fuel consumption. The larger battery pack associated with the anti-idle kit has the potential to provide new capabilities to the warfighter, who can use the battery pack to power pieces of equipment. This study analyzes a set of these new capabilities derived from the U.S. Army Universal Task List, supplemented with user interviews and doctrinal analysis. These capabilities include powering dismounted soldier systems, counter-drone and surveillance equipment, mobile refrigeration for medical applications, field maintenance tools, and mobile food services. The study then uses geolocation data collected from the U.S. Army’s National Training Center to model daily fuel consumption for soldiers performing each of these activities. The model was subsequently adapted to incorporate an anti-idle kit, revealing significant reductions in fuel usage. The analysis uses the results to define common functional requirements and inform the conceptual design of a modular kit that integrates with anti-idle systems to enable new capabilities, thereby allowing vehicles to serve as mobile energy platforms in addition to their traditional role of providing mobility.
Lusian, TrevonteMummert, TaigeKaiser, CalebGreer, MichaelBlack, NathanielOng, BennettTapahonso, EugeneMittal, Vikram
In practical applications, power cells face a mix of external influences such as temperature variations and structural limits (rigid constraints) that trigger intricate electrochemical and mechanical reactions. This study systematically explores the temporal evolution of surface pressure in lithium-ion pouch cells subjected to rigid mechanical constraints under varying thermal conditions, with a specific focus on the interplay among mechanical stress, lithium intercalation, and lithium plating. To investigate the battery’s electrochemical and mechanical responses, this work integrates experimental measurements with an electrochemical–mechanical coupling model. The analysis is performed under initial loads of 0.3, 0.5, and 1.0 MPa at 25 °C (ambient temperature) and 0 °C (representative low-temperature condition). At 25 °C, surface pressure followed a two-stage pattern: first, stress relaxation occurred, followed by a shift into quasi-steady cycling (cycle-to-cycle variations are minimal). This pattern is largely driven by the reversible volume changes in the electrodes as lithium ions are alternately inserted (intercalation) and removed (deintercalation) during electrochemical cycling of the cells. At 0 °C, slower ion transport and reaction kinetics promoted lithium plating, causing irreversible anode expansion and a continuous rise in surface pressure. Concurrently, the depletion of active lithium diminished the electrode’s maximum achievable state of charge (SOC). This limitation curtailed the degree of electrode expansion and contraction throughout charge–discharge cycles, resulting in a decrease in the amplitude of pressure fluctuations on the battery surface during cycling. Numerical simulations confirmed that lithium plating and SOC degradation collectively shaped the mechanical response at low temperatures. The proposed model accurately replicates experimental pressure evolution and distinguishes between reversible and irreversible contributions to volume changes. This work reveals how temperature and mechanical loading jointly regulate surface pressure and capacity retention, offering insights relevant to battery pack design and the optimization of low-temperature performance.
Du, YingyueChen, YingLuan, WeilingChen, Haofeng
Current studies about battery pack bottom strike usually focus on one test condition individually. To study the relation between quasi-static and dynamic crush in battery pack bottom strike, the paper combined quasi-static crush result and dynamic strike preset kinetic energy value with the same displacement damage on the battery pack bottom plate and cell. First, based on the finite element model of the battery pack, the quasi-static crush is applied. Several dynamic crush tests with different initial kinetic energy sets are also introduced. Then based on the same displacement damage, the pressure in quasi-static and kinetic energy in dynamic conditions are summarized. Fitting methods including polynomial regression, support vector regression (SVR), extreme learning machine (ELM), multilayer perceptron (MLP), Gaussian process regression (GPR), and K-nearest neighbor (KNN) regression are used to study the relation between the two different test load. The result shows that they have a strong relation. Compared with the case test of GPR and KNN, polynomial regression with a degree of 4 could be the best choice to predict the dynamic load value from quasi-static results globally for bottom plate and degree of 3 for cell.
Tang, HongxiWang, ShengweiZhou, KaiLiu, Jinyu
Due to the rapid transformation of EVs and the battery storage system, the battery management system (BMS) is essential to ensure optimal performance of the battery storage piles. A BMS monitors and controls parameters such as SOC, voltage, current, and temperature. A traditional BMS has a minimum support of analytics, and it’s limited to local processing. However, when the battery information is uploaded to the internet, it becomes easier to manage maintenance and track the battery’s performance from anywhere in the world. This Cloud-based system is easy and made earlier, thereby giving a system alarm before the issue becomes big. Managing many batteries at once saves a significant amount of money in places like EV charging stations and Energy Storage Systems (BESS). Software updates to the system can also be sent remotely. Also, a BMS connected to the cloud can be used to support weaker grids in an instant if it needs the reactive power support. Cloud integration of BMS with the grid network will help in better planning of energy management at load dispatch centers. A BMS managing a pack of batteries at a renewable energy system can help to understand power demand and decide when the best time is to charge or discharge. So, this can monitor all the batteries without being near them. Further, identifying the problems is work that focuses on an ML-RL-based battery management system connected to the cloud to control and monitor the Voltage, temperature, Cell balancing, SOC, SOH, and fault identification. This BMS system has easy scalability to thousands of batteries connected. As the demand for EVs and clean energy soars, this cloud-integrated BMS would play an important role in managing the batteries that are part of that system, making it smarter, efficient, and reliable. The proposed Q-learning–based Cloud BMS achieves 96.5% energy efficiency, 3.2% SOC RMSE, and zero safety violations across 75,000 simulated samples, using an adaptive 6,000-state Q-learning agent validated through real-time cloud integration.
R, RajarajeswariN, KalaiarasiFrancis, Elgin Calister
The performance and longevity of lithium-ion (Li-ion) batteries in electric vehicles (EVs) are critically dependent on effective thermal management. As internal heat generation during charge and discharge cycles can lead to uneven temperature distribution, exceeding optimal operating limits (25 - 40°C) can significantly degrade battery performance and lifespan. This study presents a performance evaluation of a novel liquid-based Battery Thermal Management System (BTMS) featuring a dual-directional coolant channel configuration designed to enhance thermal uniformity and heat dissipation. The proposed configuration combines horizontal and vertical coolant passages in an indirect cooling layout to address the limitations of conventional serpentine-type channels. A comprehensive thermal analysis was carried out under realistic loading conditions using three coolant types: water, ethylene glycol- based G48, and graphene-enhanced water nanofluids. These were evaluated for thermal conductivity, heat transfer efficiency, and effectiveness in minimizing temperature gradients. Graphene nanofluids exhibited superior performance due to their high thermal conductivity and enhanced convective heat transfer capabilities. Additionally, the effect of varying coolant flow rates was analyzed to simulate different operating scenarios. While increasing flow rates improved cooling effectiveness, the study also identified a threshold beyond which performance gains diminished. The novel dual-channel design demonstrated significant improvements over traditional serpentine configurations, including a notable reduction in maximum cell temperatures and enhanced temperature uniformity across the battery pack. This improvement is critical in reducing hotspots and extending battery health. The dual- directional flow facilitates more efficient convective heat transfer, offering a promising advancement in BTMS design. The integration of advanced nanofluid coolants with an innovative channel configuration pave the way for the development of more efficient, reliable, and thermally stable battery systems in next-generation electric mobility.
Selvan, Arul MozhiPeriyasamy, MuthukumarR, ThiruppathiPrasad S, HariRaghav, RBoddu, Sriram Pydi Aditya
With the development in motor technology and battery technologies, the scope for a low-cost EV has been increasing in India. There remains an after-mark potential for conversion of an ICE powered two-wheeler to an EV power train. Such a move reduces the carbon footprint from the vehicle drastically and is still being explored. This study investigates the effect of replacing the ICE with an electric motor in a 125cc motorcycle, with a particular focus on vehicle handling performance using Slalom test. The two wheelers were modelled using calculated mass properties and estimated / calculated moments of inertia using CAD for both ICE and electric powertrains. The electric propulsion system took into consideration the role of a battery pack in the mass and MI calculation. The framework with degrees of freedom is well established in BIKESIMTM simulation environment. A slalom test with automatic gear shift and throttle to maintain speed of the vehicle was set-up to estimate the handling performance. The speeds of the vehicle were computed for 60kmph condition. The output parameters of interest were the steering angle, steering torque, yaw rate, lateral acceleration and lean angle. Within the assumptions of this work, the results from the simulations indicated that handling performance of the retrofitted EV power train was comparable to that of an ICE vehicle and rider may not feel it to be drastically different.
Sankarasubramanian, HariharanM, ShaghasraV, Ramprathap
This study presents a systematic CFD-based investigation of air-cooled lithium-ion battery pack thermal management using a novel U-shaped channel. The U-shaped domain was selected due to its ability to promote recirculation and uniform air distribution, which enhances cooling effectiveness compared to conventional straight and Z-type channels. A systematic parametric optimization of inlet position and airflow velocity was performed to minimize hotspot formation and improve temperature uniformity. Results reveal that shifting the inlet from 30 mm to 20 mm and increasing velocity from 2 m/s to 3 m/s reduced the maximum battery temperature by 3.46 K, from a baseline of 333 K to 329.54 K, while maintaining minimal pressure drop. These findings highlight that strategic control of inlet parameters can yield significant thermal improvements with high cost-effectiveness and geometric simplicity.
PC, MuruganJ, SivasankarW, Beno WincyG, Arun Prasad
As electric vehicles continue to revolutionize transportation, ensuring the reliability of their powertrain systems and Battery Packs has become a critical focus. One key challenge is galvanic corrosion, which occurs when dissimilar metals in contact are exposed to an electrolyte, such as seashore moisture or road salt used in snow or ice zones. This corrosion can weaken structural components, compromise electrical conductivity, and reduce the lifespan of critical systems. Common areas at risk include metallic joints within battery enclosures, busbars, cooling systems, and electrical connectors. Environmental factors such as high humidity and temperature fluctuations further amplify the issue, making it a pressing concern for manufacturers. This paper aims to systematically identify critical galvanic joints within electric powertrain systems and Battery Packs and provide effective strategies to mitigate corrosion risks. Preventative measures include choosing compatible materials with similar electrochemical properties, applying protective coatings, and utilizing dielectric barriers to isolate metals. Design optimizations, such as minimizing contact surfaces and improving drainage, can reduce the accumulation of electrolytes, while sealed enclosures and humidity management systems offer additional environmental protection. Regular maintenance and inspections are essential to detect early signs of corrosion and prevent long-term damage. By integrating these strategies into manufacturing and design workflows, automakers can enhance the durability, safety, and overall performance of electric powertrain systems ensuring they meet the growing demands of sustainable mobility.
Narain, AdityaVenugopal, SivakumarGopalan, VijaysankarVaratharajan, Senthilkumaran
With the rise of EVs, researchers are focusing on optimizing busbar design to meet the demands of high energy density, fast charging, and compact battery packs. The busbar design starts by selecting the material and the cross-sectional area required based on the rated current requirement. The width matches or may exceed the battery cell terminal size, whereas the length is optimized such that it is packaged within the given space constraints. The research also highlights the risk of busbars to oxidation and corrosion, which increases resistance and decreases conductivity for which plating/coating techniques are applied to improve the surface finish, overall durability, conductivity and in some cases the surface hardness, while minimizing the heat loss. Using simulations and experimental validation, the study examines three key design parameters: the weld diameter for busbar welded joints, electrical resistance, and contact resistance. A detailed analysis investigates how the weld diameter influences the electrical resistance and temperature rise over ambient and the impact of contact resistance between busbars and battery cell terminals on energy efficiency and thermal behavior. The above parameters if not designed and optimized may create a bottleneck in achieving a higher performance which the cells can deliver but it will be limited because of an uneven current distribution, higher heat generation and busbar temperatures exceeding the limiting values. This makes the busbars a critical component in the battery pack design for achieving the desired performance as well as reducing concerns of overall battery safety. This study highlights the importance of an optimized busbar design for creating safer, more efficient, and reliable EV battery packs by addressing key thermal and electrical challenges.
Nogdhe, YogeshSingh, Shobit KumarPaul, JibinMishra, MukeshMenon, Praveen
Battery Thermal Management Systems (BTMS) play a critical role in ensuring the longevity, safety, and efficient operation of lithium-ion battery packs. These systems are designed to better dissipate the heat generated by the cells during vehicle operation, thereby maintaining a uniform temperature distribution across the battery modules, preventing overheating and mitigating the chances of thermal runaway. However, one of the primary challenges in BTMS design lies in achieving effective thermal contact between the battery cells and the cooling plate. Non-uniform or excessive application of Thermal Interface Materials (TIMs) without ensuring robustness and uniformity can increase interfacial thermal resistance, leading to significant temperature variations across the battery modules, which may trigger power limitations via the Battery Management System (BMS) and these thermal changes can cause inefficient cooling, ultimately affecting battery performance and lifespan. In this paper, a real-world testing was conducted on the battery pack with uneven TIM application and unoptimized distribution patterns, which resulted in significant temperature variations across the pack. In contrast, the application of uniformly optimized TIM thickness reduced these temperature differences by up to 70%, demonstrating the critical impact of consistent interface design on thermal performance. To validate and further understand these findings, combined conduction-convection heat transfer model was developed using ANSYS Fluent to simulate the thermal changes of the battery pack with different TIM thicknesses alongside the unoptimized distribution patterns. The results confirmed that uneven TIM distribution contributes significantly to thermal non-uniformity within the battery pack, whereas optimizing the thickness improves overall thermal performance. Additionally, the optimized application led to a significant reduction in weight of the thermal paste (TIMs) usage, resulting in cost savings and more efficient material utilization.
K, MathankumarJahagirdar, ManasiKumbhar, Makarand Shivaji
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