Electric Vehicle Battery Pack Research Articles

Influence mechanism of battery thermal management with flexible flame retardant composite phase change materials by temperature aging

The phase change immigration of flame retardant Composite Phase Change Material (CPCM), especially the temperature aging effect during multicycle process, greatly restricted its application in power battery pack of electric vehicle and energy storage system. In this study, the properties of flexible flame-retardant CPCMs before and after temperature aging were investigated, and the battery thermal management effects of battery modules were compared. The results revealed that flexible CPCMs with styrene block copolymers exhibited little volume change owing to their elastic and anti-leakage properties, effectively alleviating flow and agglomeration. In addition, battery modules with flexible flame-retardant CPCMs exhibited prominent battery thermal management. These mechanisms in flame-retardant CPCMs can profoundly affect the design and preparation of multifunction CPCMs, providing novel insights into passive thermal management of battery systems.

Research of electric vehicle battery packs and charging stations based on an active three-phase rectifier

Problem. The proliferation of electric vehicles has underscored the need for the development of energy-efficient charging stations and systems. These systems must deliver high efficiency, maintain a power factor close to unity, adhere to electromagnetic compatibility standards, emit low levels of higher harmonics, and enable fast charging capabilities. Current electric vehicle charging devices encounter issues such as significant power losses, high harmonic emissions to the power grid, and challenges in implementing fast charging modes. Consequently, enhancing the energy efficiency of charging stations – by reducing power losses, minimizing harmonic emissions, ensuring a high power factor, and supporting modes for regulated current and voltage sources for fast charging – is a pressing concern. Goal. The aim of this work is to perform a comparative analysis of different types of batteries for electric vehicles, exemplified by TESLA cars, presenting comparative characteristics of lithium-ion, lithium-iron-phosphate, and lithium-titanate batteries. Methodology. The study showcases an evaluation of battery units for electric vehicles and outlines a comparative assessment of lithium-ion, lithium-iron-phosphate, and lithium-titanate batteries. The research focuses on enhancing the energy efficiency of electric vehicle charging station systems through the use of active rectifiers, with modes for active power factor correction and optimal configuration. Results. An examination of the quality of converters for electric vehicle charging stations was conducted, proposing schemes for a three-phase active voltage source rectifier and an active current source rectifier. Power circuitry and space-vector switching states for power transistors are introduced. Analysis concludes that an active current rectifier may be a more promising topology. Originality. A model of a charging station based on an active current source rectifier was developed using Matlab/Simulink. Transient processes of the converter's operation and the charging of a 60 kWh battery pack were examined. It was found that the active rectifier facilitates regulation of the battery charging current, achieves a power factor close to unity, and maintains a low level of higher harmonic emissions with a harmonic distortion factor of 2.52%. Practical value. The advancement of electric vehicles necessitates the ongoing development and enhancement of the energy indicators for electric vehicle batteries and the converters of charging stations, especially those that enable fast charging. Active progress is being made in each of these areas.

Effects of inlet and outlet configurations on the topological optimization design of cooling plates for lithium-ion batteries

Topology optimization is a critical tool for enhancing the cooling efficiency and temperature uniformity of cooling plates, particularly in the context of designing thermal management systems for electric vehicle battery packs. This research employs a topology optimization approach centered on outlet enthalpy as the objective function to create a variety of cooling plates with different inlet and outlet configurations. Through an extensive numerical analysis, a comparative study is conducted among several configurations, including one inlet and one outlet (OP), two inlets and one outlet (TP), two inlets and two outlets (TTP), and four inlets and two outlets (FTP). Under 75 Pa conditions, FTP(y8) shows maximum temperature reductions of 0.42 %, 0.14 %, and 0.04 % compared to OP, TP(b), and TTP, respectively. The temperature difference also decreases by 38.55 %, 20.00 %, and 10.20 % in the respective comparisons. Additionally, as the pressure increases from 25 Pa to 75 Pa, the heat transfer coefficient of FTP(y8) experiences a notable 1.36-fold increase. Moreover, at 75 Pa, the performance evaluation criterion (PEC) value of FTP(y8) even exceeds twice the baseline. Under a 3C discharge rate, FTP(y8) excels with a maximum temperature of 304.49 K, reducing temperature differences and exhibiting superior cooling performance.

Enhancement of heat transfer efficiency in Li-ion battery packs through response surface optimization of heat pipes

Battery thermal management system (BTMS) ensure optimal performance and safety of Electric vehicle (EV) battery packs. Conventional cooling strategies using heat pipes with air and liquid cooling face challenges in effectively dissipating heat, leading to thermal management issues. This study addresses these limitations by proposing an optimized heat pipe design (helical configured) for enhanced thermal management efficiency. Computational Fluid Dynamics (CFD) simulations evaluate the proposed design for its heat transfer characteristics. The results demonstrated that Air-based cooling systems without heat pipes, in both parallel and staggered arrangements, showed temperature ranges of 30.64∘C to 42.66∘C and 31.14∘C to 41.76∘C, respectively and Liquid cooling systems using water-glycol fluid demonstrated temperature ranges of 30.33∘C to 35.96∘C within the battery pack. This is because the helical configuration provides a larger surface area for heat transfer, allowing for improved heat dissipation. Furthermore, Weight optimization techniques are employed to reduce the overall weight of the battery pack while maintaining structural integrity. The proposed design and optimization strategies contribute to advancing BTMS technology, enhancing battery performance, extending battery life, and ensuring safety. Future research directions include scalability studies for larger battery packs and evaluating the optimized design under various operating conditions. Exploring advanced materials and fabrication techniques can enhance heat transfer capabilities and system efficiency.

Evaluation method for consistency of lithium-ion battery packs in electric vehicles based on the Mahalanobis-Taguchi system

The consistency of battery packs is vital for safety and reliability during electric vehicle (EV) operations. Many consistency evaluation methods based on laboratory conditions are time-consuming and difficult to implement in the real-world. This study proposes an evaluation method for the consistency of lithium-ion battery packs in EVs based on the Mahalanobis-Taguchi system (MTS). First, a Douglas-Peucker (DP) algorithm was developed to compress high-dimensional cell voltage data, which reduced the feature extraction time by 81.64 %. Next, the consistency features were extracted based on sample entropy and fast-dynamic time warping (Fast-DTW) to quantify inconsistencies in battery parameters. Finally, the consistency evaluation method of the two-level warning based on MTS was established, and the hierarchical inconsistency warning threshold was identified based on the Chebyshev theorem. The results showed that the inconsistencies in battery packs were identified and quantitatively evaluated, and the occurrences of inconsistencies are occasionally discontinuous. The inconsistencies in battery packs were detected at high state of charge (SOC) levels at the end of charging. This method can evaluate the consistency of battery packs online based on EV operation data to monitor battery safety and provide detailed information for maintenance.

Design approach for electric vehicle battery packs based on experimentally tested multi-domain models

This work proposes a multi-domain modelling methodology to support the design of new battery packs for automotive applications. The methodology allows electro-thermal evaluation of different spatial arrangements of the storage cells by exploiting the implementation of numerical and geometrical battery pack models. Concerning the case study on Li-NMC battery technology, the study has completed the electro-thermal characterization of the storage cells starting from the collected experimental data, considering both the thermal interactions among cells and the effects of the state of health. This work also investigates the effects of forced air-cooling systems focusing on battery pack hot spots and temperature distributions. The results show a good fit between numerical models and data obtained from single-cell experiments. The virtual linking of geometric and numerical lumped-parameter models proved to be effective in rapid battery pack prototyping for electric vehicles, helping designers and manufacturers find suitable solutions for specific automotive applications.

Analysis of the electrical and thermal behaviour of Li-ion batteries using 0D and 3D-CFD approaches with validation on experimental data

Due to their characteristics, lithium-ion cells are the reference in the construction of a battery pack for electric vehicles (EVs). Despite this, their use is strongly affected by the operating temperature because the materials they are made of are thermally stable only in a relatively limited range around ambient temperature. Cell modelling and simulation become therefore essential in the design of the cell, of the battery pack and of its auxiliary systems to optimize performance while maintaining sufficient safety margins.In the present study, two zero-dimensional equivalent circuit models of a commercial Li-ion cell are developed and tuned in order to predict the electrical and thermal behaviour of the cell. The models are validated and compared with experimental data found in the scientific literature referring to both dynamic and static tests. This comparison shows the importance of tuning the model parameters, which are decisive for the accuracy of the simulation.Using a commercial tool dedicated to battery modelling, a three-dimensional model is then developed to investigate the electrical and thermal behaviour of the cell from a spatial point of view. The results obtained are aligned with those found in the scientific literature.With the present work, it has been possible to simulate and analyse the global behaviour of the cell (0D model) as well as its detailed behaviour (3D model) using relatively modest computational resources, thus constituting a solid base for more complex modelling such as that of a battery pack and its cooling system.

Lithium-Ion Batteries SOH Estimation With Multimodal Multilinear Feature Fusion

As a key status for battery energy storage systems, state of health (SOH) can provide the fundamental information for lifespan management of the battery pack in electric vehicles (EV). Traditionally, features are extracted from various signals to establish a powerful data-driven model for the lithium-ion battery (Li-ion) SOH estimation. One issue left is how to utilize the existing features from diverse modalities of measurement signals for a superior battery aging information capture. The available options are selecting the features by analyzing their correlations with SOH. This paper aims to investigate the intercorrelations between various features through the multimodal multilinear fusion mechanism, which enables to utilize the multimodal multilinear features (MMF) and their interaction characteristics. A high-order polynomial module is designed to fuse the MMF from various sources. To improve the efficiency and performance of the SOH estimator, a 2D convolutional neural network (CNN) network is chosen to use the proposed MMF. The performance of the proposed method is validated on two independent datasets, which obtains the lowest mean absolute error (MAE) of 0.37% and the lowest root mean square error (RMSE) is 0.45%.

Development of a Computational Fluid Dynamics Simulation Framework for Aerothermal Analyses of Electric Vehicle Battery Packs

Abstract The rise of electric vehicles has driven the extensive adoption of lithium-ion batteries (LIBs) due to their favorable attributes—compactness, low resistance, high power density, and minimal self-discharge. To enhance LIB reliability, an efficient battery thermal management system is imperative. This paper introduces a finite volume-based aerothermal analysis framework for a 32-cell high-energy density LIB pack. We also explore the effectiveness of various turbulence models in capturing local hotspots, discharge rates, and current levels across different geometries and inlet velocities. Our approach involves modeling the battery using Simcenter Battery Design Studio and importing it into Simcenter star-ccm+ for aerothermal simulations in which temperature distribution, discharge rates, current levels, and maximum temperature across are monitored for aligned, cross, and staggered configurations of the battery pack under varying inlet velocities. Our findings highlight the significant impact of boundary condition modeling on simulation stability. Also we observed that the standard k–ε model provides the most accurate predictions, with prediction accuracy within 3–10% of experimental data. Moreover, we identify substantial dependencies between heat generation and discharge current, as well as thermal gradients and inlet velocity. Finally, we conclude that the aligned cell arrangement offers the best thermal uniformity and cooling efficiency.

Electric vehicle battery pack state of charge estimation using parallel artificial neural networks

Electric vehicle battery pack state of charge estimation using parallel artificial neural networks

Numerical and experimental study on efficient optimization of variable cross-section battery thermal management systems using an improved flow resistance network model

Air-cooled systems are widely used for cooling of battery packs in electric vehicles. Optimization method combined with the flow resistance network (FRN) model is effective for system design. However, the local pressure loss of divergence and convergence ducts in the traditional FRN model is ignored, leading to large error when applying the model in systems with variable cross-section channels. In this study, the local loss coefficients of the contractive and diffusive channels are derived and the improved FRN model is developed for velocity calculation of variable cross-section air-cooled systems. The improved model is verified using computational fluid dynamics method. Based on the improved FRN model, the cross-section width distribution of the divergence duct is calculated from the given flow rate distribution. The shape of the divergence deflector is optimized by adjusting the flow rate distribution and using the improved model. The results indicate that the temperature difference of the battery cells decreases by more than 84% after the optimization, with the maximum temperature decreasing by more than 3.8 K. Furthermore, the optimized system performs better than those in the previous studies. Also, experiments are carried out to verify the effectiveness of the developed optimization method based on the improved FRN model.

Local Electrochemical Corrosion of 6061 Aluminum Alloy with Nano-SiO2/MAO Composite Coating.

To improve the corrosion resistance of 6061 Al in electric vehicle battery packs, a composite coating of nano-SiO2/Micro-Arc oxidation (MAO) ceramic structure was prepared on its surface. Electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization curves (PDP) were used to evaluate the corrosion resistance of the specimens after 7 days immersion in a 3.5% NaCl solution. The corrosion resistance of the prefabricated coatings was measured via local electrochemical impedance spectroscopy (LEIS). Confocal microscopy, scanning electron microscopy (SEM), and X-ray diffraction (XRD) were used to characterize the microstructure and phase composition of the specimens. An energy dispersive spectrometer (EDS) was used to detect the elemental composition of the surface of the specimen. The results showed that the specimen with nano-SiO2/MAO composite coating had the least amount of micropores and superior corrosion resistance. The global electrochemical impedance of nano-SiO2/MAO composite coating was 1.1 times higher than that of the MAO coating and 8.4 times higher than that of the 6061 Al. When the coating was defective, the local electrochemical impedance of the nano-SiO2/MAO composite coating was still two times higher than that of the MAO coating. In the presence of scratches, the nano-SiO2/MAO composite coating still showed high corrosion resistance. The collapse corrosion mechanism of the nano-SiO2/MAO composite coating was proposed.

Aqueous electrochemical delithiation of cathode materials as a strategy to selectively recover lithium from waste lithium-ion batteries

Lithium recovery from end-of-life Li-ion batteries (LIBs) through pyro- and hydrometallurgical recycling processes involves several refining stages, with high consumption of reagents and energy. A competitive technological alternative is the electrochemical oxidation of the cathode materials, whereby lithium can be deintercalated and transferred to an electrolyte solution without the aid of chemical extracting compounds. This article investigates the potential to selectively recover Li from LIB cathode materials by direct electrochemical extraction in aqueous solutions. The process allowed to recovering up to 98% of Li from high-purity commercial cathode materials (LiMn2O4, LiCoO2, and LiNi1/3Mn1/3Co1/3O2) with a faradaic efficiency of 98% and negligible co-extraction of Co, Ni, and Mn. The process was then applied to recover Li from the real waste LIBs black mass obtained by the physical treatment of electric vehicle battery packs. This black mass contained graphite, conductive carbon, and metal impurities from current collectors and steel cases, which significantly influenced the evolution and performances of Li electrochemical extraction. Particularly, due to concomitant oxidation of impurities, lithium extraction yields and faradaic efficiencies were lower than those obtained with high-purity cathode materials. Copper oxidation was found to occur within the voltage range investigated, but it could not quantitatively explain the reduced Li extraction performances. In fact, a detailed investigation revealed that above 1.3 V vs. Ag/AgCl, conductive carbon can be oxidized, contributing to the decreased Li extraction. Based on the reported experimental results, guidelines were provided that quantitatively enable the extraction of Li from the black mass, while preventing the simultaneous oxidation of impurities and, consequently, reducing the energy consumption of the proposed Li recovery method.

Heat Transfer Improvement of Prismatic Lithium-Ion Batteries via a Mini-Channel Liquid-Cooling Plate With Vortex Generators

Abstract Temperature is a critical factor affecting the performance and safety of battery packs of electric vehicles (EVs). The design of liquid cooling plates based on mini-channels has always been the research hotspots of battery thermal management systems (BTMS). This paper investigates the effect of adding vortex generators (VGs) to the liquid cooling channel on the heat dissipation capacity and temperature uniformity of the battery. The shape of the vortex generators (triangle, trapezoid, and semicircle), placement position (middle, inlet, and outlet of the channel), different flowrates, and different numbers of channels on the heat dissipation of the battery are systematically analyzed. The research results indicate that (1) compared to the triangular and trapezoidal vortex generators, the semicircular vortex generators have a lower cost in terms of pressure drop while maintaining the same heat dissipation efficiency. The pressure drop of the semicircular vortex generators is 15.89% less than that of the trapezoidal vortex generators and 20.49% less than that of the triangular vortex generators. (2) The effect of adding vortex generators is more obvious when the flowrate is small in the cooling channels. When the flow velocity is 0.025 m/s, the heat dissipation performance can be increased by 7.4%. (3) When the cross-sectional area of the inlet is fixed, the heat dissipation effect of more channels is better. The average temperature of three and seven cooling channels decreases from 311.23 K to 310.07 K, with a decrease of 8.87%. (4) The temperature difference can be effectively reduced when the vortex generators are concentrated near the outlet of the flow outlet. Its temperature difference is 1.8 K lower than that when the vortex generators are placed near the inlet, with a decrease of 10.5%.

A Data-Driven State-of-Health Estimation Model for Lithium-Ion Batteries Using Referenced-Based Charging Time

Accurate online state of health (SOH) estimation is crucial for the efficient and safe operation of lithium-ion battery packs in electric vehicles and grid-connected energy storage units. This paper proposes a novel data-driven SOH estimation model for lithium-ion batteries based on a new health indicator, namely referenced-based charging time. The proposed model utilizes the referenced-based charging time of partial charging cycles to predict the SOH using a machine learning approach. A deep feed-forward neural network, characterized via testing 90 different shallow and deep architectures, is implemented, trained, and tested on 17 batteries, which are cycled differently. The results show that the root mean square percentage error is 0.43% overall and less than 1% for each test cell.

IOT BASED BATTERY MONITORING SYSTEM FOR ELECTRIC VEHICLE

The rapid adoption of electric vehicles (EVs) represents a critical step towards reducing greenhouse gas emissions and achieving sustainable transportation solutions. One of the key components in an EV is its battery, which plays a pivotal role in determining the vehicle's performance, range, and overall efficiency. Ensuring the health and longevity of EV batteries is essential for promoting EV adoption and optimizing their operational capabilities. This project presents an IoT-based Battery Monitoring System (BMS) designed to address the challenges associated with monitoring and managing the batteries in electric vehicles. The system leverages the power of Internet of Things (IoT) technology to continuously gather real-time data from the EV's battery pack. The IoT-based BMS consists of various components, including battery sensors, microcontrollers, wireless communication modules, and cloud-based data analytics. Battery sensors collect data on parameters such as voltage, current, temperature, and state of charge (SoC) from individual cells within the battery pack. In conclusion, this project presents an innovative IoT-based Battery Monitoring System that has the potential to revolutionize the way we manage and maintain electric vehicle batteries. Key Words: Battery pack, Electric vehicle Voltage, State of charge, Vehicle performance.

Techno-economic analysis of lithium-ion battery price reduction considering carbon footprint based on life cycle assessment

Lithium-ion batteries (LIBs) play a crucial role in driving energy transitions, particularly in electric vehicles (EVs) and energy storage systems. Forecasting LIB prices has received significant attention due to the tightening of raw material markets. Additionally, the implementation of carbon pricing policies has highlighted the need to incorporate the carbon footprint of LIBs in price evaluation. This study presents a comprehensive analysis of the carbon footprint, pricing trajectories, and forthcoming carbon pricing ramifications associated with LIBs. Firstly, the findings derived from the life-cycle carbon footprint assessment indicate that the global production volume-weighted average carbon footprint of EV battery packs spans 49.2–81.1 kgCO2eq/kWh, depending on the chosen end-of-life treatment. Strategic end-of-life selections, aligned with battery chemical composition, can diminish the carbon footprint by up to 46% relative to improper disposal methods. Notably, direct cathode recycling of NCA and NMC622 batteries exhibits superior environmental performance. Secondly, techno-economic analysis predicts that the mean price of EV battery packs with diverse chemical compositions will decline to $75.1/kWh by 2030, factoring in the compound annual growth rate of critical raw material prices over the past decade. LFP batteries emerge as the top economic performers. Lastly, the results reveal that monetizing a battery's carbon footprint may offset battery price reductions through learning effects. This underscores the imperative of effective recycling for curtailing the carbon footprint and ensuring the enduring economic and environmental competitiveness of LIBs.

Enhancing Disassembly Practices for Electric Vehicle Battery Packs: A Narrative Comprehensive Review

In the context of current societal challenges, such as climate neutrality, industry digitization, and circular economy, this paper addresses the importance of improving recycling practices for electric vehicle (EV) battery packs, with a specific focus on lithium–ion batteries (LIBs). To achieve this, the paper conducts a systematic review (using Google Scholar, Scopus, and Web of Science as search engines), considering the last 10 years, to examine existing recycling methods, robotic/collaborative disassembly cells, and associated control techniques. The aim is to provide a comprehensive and detailed review that can serve as a valuable resource for future research in the industrial domain. By analyzing the current state of the field, this review identifies emerging needs and challenges that need to be addressed for the successful implementation of automatic robotic disassembly cells for end-of-life (EOL) electronic products, such as EV LIBs. The findings presented in this paper enhance our understanding of recycling practices and lay the groundwork for more precise research directions in this important area.

The effects of fast and normal charging, driving cycle, and a 24-hour regional climate on the performance of electric vehicle batteries

Battery performance is significantly influenced by temperature; therefore, many plug-in electric cars and battery-powered vehicles employ thermal management strategies to improve battery efficiency. The study includes the modeling of an electric vehicle battery pack to simulate the effects of different driving cycles, charging conditions, environmental conditions, and fast and normal charging with different HTC values. The equivalent circuit model was used to simulate the 18650 batteries consisting of 72 cells in a 6S12P configuration. The battery pack was then tested with realistic HWFET, US06, and UDDS drive cycles matched to the dimensions of the battery pack, and the battery pack was examined for the effects of fast and normal charging. The model predicted how the cell will behave thermally when subjected to stress from variables like excessive consumption of power and high surrounding temperatures. In the stress scenario, a significant temperature increase was observed during the US06 drive cycle, followed by the HWFT and UDDS drive cycles. Due to the high ambient temperature in New Delhi during the rest cycle, it takes a while for the battery pack temperature to reach the ambient temperature. Fast charging is causing damage to batteries since the temperature of the battery rises as a result of the high charging rate, resulting in lower battery life when compared to normal charging.

Heat-Absorbing Composite Strength Analysis for Electric Vehicles Battery Pack Cover

Heat-Absorbing Composite Strength Analysis for Electric Vehicles Battery Pack Cover