Vehicle Energy Storage System Research Articles

Grain Analysis of NCM Cathode Materials by ASTAR Technique and Its Effect on Battery Performance

Lithium-ion batteries (LIBs) are one of the most promising energy storage systems for portable electronic devices, electric vehicles, and renewable energy systems. Among the various cathode materials for LIBs, nickel cobalt manganese (NCM) oxide has attracted considerable attention due to its high specific capacity, good cycling stability, and appropriate cost for commercialization. However, Ni-rich NCM (Ni >80%) showed poor cyclability and huge gas evolution because of surface instability.Single crystal NCM has been suggested as a solution to these issues due to its excellent properties. However, it is difficult to quantify the degree of single crystallinity because it is so far subjective. In this study, we employed ASTAR technique (transmission electron microscopy combined with electron backscatter diffraction) to investigate the microstructural features of NCM cathode materials. Our ASTAR analysis showed that NCM cathode materials consist of complex grain and grain boundary structures with varying orientations and sizes. By analyzing the grain size and its morphology, we were able to define the single crystallinity of NCM cathode materials, including the poly NCM and single crystal NCM particles.Furthermore, we found that the grain size and its distribution significantly affects the battery performance and lifespan of NCM cathode materials. Specifically, the poly NCM particles exhibited a larger grain boundary and surface area compared to the single crystal NCM particles. The poly NCM particles also showed a faster DC-IR increase and a shorter lifespan than the single crystal NCM particles, indicating that the grain size has a critical influence on the battery performance and lifespan of NCM cathode materials.Our results provide insights into the design and optimization of NCM cathode materials for next-generation LIBs. By controlling the grain size and its distribution of NCM cathode materials, it is possible to enhance the battery performance and lifespan. Therefore, our study highlights the importance of understanding the microstructural features of NCM cathode materials for developing high-performance and stable LIBs.

Stabilizing the interface between high-Ni oxide cathode and Li6PS5Cl for all-solid-state batteries via dual-compatible halides

All-solid-state batteries (ASSBs) with enhanced safety are promising next-generation energy storage systems for electric vehicles. However, the utilization of ASSBs is hindered by the high interfacial resistances between high-Ni-oxide cathodes and sulfide solid electrolytes (SEs). Passivating interphases form on the cathode in contact with the SE upon charging, deteriorating the power capability and cyclability. Inspired by the excellent stability of halides at high voltages, herein, we propose the interfacial engineering of LiNixCoyMnzO2 (NCM) and Li6PS5Cl (LPSCl) using Li+-conductive halides with ʻdual compatibilityʼ. The charge-transport and interfacial resistances of the halide-coated NCM (NCM@halide) electrodes are analyzed using a transmission-line-based impedance model. Impedance analyses indicate that the interfacial halide nanolayers slightly increase the Li+-transport resistance, but the NCM@halide electrodes exhibit considerably lower interfacial resistances than bare NCM. Furthermore, the interfacial resistance is highly dependent on the halide composition: NCM@Li2ZrCl6 shows a lower interfacial resistance than NCM@Li3InCl6 and NCM@Li3YCl6, resulting in superior rate-capability and cycling stability. The composition-dependent electrochemical properties of the NCM@halide electrodes are discussed in terms of the dual compatibility of the halides with NCM and LPSCl. This study offers an effective approach for addressing the interfacial challenges of sulfide-based ASSBs with high-Ni oxide cathodes.

Review of Hybrid Energy Storage Systems for Hybrid Electric Vehicles

Energy storage systems play a crucial role in the overall performance of hybrid electric vehicles. Therefore, the state of the art in energy storage systems for hybrid electric vehicles is discussed in this paper along with appropriate background information for facilitating future research in this domain. Specifically, we compare key parameters such as cost, power density, energy density, cycle life, and response time for various energy storage systems. For energy storage systems employing ultra capacitors, we present characteristics such as cell voltage, cycle life, power density, and energy density. Furthermore, we discuss and evaluate the interconnection topologies for existing energy storage systems. We also discuss the hybrid battery–flywheel energy storage system as well as the mathematical modeling of the battery–ultracapacitor energy storage system. Toward the end, we discuss energy efficient powertrain for hybrid electric vehicles.

Energy management strategies in distribution system integrating electric vehicle and battery energy storage system: A review

AbstractThe electricity sector is witnessing a rise in renewable energy sources and the widespread adoption of electric vehicles, posing new challenges for distribution system. Additionally, the surge in carbon emissions resulting from industrialization and population growth continues to worsen global warming and climate change. In response, integrating electric vehicles (EVs) and battery energy storage systems (BESS) has emerged as a critical strategy, presenting both challenges and opportunities in effective energy management. BESSs offer potential solutions to mitigate these impacts. Furthermore, this review thoroughly explores issues related to lithium‐ion batteries, particularly in the context of EVs and energy management systems (EMS), identifies challenges, and provides recommendations for future research directions. The article concludes by outlining the current extent of investigation in the field of BESS and EV systems to provide researchers with a clear understanding. The escalation of carbon emissions stemming from industrialization and population expansion has worsened the effects of global warming and climate change. To address this challenge, the integration of Electric EVs and energy storage systems (ESS) has emerged as a pivotal strategy. This study examines optimization techniques, methodologies, and the evolving market landscape in distributed systems, with a focus on EVs and BESS. It also explores issues related to lithium‐ion batteries, particularly in the context of EVs and energy management systems. The article highlights the challenges and opportunities in the field of BESS and EV systems, emphasizing the need for ongoing research. BESSs offer potential solutions to mitigate these impacts. Moreover, it offers an extensive analysis of the existing BESS installations, outlining main areas of interest, pointing out difficulties, clarifying areas of unfinished study, and providing future directions.

An Integrated Self-Modularized Battery Equalizer and Supercapacitor Charger for Hybrid Electric Vehicle Energy Storage System

An Integrated Self-Modularized Battery Equalizer and Supercapacitor Charger for Hybrid Electric Vehicle Energy Storage System

A novel hybrid approach for efficient energy management in battery and supercapacitor based hybrid energy storage systems for electric vehicles

A novel hybrid approach for efficient energy management in battery and supercapacitor based hybrid energy storage systems for electric vehicles

Many-objective optimization based mutual feed scheduling for energy system of integrated energy station

The battery storage system of the integrated energy station contains electric vehicles as the distributed energy storage node of the regional power system can help the regional power system to achieve peak shaving and valley filling. This paper proposes a many-objective optimization based mutual feed model of the energy system of the integrated energy station. The model includes multiple modules of electric vehicle (EV), wind turbine (WT), photovoltaic (PV) and battery energy storage system (BESS). BESS was modeled according to the two behaviors of EVs charging and swapping. The model ensures the role of peak shaving and valley filling for regional power, reduces the loss of battery life in the battery storage system of the integrated energy station, and reduces the operating cost of the battery storage system. In the optimized results, the regional power system load peak-to-valley ratio by 28.72 %, and the daily battery charge/discharge life loss is minimized to 0.00036 %. In addition, for known many-objective optimization problems, this paper also proposes a new meta-heuristic many-objective optimization algorithm the non-dominated sorting hunter prey optimization (NSHPO for short) and compared with other four many-objective optimization algorithms by three indexes (Distribution range, Hypervolume index, and Running time). The simulation results show that compared with other algorithms, the HV metrics of NSHPO are lower by about 1.56 %-7.26 %, Spread metrics are better by about 0.39 %-2.73 %, and the proposed NSHPO algorithm is better in terms of convergence and distributivity.

A novel hybrid PI–backstepping cascade controller for battery–supercapacitor electric vehicles considering various driving cycles scenarios

AbstractThe integration of supercapacitors as hybrid energy storage systems in electric vehicles has attracted the attention of many researchers and has been considered as a promising solution. Bidirectional DC/DC converters (BDDCs) play a fundamental role in HESS, as they manage the power flow by controlling currents and regulating the DC bus voltage. However, they encounter the challenge of uncertainties and high fluctuation power loads, necessitating the fast dynamics, stability, and high robustness of the controller. This paper proposes a novel hybrid proportional–integral and backstepping cascade controller to regulate the DC‐bus voltage under uncertainties and load variations, and to control the current references of the on‐boarded sources. To confirm the asymptotic stability of the whole system, a nonlinear stability analysis is conducted using the Lyapunov theorem. A power management strategy is applied to distribute the power loads and generate reference currents for the BDDCs controller. Simulations results under various driving cycles using MATLAB/Simulink demonstrate the superiority of the proposed controller compared to conventional proportional–integral and backstepping controllers. A real‐time controller‐hardware‐in‐the‐loop test bench is developed to validate the effectiveness of the proposed strategy.

Exploring the Synergy of Artificial Intelligence in Energy Storage Systems for Electric Vehicles

The integration of Artificial Intelligence (AI) in Energy Storage Systems (ESS) for Electric Vehicles (EVs) has emerged as a pivotal solution to address the challenges of energy efficiency, battery degradation, and optimal power management. The capability of such systems to differ from theoretical modeling enhances their applicability across various domains. The vast amount of data available today has enabled AI to be trained and to predict the behavior of complex systems with a high degree of accuracy. As we move towards a more sustainable future, the electrification of vehicles and integrating electric systems for energy storage are becoming increasingly important and need to be addressed. The synergy of AI and ESS enhances the overall efficiency of electric vehicles and plays a crucial role in shaping a sustainable and intelligent energy ecosystem. To the best of the authors’ knowledge, AI applications in energy storage systems for the integration of electric vehicles have not been explicitly reviewed. The research investigates the importance of AI advancements in energy storage systems for electric vehicles, specifically focusing on Battery Management Systems (BMS), Power Quality (PQ) issues, predicting battery State-of-Charge (SOC) and State-of-Health (SOH), and exploring the potential for integrating Renewable Energy Sources with EV charging needs and optimizing charging cycles. This study examined all topics to identify the most commonly used methods, which were analyzed based on their characteristics and potential. Future trends were identified by exploring emerging techniques introduced in recent literature contributions published since 2017.

Enhancing passive cell balancing techniques for electric vehicles

This research endeavors to enhance the efficiency and functionality of electric vehicle (EV) energy storage systems by scrutinizing the state of charge (SOC) across three batteries. Utilizing Matlab Simulink, a comprehensive battery management system (BMS) integrating passive cell balancing techniques has been meticulously devised. Additionally, a pioneering protective mechanism has been proposed to prevent undue discharges and overcharges, thus ensuring the longevity and reliability of EV battery systems. The study's findings underline the significance and applicability of the developed model in facilitating prospective enhancements within the realm of EV energy storage systems. By meticulously analyzing SOC dynamics across multiple batteries, the study offers valuable insights into optimizing battery utilization, prolonging battery lifespan, and enhancing overall system performance. Moreover, the integration of passive cell balancing techniques within the BMS framework represents a noteworthy advancement in battery management strategies. This approach not only promotes uniformity in SOC distribution among battery cells but also minimizes energy losses and mitigates the risk of cell degradation, thereby bolstering the operational efficiency and durability of EV energy storage systems. Furthermore, the proposed protective mechanism serves as a proactive measure to safeguard against potential damage caused by extreme operating conditions, such as overdischarge and overcharge events. By implementing real-time monitoring and control mechanisms, the protective system ensures the safe and reliable operation of EV batteries under varying driving conditions, thereby enhancing both safety and performance aspects. In conclusion, this research contributes to the ongoing efforts aimed at advancing the state-of-the-art in EV energy storage systems, holding immense potential for fostering innovation and driving sustainable progress in the field of electric mobility.

The gas production characteristics and catastrophic hazards evaluation of thermal runaway for LiNi0.5Co0.2Mn0.3O2 lithium-ion batteries under different SOCs

Lithium-ion batteries (LIBs) are widely used as electrochemical energy storage systems in electric vehicles due to their high energy density and long cycle life. However, fire accidents present a trend of frequent occurrence caused by thermal runaway (TR) of LIBs, so it is especially important to evaluate the catastrophic hazards of these LIBs. This study conducted the adiabatic TR test coupled gas production test, Gas Chromatography-Mass Spectrometry test, and explosion limit test on a commercial LIB with Ni0.5Co0.2Mn0.3 as the cathode material at different states of charge (SOCs). The results show that the TR temperature and the maximum temperature at low SOC are lower compared to that at a high SOC. The probability of LIBs TR at less than SOC = 50 % is small and also causing less harm. For the gas production characteristics, the lower the SOC of the battery, the lower the gas production volume. The peak and steady-state gas production increase with the increase of SOC. For the mixed gases generated during TR, the content of CO2 shows a trend of decreasing with the increasing of battery SOC, while that of H2 and CO increase with the increasing of SOC. For the explosion limit of the mixed gas, the lower explosion limit and upper explosion limit decrease and increase with the increasing of SOC, respectively. Finally, based on the seven parameters related to the TR gas production of LIBs and so on, the analytic hierarchy process method was used to establish a LIB TR disaster-causing hazard evaluation system. The evaluation system can quantitatively evaluate the thermal safety of a LIB. This is instructive for establishing a comprehensive quantitative evaluation method for battery safety in practical engineering applications.

Energy management strategy for photovoltaic powered hybrid energy storage systems in electric vehicles

Nowadays, electric vehicles (EVs) using additional energy sources frequently deliver a safe ride without concern about the distance. The energy sources including a battery, an ultra-capacitor (UC), and a photovoltaic (PV) are considered in this research for driving the EV. Vehicles that only use battery-oriented technologies experience problems with charging and quick battery discharge. EVs are used with an ultracapacitor to decrease the quick discharge effects and increase the lifetime of the battery. Furthermore, bidirectional DC-DC converters are a type of power electronics device used to verify the smooth transfer of generated power from energy sources to the motor throughout various stages of the driving cycle. Therefore, this study proposes a perturb and observe (P&O) energy management control technique based on tuna swarm optimization (TSO). The suggested TSO-P&O completely uses UC while regulating the battery because it lowers dynamic battery charging and discharging currents. Due to the aforementioned aspect, the suggested TSO-P&O increases battery life and demonstrates a very dependable, long range power source for an electric car. The TSO-P&O technique achieves the EVs by obtaining the maximum speed of 91.93 km/hr. with a quicker settling time of 4,930 ms when compared with the existing zero-fuel zero-emission (ZFZE) method.

Energy management of hybrid energy storage system in electric vehicle using hybrid methodology

ABSTRACT Electric vehicles operate in a dynamic environment with constantly changing driving conditions, such as varying speeds, terrains, and traffic patterns. Adapting an energy management (EM) strategy to these conditions to maximise efficiency is a significant challenge. Achieving optimal energy management must also consider the cost implications. This manuscript proposes a hybrid technique for the optimum charging capability of electric vehicles (EVs) with a hybrid energy storage system (HESS), such as an electric vehicle, battery, and supercapacitor (SC). The objective is to maximise energy utilisation efficiency, extend the lifespan of energy storage devices, improve overall vehicle performance, and minimise charging costs. The WSO is incorporated to generate the dataset of possible input parameters of HESS. Using the accomplished WSO dataset, the SNN is trained and forecasts the optimum input parameters of Hybrid ESS. The proposed method is implemented in the MATLAB platform and compared with existing methods. The proposed method supercapacitor power is 4.3 × 104W, proposed battery power is 7 × 104 W, supercapacitor current is 90 A and the proposed battery current is 20 A. The proposed method is higher than other existing methods like RFA, WHO and DCNN methods.

Electrochemical Performance and Microstructure Evolution of a Quasi-Solid-State Lithium Battery Prepared by Spark Plasma Sintering.

Solid-state lithium batteries are promising next-generation energy storage systems for electric vehicles due to their high energy density and high safety and require achieving and maintaining intimate solid-solid interfaces for lithium-ion and electron transport. However, the solid-solid interfaces may evolve over cycling, disrupting the ion and electron diffusion pathways and leading to rapid performance degradation. The development of solid-state lithium batteries has been hindered by the lack of fundamental understanding of the interfacial microstructure change over cycling and its relation to electrochemical properties. Herein, we prepared a quasi-solid-state lithium battery, 30%LiFePO4-55%Li1.5Al0.5Ge1.5(PO4)3-15%C| Li1.5Al0.5Ge1.5(PO4)3|Li, by spark plasma sintering, and employed it as a model system to reveal the microstructure evolution at the solid-solid interfaces with electrochemical performance of the batteries. The electrochemical assessment showed that the quasi-solid-state lithium battery exhibited a discharge specific capacity of about 150 mAh g-1 in the first 80 cycles and then experienced severe capacity attenuation afterward, accompanied by a gradual internal resistance increase. Scanning electron microscopy observation showed that more cracks were formed inside the solid-state electrolyte and at the solid-solid interfaces as the battery cycled from 10 to 67 and 157 cycles. Detailed microstructure and phase analysis by high-resolution transmission electron microscopy and selected area electron diffraction discovered that the crack formation and performance decay were mainly caused by (1) the volume change of the LiFePO4 composite cathode during cycling, (2) the grain expansion of the Li1.5Al0.5Ge1.5(PO4)3 solid-state electrolyte at its interface with lithium anode, and (3) the formation of a solid electrolyte interphase layer, comprising Li2CO3, LiF, and LiTFSI, at the cathode-solid-state electrolyte interface. These microstructure changes built up over repeated battery cycling, ultimately causing the structure collapse and battery failure. The microstructure evolution information is expected to guide the design of better structures and interfaces for solid-state lithium batteries.

Ultrasonic Nondestructive Diagnosis of Cylindrical Batteries Under Various Charging Rates

Lithium-ion batteries have been used increasingly as electrochemical energy storage systems for electronic devices and vehicles. It is important to accurately estimate the state of charge (SoC) of a battery management system to control the battery operation to optimize performance, lifetime, and safety. The current work experimentally leverages ultrasonic diagnostic technology to investigate the SoC of lithium-ion batteries during the charge/discharge processes. A cylindrical-type nickel-cobalt-aluminum (NCA)–based 2500mAh 20A (INR18650-25R) battery was used for ultrasonic measurements with various charge/discharge rates of C/10.4, C/5.2, and C/1.3 at constant currents. The ultrasonic signals were analyzed for extracting wave velocity and wave attenuation. For all the testing rates, wave velocity increased in the charge process and decreased in the discharge process. Velocity profiles corresponding to lower rates of C/10.4 and C/5.2 exhibited primary peaks at the maximum SoCs, whereas the absolute wave velocity of C/1.3 rate showed primary peaks that occurred slightly after the SoC peak, indicating a delayed maximum Young's modulus. The wave attenuation computed for the C/10.4 rate had local maxima in the charge and discharge processes and depicted negative correlations with SoC, ranging from 0% to 18%, and positive correlations with SoC from 18% to 85%. On the other hand, the wave attenuation curves of the C/1.3 rate showed no local peaks and had negative correlations with SoC, ranging from 0% to 28%, and positive correlations with SoC ranging from 28% to 53%.

Frequency Based Supervisory Power Management Approach for Battery-Supercapacitor Electric Vehicle Considering Road Slope

This article proposes a real time strategy based on frequency separation for energy management of battery/Supercapacitor (SC) based Hybrid Energy Storage System (HESS) in Electric Vehicle (EV). The performance and life cycle of battery are important parameters in determining the efficiency of EVs. With the aim of improving the effectiveness of battery in battery/SC based EVs, a supervisory Symlets wavelet based Energy Management System (EMS) using Fuzzy Controller (FC) is proposed which considers real time road slope and vehicle condition. Actual road grade values are computed from Contour Positioning System (CPS) using Google Earth software. Symlets wavelet control technique is utilised to separate the high frequency transients from the required load power. After separation of high frequency components, a FC is developed to provide an additional reference power for battery and SC. Then, the high frequency transients along with additional power obtained from FC are allocated to SC and the rest is handled by the battery. Three road slope conditions viz. city tour, downhill and uphill and two drive cycles viz. NYCC and UDDS are applied to examine the capability of proposed EMS. The proposed Fuzzy Symlets Wavelet based controller is observed to improve the battery Ampere hour (Ah) throughput and Root Mean Square (RMS) value of battery current in comparison to only Symlets wavelet based controller for city tour, uphill and downhill journeys. The results indicate the robustness and superiority of the designed Fuzzy Symlets Wavelet based control technique as compared to Symlets Wavelet technique in handling practical conditions and improving vehicle performance.

Comparative analysis of electrical models of lith-ium-ion batteries in electric vehicles

Problem. This article addresses the challenge of enhancing the environmental friendliness and energy efficiency of vehicles. It does so by conducting a comparative analysis and identifying ways to improve the electrical models of lithium-ion batteries used in electric vehicles. The study includes an examination of well-known electrical models of lithium-ion rechargeable batteries, such as the Rint model, the RC model, the Thevenin model, and the PNGV model. It identifies key characteristics of lithium-ion batteries in electric vehicles, including state of charge, mass, actual voltage, energy required for recharging, among others. The study also explores models of battery degradation, focusing on capacity reduction and the increase in active resistance. It substantiates directions for improving electrical models of lithium-ion batteries in electric vehicles by considering changes in capacity, internal resistance, polarization resistance, and both calendar and cyclic degradation. Goal. The aim of this work is to enhance the environmental friendliness and energy efficiency of vehicles through a comparative analysis and by determining ways to improve the electrical models of lithium-ion batteries in electric vehicles. Methodology. Our approach to achieving this goal involves using electrical models of lithium-ion batteries in electric vehicles, which describe various parameters such as state of charge, actual voltage during charge/discharge processes, and energy required for recharging. The study encompasses an investigation into the degradation of electric vehicle batteries, including their use in Vehicle to Grid (V2G) technology. Results. The analysis of electrical models of lithium-ion batteries in electric vehicles, aiming to increase their accuracy, considers the following aspects: changes in internal resistance and polarization resistance; capacity variation; and battery degradation. The change in internal resistance and polarization resistance should be considered based on two factors: the state of charge of the battery and the degree of its degradation. While the first factor is relevant primarily when the battery is deeply discharged (SoC<30%), the second factor must be considered at any state of charge. Capacity changes should be accounted for based on calendar and cyclic degradation. It has been determined that the primary causes of degradation in electric vehicle batteries are calendar aging (service life) and aging due to charge/discharge cycles. Contrarily, it is argued that using Vehicle to Grid (V2G) technology can reduce battery degradation by 10%. Originality. The results of this study provide a comprehensive understanding of the electrical models of lithium-ion batteries in electric vehicles and contribute to the improvement of existing models. Practical value. This research enhances the accuracy of current electrical models of lithium-ion batteries in electric vehicles by considering the variable nature of internal resistance and capacity during vehicle operation. It may be valuable in assessing the residual parameters of electric vehicle batteries during their secondary use, such as in the residential sector for solar energy support. The findings can be recommended to scientific and technical professionals involved in developing energy storage systems for electric vehicles.

Covalently Joined Electrode Architectures for Extreme Fast Charging Li-Ion Batteries

Li-ion batteries are the backbone of all electric vehicles (EVs) in production today [1]. However, they compete poorly against the few-minute refueling time of fossil fuel powered vehicles [2, 3]. To successfully replace fossil fuel powered vehicles, the EV batteries must support charging rates under the 15-minute mark as determined by the eXtreme Fast Charging (XFC) standard defined by the U.S. Department of Energy [4]. When subjected to XFC charging rates, well-known problems of lithium plating and delamination plague graphite anodes due to local potential gradients and binder degradation respectively [5].Our work replaces the traditional polymer binder with conductive titanium carbide interconnects that covalently join graphite particles as well as bond them to the current collector [6]. This new architecture demonstrates ~400% increase in electrical conductivity compared to traditional architectures with polymer binders while maintaining interparticle integrity and improving adhesion. The adhesion and mechanical properties are provided by conductive chemical bonds mitigating delamination as these novel bonds suffer less mechanical and chemical degradation under high current rates than adhesion provided by polymer binders. The improved conductivity was also utilized to form a solid electrolyte interphase (SEI) at rates up to 4C reducing the ionic impedance of the SEI interface significantly [7]. The improved graphite electrodes can sustain 15-minute charge maintaining 80% of the specific capacity of the graphite particles for 800 cycles at commercially relevant loadings. Our studies introduce an effective strategy to engineer Li-ion battery electrode architectures that simultaneously improve electrical and ionic conductivity mitigating lithium plating and delamination under XFC charging rate needed for the mass adoption of EVs. Habib, A.A., S. Motakabber, and M.I. Ibrahimy. A comparative study of electrochemical battery for electric vehicles applications. in 2019 IEEE International Conference on Power, Electrical, and Electronics and Industrial Applications (PEEIACON). 2019. IEEE.Balali, Y. and S. Stegen, Review of energy storage systems for vehicles based on technology, environmental impacts, and costs. Renewable and Sustainable Energy Reviews, 2021. 135: p. 110185.Andwari, A.M., et al., A review of Battery Electric Vehicle technology and readiness levels. Renewable and Sustainable Energy Reviews, 2017. 78: p. 414-430.Dufek, E.J., et al., Developing extreme fast charge battery protocols–A review spanning materials to systems. Journal of Power Sources, 2022: p. 231129.Ahmed, S., et al., Enabling fast charging–A battery technology gap assessment. Journal of Power Sources, 2017. 367: p. 250-262.Rangom, Y., Covalently Joined Carbonaceous and Mettalloid Powders by Carbide-Based Interconnects and Method of Fabrication for High-Performance Electrodes. 2021: United States preliminary patent #63/248,293.Rangom, Y., T.T. Duignan, and X. Zhao, Lithium-ion transport behavior in thin-film graphite electrodes with SEI layers formed at different current densities. ACS Applied Materials & Interfaces, 2021. 13(36): p. 42662-42669. Figure 1

(Invited) Electrolytes for Next-Generation Sodium Metal Batteries

Developing reliable and cost-effective electrical energy storage systems (EESs) for portable electronics, electric vehicles, and grid storage applications is vital. Na-ion batteries are the most promising alternative technology owing to their natural abundance and low sodium cost.[1] Solid-state batteries (SSBs) have garnered extensive attention for their ability to suppress the safety hazards of organic liquid electrolytes by replacing them with solid electrolytes.[2] Among the various solid electrolytes being explored, our group mainly focuses on NASICON (Sodium superionic conductor) type silicate and solid polymer electrolytes. Sodium silicates are a class of materials with composition, NaxMxSixOx (M = rare-earth metals, x = integer (1-10)).[3] They have the advantage of low sintering temperature (~1050 °C) and 3D framework structure containing MO6 octahedra and SiO4 tetrahedra providing facile ionic movement.[4] Solid polymer electrolytes (SPE) are known for their flexibility and electrode compatibility. Highly conductive, filler-free composite solid polymer electrolyte films were prepared using poly(vinylidene fluoride), poly(vinyl pyrrolidone) (PVP), and NaPF6.[5] PVP binder played an essential role in improving Na ion conductivity and excellent plating−stripping performance. This talk will present an overview of these solid electrolytes for next-generation sodium metal batteries.

Development of Electro-Thermal Model for Air Cooling Study of Electric Vehicle Lithium-Ion Battery Module Operating in Indian Conditions and Drive Cycle

Lithium-ion cells have higher energy density at a specific power, making them a primary choice for battery packs in energy storage of modern technology, powering from smartphones to Electric vehicle (EV) and grid-scale energy storage systems. However, their performance, safety and lifespan are temperature sensitive and developing a fail-safe mechanism is considered as a pressing priority. In the present study, a 2D electro-thermal model is developed in MATLAB to characterize the thermal behaviour of cylindrical cells (individual and inline) during discharge. The thermal model solves the transient heat conduction equation with internal heat generation. The model is validated with the available experimental data for a single cell at a constant discharge rate and found to be in good agreement within 0.5°C. The analysis is extended to a battery module with 6 cell-inline configuration and validated. This validated model is used to study the impact of multiple cells (1-10) in inline configuration. For Indian drive cycle analysis, the current profile is estimated based on the drive cycle and its impacts on cell temperature rise in battery module is studied when subjected to variation in monthly average ambient temperature. Battery module maximum temperature rises to 60 °C and Δ T (Tmax - Tmin) across cells is 8.8 °C during summer conditions under natural convection due to multiple drive cycle loading. The battery module temperature can be kept under safe operating limits (Tmax≤ 45 °C, Δ T ≤ 4 °C) with forced convection of 2 m/s and 25 °C. The study aims to provide insights into the thermal behaviour of Lithium-ion cells that can be used to design safe and cost-effective air-cooled thermal management system for battery module.