Electric Vehicles Research Articles

Innovations in Energy Through Nanomaterials Enhancing Solid-State Battery Safety and Efficacy

This paper explores the potential of Si-based nanomaterials to enhance the performance of lithium-ion batteries (LIBs), particularly for electric vehicles (EVs). Traditional graphite anodes limit the energy density and range of EVs, increasing the need to search for alternative materials like silicon, which offers a much higher theoretical specific capacity. However, silicon’s application has been challenged by significant volume changes during cycling, leading to mechanical stress and failure. The use of nanotechnology, especially silicon nanomaterials, offers promising solutions to these challenges. Silicon nanostructures, such as nanowires, exhibit enhanced mechanical properties, allowing them to withstand volumetric changes and maintain high capacity during cycling. This review delves into the chemo-physical properties of silicon, the challenges posed by silicon anodes (SAs), and the recent advancements in silicon nanomaterials. Additionally, it also discusses different approaches to enhancing the performance of Si-based anodes, as well as the difficulties that exist now and the directions that future research in this exciting area is headed.

Hazardous Effects of Battery Waste and Role of the Battery Waste Management Rule 2022 in Enhancing Energy Efficiency

Replacing batteries in present world is challenging because they are extensively utilised in every facet of human existence. These batteries contain a variety of toxic heavy metals, including as cadmium, copper, lead, mercury, nickel, and zinc, all of which pose risks to human health and the environment. Improperly disposing of used batteries in landfills leads to the infiltration of toxic heavy metals and other dangerous compounds into the soil and water over time. India’s long-term development has significant challenges in both reducing CO2 emissions and meeting the energy demands of its large population. This has significantly bolstered the electric vehicle (EV) and renewable energy industries. Battery-based energy storage systems can enhance the management of operational and energy evacuation challenges associated with renewable energy. Consequently, the effective disposal of battery waste is more crucial than battery production. However, it is neglected often, specially in developing and impoverished nations. Three established methods exist for preventing and managing the issues arising from the inappropriate disposal of used batteries. The three R’s are: decrease, replenish, and reuse. This article initially analyses the health and environmental consequences of battery waste, and subsequently highlights the potential of new regulations on battery waste management to effectively handle huge amounts of battery waste and encourage energy conservation.

A Variant of the Growing Neural Gas Algorithm for the Design of an Electric Vehicle Charger Network

The Growing Neural Gas (GNG) algorithm constitutes an incremental neural network model based on the idea of a Self-Organizing Map (SOM), that is, unsupervised learning algorithms that reduce the dimensionality of datasets by locating similar samples close to each other. The design of an electric vehicle charging network is an essential aspect in the transition towards more sustainable and environmentally friendly mobility. The need to design and implement an efficient network that meets the needs of all users motivates us to propose the use of a model based on GNG-type neural networks for the design of the network in a specific geographical area. In this paper, a variant of this iterative neural network algorithm is used with the objective that, from an initial dataset of points in the plane, it calculates a new simplified dataset with the main characteristic that the final set of points maintains the geometric shape and topology of the original set. To demonstrate the capabilities of the algorithm, it is exemplified in a real case, in which the design of an electric vehicle charging network is proposed. This network is built by applying the algorithm, taking as the original set of points the ones formed by the nodes of the gas station network in the geographical area studied. Several tests of running the algorithm for different sizes of the final dataset are performed, showing the differences between the original network and the computationally generated one.

Multi-objective Tuna Swarm Optimization for Coordinated Allocation of Electric Vehicle Charging Stations and Photovoltaic Distributed Generators in Radial Distribution Systems

Multi-objective Tuna Swarm Optimization for Coordinated Allocation of Electric Vehicle Charging Stations and Photovoltaic Distributed Generators in Radial Distribution Systems

A Depreciation Method Based on Perceived Information Asymmetry in the Market for Electric Vehicles in Colombia

A Depreciation Method Based on Perceived Information Asymmetry in the Market for Electric Vehicles in Colombia

An investigation into the major barriers to the adoption of electric vehicles in last-mile deliveries for sustainable transport

An investigation into the major barriers to the adoption of electric vehicles in last-mile deliveries for sustainable transport

Battery Control for Node Capacity Increase for Electric Vehicle Charging Support

Battery Control for Node Capacity Increase for Electric Vehicle Charging Support

Repurposing as a Decommissioning Strategy for Complex Systems: A Systematic Review

Abstract Managing the waste of decommissioned complex systems (e.g., aircraft, wind turbines, etc.) is a growing issue. In this review, we investigate repurposing as a potential solution. The objectives are to identify strategies that can enable repurposing and identify the research gaps hindering those strategies. We analyzed 104 journal articles published in the last decade. We identified four proactive strategies that can be applied before the decommissioning stage and three reactive strategies that can be applied after the decommissioning stage. The proactive strategies are local ecosystem-focused repurposing, modular design, efficient disassembly methods, and component embedded design and health information. The reactive strategies are decision support methods for repurposable component selection, function and context based repurposing opportunities, and business models for repurposing. Six research gaps were identified, hindering the strategies due to the lack of support methods for repurposing, strategy scope limitations, and repurposing opportunity limitations. We identified that two repurposing examples were most commonly studied (wind turbine blades and electric vehicle batteries). Addressing the research gaps through design could uncover new repurposing opportunities. The resulting opportunities could follow similar processes addressed under the two well-researched examples, enabling repurposing as an advantageous and sustainable decommissioning strategy for complex systems. Keywords: circular economy, sustainability, decommissioning, complex systems, repurposing, literature review

Research on the Synchronization Control Strategy of Regenerative Braking of Distributed Drive Electric Vehicles

Research on the Synchronization Control Strategy of Regenerative Braking of Distributed Drive Electric Vehicles

Design of Silicon-Based Anode Materials for High Energy Density Li-Ion Batteries

Compared to other types of batteries, lithium batteries have an extremely high energy density, which means they can store more energy while maintaining a smaller size and weight. The ideal electrode material must have a high lithium ion capacity to store many lithium ions. In addition, the electrode material must have good electronic conductivity to promote lithium ions' rapid entry and exit. However, traditional carbon materials have limited theoretical specific capacity, and the transmission of lithium-ion batteries in traditional materials is limited, resulting in a significant decrease in capacity. Silicon has a theoretical capacity of up to 4200mAh/g, more than ten times the capacity of commercial graphite negative electrodes. In addition, silicon and lithium can undergo alloying reactions to form Li Si alloys, which helps improve the material's specific capacity. This article first summarizes the advantages of electric vehicles and lithium-ion batteries. Then, the benefits and challenges of using silicon-based materials as negative electrodes for lithium-ion batteries were elaborated in detail, and finally, the prospects of silicon-based materials in lithium-ion battery applications were summarized. This article has reference significance in improving the energy density of lithium-ion batteries.

Modeling EV dynamic wireless charging loads and constructing risk constrained operating strategy for associated distribution systems

Dynamic wireless charging (DWC) is an emerging technology that enables the charging of electric vehicles (EVs) while they are in motion. However, previous load modeling methods have not thoroughly explored the detailed analysis of DWC load characteristics. Existing research only considers the single-node supply mode for dynamic wireless charging roads (DWCRs), and the assessment of operational risks arising from the uncertain DWC loads has not been addressed. This paper begins by conducting an equivalent circuit analysis of a typical EV DWC system with multiple segmented coils. We present a more accurate trapezoidal power model for a single EV. Subsequently, we model the aggregated EV DWC load, accounting for traffic flow and headway using Poisson and negative exponential distribution functions, respectively. In the operation process, we consider a multi-node supply mode for DWCRs. To address the inaccuracy of long-term predictions, we propose a rolling optimization model to coordinate DWC and renewables with heterogeneous uncertainties by introducing a risk metric to manage potential uncertain risks. The proposed optimization model is transformed into a mixed-integer second-order cone programming (MISOCP) problem after convex relaxation. Finally, we conduct case studies to validate the proposed methods.

The Energy Transition and Its Macroeconomic Effects

Abstract The energy transition will have profound and varying effects across the globe. We provide an evidence-based qualitative analysis and assess how clean technologies are evolving – mainly wind, solar and electric vehicles – and the challenges and opportunities the transition poses for fossil fuel and metals and minerals producers in the short and long term. We describe the likely macroeconomic consequences of the energy transition and identify the countries that are most positively and negatively exposed. A small number of fossil fuel-producing countries are likely to be severely hit. Meanwhile, a concentrated group of minerals producers should experience large net benefits. Fuel importers – that is, most of the world – should benefit to varying degrees.

A deep reinforcement learning based charging and discharging scheduling strategy for electric vehicles

Grid security is threatened by the uncontrolled access of large-scale electric vehicles (EVs) to the grid. The scheduling problem of EVs charging and discharging is described as a Markov decision process (MDP) to develop an efficient charging and discharging scheduling strategy. Furthermore, a deep reinforcement learning (DRL)-based model-free method is suggested to address such issue. The proposed method aims to enhance EVs charging and discharging profits while reducing drivers' electricity anxiety and ensuring grid security. Drivers' electricity anxiety is described by fuzzy mathematical theory, and analyze the effect of EV current power and remaining charging time on it. Variable electricity pricing is calculated by real-time residential load. A dynamic charging environment is constructed considering the stochasticity of electricity prices, driver’s behavior, and residential load. A soft actor-critic (SAC) framework is used to train the agent, which learns the optimal charging and discharging scheduling strategies by interacting with the dynamic charging environment. Finally, simulation with actual data is used to verify that the suggested approach can reduce drivers' charging costs and electricity anxiety while avoiding transformer overload.

Research on Energy Management Technology of Photovoltaic-FESS-EV Load Microgrid System

This study focuses on the development and implementation of coordinated control and energy management strategies for a photovoltaic–flywheel energy storage system (PV-FESS)-electric vehicle (EV) load microgrid with direct current (DC). A comprehensive PV-FESS microgrid system is constructed, comprising PV power generation, a flywheel energy storage array, and electric vehicle loads. The research delves into the control strategies for each subsystem within the microgrid, investigating both steady-state operations and transitions between different states. A novel energy management strategy, centered on event-driven mode switching, is proposed to ensure the coordinated control and stable operation of the entire system. Based on the simulation results, the PV system cannot cope with the load demand power when it is increased to a maximum of 2800 W, the effectiveness of the individual control strategies, the coordinated control of the subsystems, and the overall energy management approach are confirmed. The main contribution of this research is the development of a coordinated control mechanism that integrates PV generation with FESS and EV loads, ensuring synchronized operation and enhanced stability of the microgrid. This work provides significant insights into optimizing energy distribution and minimizing losses within microgrid systems, thereby advancing the field of energy management in DC microgrids.

Profit enhancement and imbalance cost reduction with solar PV-fuel cell-EV hybrid system in a wind-integrated day-ahead power market

Abstract In a wind-integrated deregulated network, the wind farm must intimate the power-generating capacity bids to the market controller at least one day before it begins operations. The wind farm's bid submissions are based on the estimated wind speed (EWS); nevertheless, slight differences between the real wind speed (RWS) and the EWS will result in penalties or incentives imposed by the Independent System Operator (ISO). This occurrence is known as the power market imbalance cost, and it has a direct influence on the system's profitability. To mitigate this effect, solar PV and fuel cell storage technologies are used with the wind farm to enhance system profit by offsetting the negative effects of the imbalance cost. Here, solar PV and fuel cells are used to function in the required time i.e. operate in the charging mode when the RWS is greater than the EWS and in discharging mode when the EWS is greater than the RWS to balance the power supply in the grid as to fulfill the power bidding conditions. Furthermore, the study focuses on minimizing potential system risks, which have been assessed using several risk assessment tools such as Value-at-Risk (VaR) and Cumulative Value-at-Risk (CVaR). The work was conducted using an IEEE 14 bus test system. Initially, the solar PV-fuel cell system supplies power to meet local needs, and the remaining energy is sent to the grid to maximize the system's profit. Electric vehicles (EVs) have also been incorporated to maximize the system economy in more quantities and to reduce the system risk further as compared to the solar PV-fuel cell operation. Three different optimization methods, i.e. AGTO (Artificial Gorilla Troops Optimizer Algorithm), ABC (Artificial Bee Colony Algorithm), and SQP (Sequential Quadratic Programming), were used in a comparative analysis to assess the effectiveness of the proposed approach.

Plasma Treatment Technologies for GaN Electronics

Nowadays, the third-generation semiconductor led by GaN has brought great changes to the semiconductor industry. Utilizing its characteristics of a wide bandgap, high breakdown Electric field, and high electron mobility, GaN material is widely applied in areas such as 5G communication and electric vehicles to improve energy conservation and reduce emissions. However, with the progress in the development of GaN electronics, surface and interface defects have become a main problem that limits the further promotion of their performance and stability, increasing leakage current and causing degradation in breakdown voltage. Thus, to reduce the damage, Plasma treatment technologies are introduced in the fabrication process of GaN electronics. Up to now, designs like the high-resistivity p-GaN cap Layer, passivating termination, and surface recovery process have been established via Plasma treatment, reaching the goals of normally-off transistors, diodes with high breakdown voltage and high-reliability GaN electronics, etc. In this article, hydrogen, fluorine, oxygen, and nitrogen Plasma treatment technologies will be discussed, and their application in GaN electronics will be reviewed and compared.

Hybrid solar photovoltaic-wind turbine system for on-site hydrogen production: A techno-economic feasibility analysis of hydrogen refueling Station in South Korea's climatic conditions

The South Korean government has an ambitious policy to roll out hydrogen-powered vehicles across the country with 2000 hydrogen refueling stations (HRSs) infrastructure by 2050. However, the country currently lacks sufficient HRS infrastructure. In this context, this study proposes and investigates the technoeconomic feasibility and performance assessment of an optimal hybrid renewable energy system integrated with a vanadium redox flow battery for on-site hydrogen production. The system is designed to refuel a fleet of 20 fuel cell electric vehicles at seven South Korean locations with distinct climates. Based on the typical daily hydrogen and electric load profile of the HRS, the capital expenditure, net present cost, operation expenditure, levelized cost of hydrogen and levelized cost of energy were estimated to be, $5.95 - $13.2 M, $8.93 - $19.4 M, 82,670–202,184 $/yr, 8.77–19.1 $/kg and 2.1–4.58 $kWh, respectively.

Manipulation in the In Situ Growth Design Parameters of Aqueous Zinc‐Based Electrodes for Batteries: The Fundamentals and Perspectives

ABSTRACTPrecise exploitation of the growth of Zn metal anode in a power converter system has re‐emerged as one of the technological interests that have surged globally in the past 5 years, specifically to improve the practical use of deep cycling metal batteries. In this review, the in situ architectures of aqueous Zn metal‐based batteries focusing on the intrinsic geometrical building block and their respective mode of assembly classifying the deposition morphologies are scrutinised and discussed. The fundamental electrochemical kinetic principles and the associated critical issues, especially associated with the metal plague deposition that influences the morphology of deposited Zn, are considered. Also, the growing interest in the interphase system, which has an intense influence in characterising the types of Zn deposition morphology, is included. Consideration of the fundamental crystal features of Zn, endowing the predominant key for its growth assembly, is provided. Last, the review offers perspectives on the current progress of Zn–Air batteries in the application of electric vehicles.

Mathematical Model to Evaluate the Impact of Power Supply Constraint for Electric Vehicles on Transportation Network

AbstractThis paper proposes the UE-based mathematical model to evaluate driver's choice of vehicle types and paths, explicitly considering the supply power constraint in addition to the charging station capacity constraints. Because the flows of EVs in the proposed model are represented in a path-based manner, we apply a column generation-based algorithm to avoid enumerating all of the possible paths. The contributions of this study are that 1) we consider both pre-trip charging and charging during a trip, and that 2) we focus on the difference in the impact of power supply constraints on vehicles that need to charge during a trip and those that do not. The proposed model is applied to a hypothetical network. As a result, we confirmed that 1) while the share of EVs in the middle distance tends to be higher, the share of EVs in the short and long distances tends to be lower, and that 2) in case of inadequate power supply, the share of EVs in the short and middle distances decreases significantly, whereas the share of EVs remains almost unchanged in long OD.

Synthesis of Trisiloxane with the Dioxaborolane Group as a Cathode Film-Forming Electrolyte Additive for High-Temperature LiMn2O4/Li4Ti5O12 Batteries.

LiMn2O4 batteries have been widely applied as various portable electronic devices and electric vehicles owing to the merits of low cost, high operating voltage, excellent rate capability, and environmental friendliness. However, the poor performance at elevated temperatures remains a serious technical challenge in terms of commercial application purposes. A borate-containing trisiloxane compound of TSMBO is designed and synthesized as a cathode film-forming electrolyte additive to improve the electrochemical performances of LiMn2O4/Li4Ti5O12 batteries, especially at high temperatures of 55 °C. Atomic force microscopy measurement confirms that the trisiloxane moiety in TSMBO can construct a cathode electrolyte interface (CEI) with higher mechanical strength and better flatness compared to the disiloxane moiety in the TSMBO analogue with a similar chemical structure. The robust CEI film on the surface of the LiMn2O4 cathode and the inhibited hydrolysis of LiPF6 in the electrolyte significantly suppress the dissolution of Mn from the LiMn2O4 cathode and maintain the structural integrity of the LiMn2O4 lattice over cycling. Thus, the LiMn2O4/Li4Ti5O12 coin cell using the TSMBO-containing electrolyte with an optimized addition level of 0.5 wt % exhibits a higher capacity retention of 49.3% compared with 34.3% for the baseline electrolyte after 300 cycles under 1C rate at 55 °C. The LiMn2O4/Li4Ti5O12 pouch cell tests show excellent high-temperature and cycling performance at 55 °C and a higher capacity retention of 90.4% after 500 cycles at 2C compared to 79.7% for that with the baseline electrolyte after 430 cycles at 2C. This work demonstrates that TSMBO is a promising electrolyte additive for practical use to improve the cycling stability of LiMn2O4/Li4Ti5O12 batteries at elevated temperatures.