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Summary: The magnetic couplers play an important role in electric vehicle (EV) wireless power transfer (WPT) systems. Conversational coupling structures are mainly based on unipolar, bipolar, and quadrupole coils, and the interoperability among them cannot be achieved. To solve the interoperability problem in the coupling structure, a novel bipolar coil structure is proposed in this paper. Energy transfer with unipolar and bipolar coils is achieved by interconnecting unipolar and bipolar types crosswise in the same plane and combining them with the corresponding topologies. They are connected in series on the dc side. An experimental prototype is built to verify the interoperability performance of the proposed novel bipolar coil structure. The proposed novel bipolar coil structure can be compatible with unipolar, bipolar, and quadrupole coils and achieve a maximum dc‐dc efficiency of more than 85%. [ABSTRACT FROM AUTHOR]

ABSTRACT Bi‐directional power exchange between the lithium‐ion battery and the grid can be achieved using vehicle‐to‐grid (V2G) technology. Bi‐directional battery chargers for V2G applications present opportunities and challenges, as the rapid growth of active components can compromise system reliability. This paper proposes an adaptive control mechanism for a three‐phase bi‐directional battery charging system to address this. The system integrates a bi‐directional active front‐end (AFE) converter (BAC) with an interleaved buck‐boost converter to enable adaptive constant current/constant voltage (CC/CV) mode operation and bi‐directional power flow. A feedforward decoupled current controller and pulse width modulation scheme optimize battery charging, while an optimized voltage‐oriented control (OVOC) model‐based controller ensures stable bi‐directional power exchange between the electric vehicle (EV) and the utility. Experimental results validate the effectiveness of the proposed approach, with findings demonstrating low total harmonic distortion (THD), unity power factor (UPF), and minimal DC voltage ripple. A 12.5 kW prototype further confirms the practical viability of the design, offering a promising solution for enhanced reliability and performance in V2G battery chargers. [ABSTRACT FROM AUTHOR]

Future inductive charging ports must possess the capability to charge any electric vehicle (EV), irrespective of the specific coil architecture it is equipped with. This study examines the misalignment scenarios of the global circular pad at transmitter side (CirPT) with circular receiver pad (CirPR) and a double-D receiver pad (DDPR). The CirPT, CirPR, and DDPR configurations for WPT3 (11.1 kW) with ground clearance meeting the Z2-class specifications and above ground surface installation are built by utilizing circuit analysis and 3D-finite element simulations, as outlined by the Society of Automotive Engineering (SAE) J2954 standard. The simulated designs are employed to determine the frequency (f) and the compensating network components (CNCs) required to achieve optimal power transfer efficiency while maintaining nominal power levels. The analysis of misalignment scenarios involves examining various performance factors, including coupling coefficient (k), transmission power (Po), efficiency (η), and leakage electromagnetic fields (EMFs). These factors are assessed under conditions of ideal alignment, as well as various linear and angular misalignments within the inductive charging system. The results demonstrate that both the CirPR and DDPR configurations can successfully interface with the CirPT to provide the required Po to the EV battery with commendable efficiency. In perfect alignment, the efficiencies are 95.10% for the CirPT-CirPR model and 91.60% for the CirPT-DDPR model. In maximum misalignment, the efficiencies are 87.10% for the CirPT-CirPR model and 89.50% for the CirPT-DDPR model, all exceeding the acceptable threshold of 80%. [ABSTRACT FROM AUTHOR]

The rapid adoption of electric vehicles (EVs) has created a pressing need for efficient charging infrastructure. but challenges such as inconsistent demand and poor placement remain. An effective distribution of sufficient EV charging stations (CSs) is one of the major obstacles preventing the market penetration of EVs and the realization of a sustainable transportation system in urban areas. In this paper, a new machine learning technique is proposed in order to optimize the placement of EV charging stations (EVCSs) in metropolitan areas based on an energy consumption prediction model. A dataset from 148,136 charging transactions in Boulder, Colorado, is used with the proposed model. Key algorithms such as KNeighborsRegressor and RandomForestRegressor were incorporated to solve the placement problem. The analysis revealed significant demand fluctuations during peak commute hours, with the KNeighborsRegressor model demonstrating superior prediction accuracy. These insights can guide more effective infrastructure planning and resource allocation, ultimately enhancing the efficiency and user experience of EV charging networks and promoting sustainable urban transportation. [ABSTRACT FROM AUTHOR]

The motor characteristics control method using the winding changeover technique can improve the matching ratio between the most frequent operating point of electric vehicle (EV) and the motor's high-efficiency operating point, thereby enhancing the overall average efficiency of the drive system. This technology reduces back electromotive force and winding resistance by adjusting the effective number of motor winding turns according to the EV's operating speed, ultimately improving the average efficiency. In this paper, we propose a winding changeover circuit and control method that maximizes the average efficiency in the main driving regions to extend the driving range per charge and improve the fuel efficiency of EVs. The proposed circuit is constructed using thyristor switching devices, offering the advantage of relatively lower overall system losses compared to conventional circuits. Due to the characteristics of the thyristor switching devices used in the proposed circuit, seamless winding changeover is possible during motor operation. Additionally, no extra snubber circuits are required, and the relatively low switch losses suggest the potential for improved efficiency and lightweight design in EV drive systems. To verify the proposed winding changeover circuit and control scheme, experiments were conducted using a dynamometer with an 80 kW permanent magnet motor, inverter, and the developed prototype of the winding changeover circuit. [ABSTRACT FROM AUTHOR]

In the United States, new laws and regulations in several states require increasing percentages of vehicles produced in the future to be zero emission to address climate-related issues. Manufacturers are producing more Electric Vehicles (EVs), but potential customers are hesitant to adopt EVs due to range anxiety. Log truck owners are particularly hesitant to invest in electric log trucks (ELTs) due to forest harvest operations remote nature. However, regenerative braking utilizing gravitational potential energy provides the opportunity to increase the range of ELTs. This manuscript presents the workflow for calculating and mapping energy transportation cost on an ELT using a GIS-enabled tool and demonstrates the tool's applicability through a case study. The study area, the McDonald Dunn Research Forest, included 5,607 ha of forest stands partitioned into 357 harvest polygons averaging 15.7 ha, 326 harvest landings and 295 km of road. Using remotely sensed data from the study site, the tool digitalizes the wood supply chain and optimizes routing based on minimum energy expenditure, providing results such as trip energy cost, distance, and time. The results show the tools forest operations planning potential, applicability as a GIS navigation system, and provides EV buyers with a tool to make informed decisions when investing in technology that could combat climate-related issues. EV adoption will reduce reliance on fossil fuels and potentially ameliorate other environmental problems. [ABSTRACT FROM AUTHOR]

Electric Vehicles (EVs) are anticipated to dominate passenger car transportation, playing a pivotal role in advancing sustainable mobility. However, with the increasing enthusiasm for EVs, impediments endure within the realm of power transmission. This is especially evident in addressing challenges related to minimizing torque ripple and implementing advanced control techniques in traction for high-performance and efficient operation of EVs. Numerous control algorithms for motor drives have been developed in the recent past but face challenges in attaining effective control under varying drive cycles of EVs. To tackle these challenges, motor drive control algorithms integrate various control techniques, including field orientation control, model predictive control, intelligent control, etc. This paper proposes an innovative online-tuned MPCC algorithm based on the adaptive neuro-fuzzy inference system (ANFIS). The traditional proportional–integral (PI) controller is replaced with an adapted ANFIS algorithm, and the tuning of ANFIS parameters is achieved by leveraging the error between the reference and adjustable models through a hybrid training algorithm. The proposed novel control technique improves the dynamic speed response of permanent magnet synchronous motor drives EVs. This improvement is realized by replacing the PI-HCC controller with an ANFIS controller coupled with MPCC. A laboratory prototype of the proposed control technique for EVs has been developed, and a comparative analysis of ANFIS-MPCC techniques with other known control techniques has been presented. This paper also demonstrates the importance of choosing optimal motor control techniques for torque ripple minimization and improving the overall performance of EVs. [ABSTRACT FROM AUTHOR]

In the context of modern power systems, the reliance on a single-time-of-use electricity pricing model presents challenges in managing electric vehicle (EV) charging in a way that can effectively accommodate the variable supply and demand patterns, particularly in the presence of wind power generation. This often results in undesirable peak–valley differences in microgrid load profiles. To address this challenge, this paper introduces an innovative approach that combines time-of-use electricity pricing with the flexible energy storage capabilities of electric vehicles. By dynamically adjusting the time-of-use electricity prices and implementing a tiered carbon pricing system, this paper presents a comprehensive strategy for formulating optimized charging and discharging plans that leverage the inherent flexibility of electric vehicles. This approach aims to mitigate the fluctuations in the microgrid load and enhance the overall grid stability. The proposed strategy was simulated and compared with the no-incentive and single-incentive strategies. The results indicate that the load peak-to-trough difference was reduced by 30.1% and 18.6%, respectively, verifying its effectiveness and superiority. Additionally, the increase in user income and the reduction in carbon emissions verify the need for the development of EVs in tandem with clean energy for environmental benefits. [ABSTRACT FROM AUTHOR]

This research assesses the feasibility of utilizing alternative energy sources for electric vehicle (EV) charging facilities in four cities representing provinces in Indonesia. The analysis employed HOMER Pro software to optimize PV and wind turbine systems to develop the most efficient hybrid system. This PV-wind hybrid system is considered more environmentally friendly than conventional systems due to its reduced fossil fuel use and increased renewable energy. The data interpretation results indicate that the optimal model for developing the Hybrid PV-Wind system is the best choice and operates effectively in Yogyakarta, with a wind contribution of 32.33% and solar energy accounting for 9.99%. This benefit is mainly attributable to Yogyakarta's favorable geographical and climatic conditions for realizing optimal wind power and solar radiation potential. Out of the four cities studied, the hybrid PV-wind system in Yogyakarta was the most effective regarding renewable energy contribution and financial viability. The hybrid PV-Wind system indeed has a high initial capital requirement. However, operational and maintenance costs are more favorable in the long run than separately installed systems (wind-only or solar-only). This contributes to the long-term efficiency goals in operational costs. Yogyakarta reported the highest Internal Rate of Return (IRR) and Return on Investment (ROI), which signifies a reasonable prospect of higher and faster returns on investment. Moreover, the most remarkable annual energy output was recorded in Yogyakarta, which registered a total production of 987,155 kWh per year and the least LCOE at IDR 1,245/kWh. Nonetheless, the contribution of renewable energy sources in this scheme is still quite limited, around 27% to 42% of the total annual energy requirements. Hence, there still exists a need to buy energy from the conventional grid for the complete requirements of EV charging stations. Oehler et al. highlight the need to deploy renewable energy-based systems in EV charging stations' operation for sustainability and efficiency. In addition, the results of this study also reinforce the urgency of the transition towards a more widespread utilization of renewable energy in the transport sector. [ABSTRACT FROM AUTHOR]

In this paper, simulation, and performance comparison of a switched reluctance motor (SRM) for a classical asymmetric bridge converter and an improved reduced switch converter topology are provided. In an improved converter, switches are shared by adjacent phases, and one diode is connected in series with each phase winding to avoid reversal of current. Double-phase magnetization is adopted for the analysis of both converter topologies. The performance of both converter topologies are demonstrated using a proportional plus integral (PI) based hysteresis current controller and dynamic load on a 7.5 kW, 8/6 pole, 4-phase SRM. Improved reduced switch converter topology uses half the number of switches as compared to the classical asymmetric bridge converter. According to the simulation results, an improved converter offers superior starting and average torque with less speed settling time. An improved converter reduces the most serious problem of torque ripple in SRM by 50% compared to the classical topology. The reduced switches lower the winding losses and improve the efficiency of the drive system. [ABSTRACT FROM AUTHOR]

Abstract Future inductive charging ports must possess the capability to charge any electric vehicle (EV), irrespective of the specific coil architecture it is equipped with. This study examines the misalignment scenarios of the global circular pad at transmitter side (CirPT) with circular receiver pad (CirPR) and a double-D receiver pad (DDPR). The CirPT, CirPR, and DDPR configurations for WPT3 (11.1 kW) with ground clearance meeting the Z2-class specifications and above ground surface installation are built by utilizing circuit analysis and 3D-finite element simulations, as outlined by the Society of Automotive Engineering (SAE) J2954 standard. The simulated designs are employed to determine the frequency (f) and the compensating network components (CNCs) required to achieve optimal power transfer efficiency while maintaining nominal power levels. The analysis of misalignment scenarios involves examining various performance factors, including coupling coefficient (k), transmission power (P o ), efficiency (η), and leakage electromagnetic fields (EMFs). These factors are assessed under conditions of ideal alignment, as well as various linear and angular misalignments within the inductive charging system. The results demonstrate that both the CirPR and DDPR configurations can successfully interface with the CirPT to provide the required P o to the EV battery with commendable efficiency. In perfect alignment, the efficiencies are 95.10% for the CirPT-CirPR model and 91.60% for the CirPT-DDPR model. In maximum misalignment, the efficiencies are 87.10% for the CirPT-CirPR model and 89.50% for the CirPT-DDPR model, all exceeding the acceptable threshold of 80%.

High-performance supercars using Li-ion batteries necessitate thicker aluminium busbars with thin steel joints. However, joining these materials often leads to overheating resulting in brittle intermetallic compounds (IMCs), reduced weld quality, and higher electrical resistance. This study evaluated, laser wobble welding of a nickel-plated Al busbar of 0.9 mm thickness with a 0.3 mm thin 21700 cell nickel-plated steel terminal. An optimised joint using the wobbling method is implemented for the direct application to battery packs, satisfying the current carrying capacity with minimal electrical resistance and enhanced weld quality was generated. Elemental and microhardness analysis revealed the mechanism of IMC formation and observed that the brittle and therefore detrimental Fe2Al5 IMC predominantly forms near the protruding interface between Al-Fe solid solutions.

In this paper, simulation, and performance comparison of a switched reluctance motor (SRM) for a classical asymmetric bridge converter and an improved reduced switch converter topology are provided. In an improved converter, switches are shared by adjacent phases, and one diode is connected in series with each phase winding to avoid reversal of current. Double-phase magnetization is adopted for the analysis of both converter topologies. The performance of both converter topologies are demonstrated using a proportional plus integral (PI) based hysteresis current controller and dynamic load on a 7.5 kW, 8/6 pole, 4- phase SRM. Improved reduced switch converter topology uses half the number of switches as compared to the classical asymmetric bridge converter. According to the simulation results, an improved converter offers superior starting and average torque with less speed settling time. An improved converter reduces the most serious problem of torque ripple in SRM by 50% compared to the classical topology. The reduced switches lower the winding losses and improve the efficiency of the drive system.

Prior research studies sustainable supply chain (SC) management for the electric vehicle (EV) industry in which SC members have sufficient funds. However, many EV firms always face the problems of financial constraints, which lead to the importance and urgency for the research of sustainable SC finance. To address this new problem, we consider the members of the electric vehicle supply chain (EVSC) can be risk averse because of the financial risks from uncertain demands. The EV retailer has limited liability and can obtain loans through a bank or an EV manufacturer. We first address a base model in which the EV manufacturer invests in the green research and development (R&D) effort and investigate operational decisions and sustainable SC finance strategies for the EVSC and members. Using the real data from a top-four EV manufacturer in the world, we do a case study to verify the outcomes of the base model and find that the EVSC and members can derive higher profits with MF strategy for the most cases. Furthermore, we extend the base model to consider government subsidies and the EV retailer's service levels, and find that government subsidies and the EV retailer's service are beneficial to the EVSC. [ABSTRACT FROM AUTHOR]

The study investigates the impact of electric vehicle (EV) technology on Indonesia's automotive industry and economy, emphasizing EVs' role in emission reduction. Factors affecting EV uptake, including purchasing behavior and environmental awareness, are analyzed, contributing to the theory of planned behavior. Data from 136 respondents were collected through surveys, revealing positive correlations between environmental awareness, knowledge, attitude, and purchase intent. Price affordability emerges as an intervening variable. The study offers insights for the gradual integration of EVs into Indonesia's automotive sector, highlighting initiatives by both manufacturers and the government, such as introducing EV options and implementing regulations related to energy, charging infrastructure, and taxation. This research underscores the importance of addressing consumer perceptions and market dynamics to facilitate the transition toward electric mobility in Indonesia.

The rapid development of electric vehicles (EVs) and unmanned aerial vehicles (UAVs) provides new ways for personnel search and material distribution during emergency periods. This paper proposes an EV-UAV joint rescue system, in which the UAVs use the EVs as charging and maintenance base stations to provide various services for the objects to be rescued, and the EVs can use distributed generations to obtain diversified electricity supply, which improves the adaptability and endurance level of the system in emergencies. The coordinated scheduling model of the EV-UAV system is established in the mixed-integer linear programming (MILP) formulation, which considers factors including electricity consumption, electricity replenishment, loading capacity, distribution route, and distribution time window of the EVs and the UAVs. Case studies verify the validity of the model proposed, compare the EV-UAV and ground vehicle (GV)-UAV rescue systems, and illustrate the technical characteristics and application potential of the EV-UAV system in emergency assistance.

Wireless charging of electric vehicles (EVs) poses issues like power ripples that reduce battery lifetime. This study proposes a four-quadrant DC/DC chopper controlled by an adaptive neuro-fuzzy controller (ANFIS) for wireless EV charging. The system is modeled and simulated in Matlab/Simulink. Compared to a PI-PSO controller, the proposed ANFIS control reduced the ripple factor in power over half to about 0.7% and optimized stability and efficiency. Though settling time increased, the difference in rise time was negligible. Future work will improve dynamic response. The ANFIS-controlled DC/DC chopper enhances wireless charging performance with minimal power ripples for safe, efficient EV power transfer.

The escalating necessity for more efficient and defect-free joining of 'ultra-thin foil collectors-to-tabs' in electric vehicle (EV) Li-ion pouch cells motivates this study. The prevalent ultrasonic welding (USW) method for these joint types, faces limitations such as design constraints and access requirements, laser welding (LW) emerges as a promising alternative offering flexibility, one-side access and faster speeds with efficient heat input. This study aims to investigate the feasibility of LW as a viable alternative to USW for joining current collectors-to-tab joints. It compares the mechanical, metallurgical, electrical and thermal analysis of the joints to evaluate both welding techniques for joint defects. The comparison of solid-state material mixing during USW and the intermixing of aluminium (Al) and copper (Cu) during fusion LW using EDX analysis presents interesting observations in the study. The USW generates a thin transition layer with intermetallic compounds (IMCs) attributed to the diffusion of Cu into the Al matrix during joining, which is comparatively lower as in the case of LW with higher material mixing with brittle IMCs like Al2Cu and Al4Cu9. However, the joint strength of LW is comparatively lower than the USW joint attributed to the reduced fusion zone area. Furthermore, from the electrical contact resistance and the joint temperature analysis, it was found that the resistance and temperature vary by as much as 13% and 6%, respectively, for the 50 A and 75 A passing currents when the USW is replaced with the LW process. [ABSTRACT FROM AUTHOR]

This article delves into the potential of electric vehicle (EV) adoption in Central Jakarta, a densely populated area grappling with significant urban and transportation challenges. Trams are an environmentally friendly mode of transport that is environmentally friendly, efficient, comfortable, accessibility, and enhances the aesthetic value of the city. Trams do not produce exhaust emissions, so they can help reduce air pollution in big cities. This is important for improving air quality and public health. The research variables include cost implications, environmental impact, and other relevant aspects of transitioning from fuel-based cars and motorcycles to electric vehicles. The research extensively explores various reputable sources such as papers, journals, and research studies relevant to the chosen research variables, enhancing the credibility of the findings. The study reveals that while the adoption of EVs presents several opportunities, such as reducing traffic congestion and environmental pollution, it also poses significant challenges. These include high costs of EVs, lack of charging infrastructure, and consumers' unfamiliarity with the technology. The research suggests that addressing these challenges requires an integrated and comprehensive solution, including policy measures such as increasing public charging infrastructure, transforming tax schemes, and providing incentives for EV users. This research contributes to the ongoing discourse on sustainable urban transportation, providing valuable insights for policymakers, academia, and the local community in Jakarta and beyond. [ABSTRACT FROM AUTHOR]

This paper presents the design and optimization of a bidirectional Dual Active Bridge (DAB) converter for electric vehicle battery charging applications, encompassing both heavy and light electric vehicles. The core of this study is a 5.6 kW DAB converter that can seamlessly transition between 3.7 kW and 11.2 kW power outputs to accommodate different vehicle requirements without the need for circuit component changes. This flexibility is achieved through the novel integration of interleaved and parallel operation capabilities, allowing for efficient operation across a broad power range. Key innovations include the design of a high-frequency transformer with dual secondary outputs to facilitate power transfer at high currents up to 30 A, an optimized thermal design, and minimized stress on the circuit board. The use of next-generation power semiconductors and low-loss magnetic circuit elements has resulted in an optimized single-stage bidirectional converter design that showcases enhanced efficiency and competitiveness in the field. Furthermore, the converter's design enables easy reconfiguration to meet the desired power output, vehicle type, and application needs, making it adaptable for future applications such as Vehicle-to-Grid (V2G) systems. The combination of these features—versatility in power output, efficient high-current transfer, innovative use of power semiconductors, and adaptability for future technologies—positions this DAB converter as a significant advancement in electric vehicle charging technology, offering a scalable solution to meet the evolving demands of electric mobility and renewable energy integration. [ABSTRACT FROM AUTHOR]

In this paper, an enhanced indirect instantaneous‐torque‐control is proposed based on the torque sharing function approach of switched reluctance motor drives for electric vehicles by employing the jelly fish search. The major goal is to attain vehicle desires that include minimal torque ripple, maximum torque per ampere (MTPA), and huge performance and extend speed limit. First, a simplest analytic design is developed a determine more proficient turn‐on angle for the torque product. Second, an altered torque sharing function (TSF) is used for compensating the faults of torque tracking. The proposed technique is calculated to represent an accurate switched reluctance motor and its magnetized features. They have worked to create the machine model and execute the necessary transmits. The torque fault is evaluated and compensated inside the torque sharing function. The adapting TSF is compensates for the torque fault with receiving the phase because it is the minimal flux rate connecting variation. Finally, the jellyfish search technique is accepted to determine the optimal control parameters. The proposed strategies are done in MATLAB and its performance is contrasted with different existing strategies. According to the simulation result, the proposed strategy‐based accuracy is 94.2% at 50 iteration and 80% at 100th iteration which is higher than the existing methods. From this analyses, it proved that the proposed technique gives superior performance to existing one. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Electric Vehicles (EVs) are becoming more and more popular in our daily life, which replaces traditional fuel vehicles to reduce carbon emissions and protect the environment. EVs need to be charged, but the number of charging piles in a Charging Station (CS) is limited, and charging is usually more time-consuming than fueling. According to this scenario, we propose a secure and efficient charging scheduling system based on a Directed Acyclic Graph (DAG)-blockchain and double-auction mechanism. In a smart area, it attempts to assign EVs to the available CSs in the light of their submitted charging requests and status information. First, we design a lightweight charging scheduling framework that integrates DAG-blockchain and modern cryptography technology to ensure security and scalability during performing scheduling and completing tradings. In this process, a constrained multi-item double-auction problem is formulated because of the limited charging resources in a CS, which motivates EVs and CSs in this area to participate in the market based on their preferences and statuses. Due to this constraint, our problem is more complicated and harder to achieve truthfulness as well as system efficiency compared to the existing double-auction model. To adapt to it, we propose two algorithms, namely, Truthful Mechanism for Charging (TMC) and Efficient Mechanism for Charging (EMC), to determine an assignment between EVs and CSs and pricing strategies. Then, both theoretical analysis and numerical simulations show the correctness and effectiveness of our proposed algorithms. [ABSTRACT FROM AUTHOR]

The power quality (PQ) variations due to the introduction of electric vehicles (EVs) and Electric Vehicle Charging Stations (EVCS) into the power system network is the foremost limitation which is holding back the push for a complete overhaul of fossil fuel-based internal combustion (IC) engine vehicles by EVs. With the emergence of EVs into the mainstream in the automobile sector, this research article proposes a system wherein distributed energy resources (DERs) like Fuel-Cells (FCs) are integrated to grid in order to supply for the additional power demand created by the EVs such that the current injected from FC compensates the grid current harmonics maintain the grid current THD ≤ 5% as per IEEE519 standards. A Particle Swarm Optimized (PSO) based PI current controller and a Fuzzy-logic-based controller are proposed for a grid connected fuel cell so as to mitigate the grid current deterioration caused due to the presence of existing nonlinear loads as well as EVCS. In addition, the parameters like grid voltage distortion and frequency variance are considered simultaneously to ascertain the capability of proposed controllers. This work is carried out in the MATLAB/SIMULINK environment. [ABSTRACT FROM AUTHOR]

The rise of electric vehicles (EVs) has initiated a significant transformation in both the transportation and energy sectors. With the increasing adoption of EVs, their interaction with the power grid is becoming more critical. A notable and innovative concept emerging in this context is Vehicle-to-Home (V2H) operations, which utilize the battery storage capabilities of EVs to meet residential energy demands. Our research provides a way of economically evaluating V2H operations under various environmental conditions including pricing, seasonal differences, and EV operations. The proposed model aids in understanding the optimal operation of V2H and identifying the factors that encourage its adoption. Furthermore, optimizing V2H use can promote renewable energy utilization, providing an additional solution to address its intermittent nature. The findings highlight the potential of V2H operations to contribute to more economically efficient energy systems, provided that supportive policies and adaptive technologies are in place. [ABSTRACT FROM AUTHOR]

In terms of electric vehicle architectures, the drivetrain offers unprecedented freedom, but it also creates new obstacles in terms of achieving all needs. The architecture of electric vehicles is simplified and adjustable at the component level because they don't have a combustion engine or fuel tank, only an electric motor and a battery. Implementing safe zones within electric vehicles (EVs) to accommodate battery packs necessitates significant adjustments to ensure the secure integration of the battery. A Battery EV, also known as a pure EV, solely relies on rechargeable battery packs as its source of energy, without any additional propulsion system. The Battery Management System (BMS) plays a significant role in maintaining the safety of electric vehicles by controlling the electronics of rechargeable batteries, whether they are individual cells or battery packs. The BMS plays crucial role in protecting both the user and the battery by monitoring and maintaining the cell's operation within safe limits. This research paper focuses on the control of solar‐powered charging for lithium‐ion batteries. An optimized FOPID controller is utilized to maximize power extraction from PV array and efficiently charge the battery. A hybrid optimization model is employed to optimize the gain parameters of the FOPID controller. [ABSTRACT FROM AUTHOR]

Copyright of Automotive Digest is the property of Automotive Digest Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The growth of electric vehicles (EVs) has prompted the need to enhance the technology of lithium-ion batteries (LIBs) in order to improve their response when subjected to external factors that can alter their performance, thereby affecting their safety and efficiency. Mechanical abuse has been considered one of the major sources of LIB failure due to the changes it provokes in the structural integrity of cells. Therefore, this article aims to review the main factors that aggravate the effects of mechanical loading based on the results of different laboratory tests that subjected LIBs to abusive testing. The results of different cell types tested under different mechanical loadings have been gathered in order to assess the changes in LIB properties and the main mechanisms responsible for their failure and permanent damage. The main consequences of mechanical abuse are the increase in LIB degradation and the formation of events such as internal short circuits (ISCs) and thermal runways (TRs). Then, a set of standards and regulations that evaluate the LIB under mechanical abuse conditions are also reviewed. [ABSTRACT FROM AUTHOR]

Electric vehicle charging stations (EVCS) that are based on DC microgrids are presented in this research. The system comprises a solar photovoltaic system (SPVS), storage battery (SB), electric vehicle (EV) and grid. The adaptive interaction artificial neural network (AI-ANN)-based vehicle to grid (V2G) and grid to vehicle (G2V) power management controller (PMC) is suggested for DC microgrid based EVCS. This EVCS is suitable for the residential building and offices where EV may be parked. This EVCS provides the facility to manage the power of the building in addition to charge the EVIt has two different modes of operation. The first mode uses the EV as a power source. In the second mode, the EV functions as a load. This controller is developed to acquire electrical power from the solar photovoltaic system (SPVS), storage battery, EV and grid respectively. If the solar photovoltaic system (SPVS) and storage battery power are insufficient to meet the demand, power is extracted from electric vehicle (V2G). If the solar photovoltaic system (SPVS), storage battery and EV are not sufficient to meet up demand, then deficit power is obtained from the grid (G2V). ANN based power management controller (PMC) Also provides a consistent DC bus voltage and reduces overshoot from 9.6 % to 0 %., settling time from 1.18 sec. to 0.52 sec. and rise time from 0.27 sec. to 0.25 sec. of DC bus voltage compared to conventional controller. The suggested power management controller tested for two different modes i.e., V2G and G2V using MATLAB Simulink software.