Charging Methods Research Articles

Application of wireless energy delivery system in automobile charging

With the popularity of electric vehicles, wireless charging technology has become a key area to address the convenience of charging electric vehicles. The aim of this study is to explore the principles of wireless energy transfer technology and its application in the field of electric vehicles. We first provide a background introduction to the field of electric vehicles, emphasising the importance of wireless charging technology. Subsequently, we delve into the charging and discharging characteristics of power batteries to better understand the need for energy transfer. Then, we carefully selected wireless charging methods suitable for electric vehicles and developed a corresponding wireless charging system architecture. In this paper, we also provide theoretical analyses of two major wireless energy transfer technologies, including electromagnetic coupled wireless energy transfer and resonant wireless energy transfer, as well as exploring the principles of RF wireless energy transfer technology. Finally, we propose an architecture for a static wireless charging system including five modules: pre-processing, transmission, reception, charging control and battery load. The contribution of this study is to provide an in-depth research and a comprehensive theoretical foundation for wireless charging technology in the field of electric vehicles, which helps to improve the charging efficiency and convenience of electric vehicles.

Multi-Objective Optimization Study on the Coupling Mechanism of Underwater Wireless Power Transfer Systems

Magnetically coupled resonant wireless power transfer (MCR-WPT) technology offers longer effective transmission distances and higher efficiency compared to traditional charging methods, making it better suited to the prolonged and efficient operation of autonomous underwater vehicles. This paper first establishes a traditional mathematical model and then refines it while analyzing the variations in the self-inductance and mutual inductance of underwater coils. To further enhance the system’s performance, a multi-objective optimization of the coupling mechanism is conducted. An orthogonal experiment is employed to determine the effects of various influencing factors on the coils’ self-inductance and mutual inductance. Subsequently, an RBF neural network is used to create a regression prediction model based on the results of the orthogonal experiment. The NSGA-II algorithm is then applied for the multi-objective optimization of the coupling mechanism, resulting in a Pareto front solution set. The optimized efficiency is 93.35%, representing an approximately 6% improvement over the original system, with the power density increasing from 1.267×106 W/m3 before optimization to 4.782×106 W/m3 after optimization. Significant enhancement in system performance is achieved.

Experiment-Based Determination of Optimal Parameters in Constant Temperature–Constant Voltage Charging Technique for Lithium-Ion Batteries Using Taguchi Method

Charging methods significantly affect the performance and lifespan of lithium-ion batteries. Investigating charging techniques is crucial for optimizing the charging time, charging efficiency, and cycle life of the battery cells. This study introduces a real-time charging monitoring platform based on LabVIEW, enabling observation of battery parameters such as voltage, current, and temperature. The proposed system allows the precise control of charging parameters via a user-friendly interface. Utilizing a programmable DC power supply, it delivers specific charging waveforms, while data acquisition instruments record temperature changes. Key performance metrics, including charging time, efficiency, and temperature rise, are analyzed. Moreover, this paper conducts in-depth research on the constant temperature–constant voltage (CT-CV) charging technique and applies the Taguchi method to identify key parameter configurations that achieve the objectives of the shortest charging time, highest charging efficiency, and lowest average temperature rise. A comprehensive evaluation compares the optimized CT-CV method with conventional constant current–constant voltage (CC-CV) charging. The results demonstrate a 10.7% reduction in charging time compared to the 1C CC-CV method, indicating the efficacy of CT-CV in shortening charging duration while managing temperature rise.

A fast charge algorithm for Li-ion battery for electric vehicles

The renewable solar energy industry and electric vehicle industry are today seeking for fast battery pack recharging methods to achieve higher performances, and fast energy recovery for energy storage systems (ESS) and for electric vehicles. The charge rate of batteries impacts directly the temperature which in turn impacts the capacity fade, thus it should be kept low to prevent the cells from warming up. This not only limits the charging rate but also puts us on a trade-off, a long lifetime or a fast recharge. In this study, we tried to achieve fast charging using a new charging method that combine two charging methods, without much deterring the capacity of the battery, in order to be able to maintain a long battery lifetime. Charging time of around 82 min was achieved for a 1.8 Ah battery. We compared our findings with the literature with known charging profiles.

Electric Vehicle Battery Pack Charging Time Prediction

The electric vehicle's most crucial component is its battery, which provides the vehicle with power. A key element of electric vehicles (EVs) is the battery management system (BMS), which ensures the safe and efficient functioning of the battery pack. Previous research on electric vehicles has identified some drawbacks, such as lengthy charging times and the need for different charging methods depending on battery capacity and temperature. In the proposed work, the battery's state of charge and remaining capacity will be estimated by measuring the voltage and current with the use of a current sensor and temperature monitor. The novelty of the work lies in its ability to increase the range of electric vehicles. This is achieved through higher energy densities in high-voltage batteries, which allow for longer driving distances between charges. Additionally, faster charging systems can handle higher charging power levels, resulting in quicker charging times. These improvements in performance are made possible by the use of high-voltage batteries, which provide the necessary power for greater peak speeds and improved acceleration. As electric mobility becomes more widespread, the ability to accurately predict charging times based on layout becomes crucial in building user confidence, optimizing energy grid management, and promoting the widespread adoption of electric vehicles.

Analyzing EV User Behavior in Aggregator Smart Charging with ESS and Real-Time Pricing

Amidst increasing global electricity consumption, governments prioritize energy efficiency and electric vehicle (EV) integration into energy markets. This study examines EV aggregator strategies employing smart charging methods, adjusting charging rates based on user preferences. Through simulations in Quito's distribution system, it analyzes actions' effects on aggregator costs and technical conditions, with a focus on demand response (DR) strategies, particularly in residential areas. Exploring EVs' potential as energy storage via vehicle-to-home (V2H) and vehicle-to-grid (V2G) options, the study introduces a collaborative evaluation of dynamic pricing and peak power limiting-based DR strategies, integrating bi-directional EV and energy storage system (ESS) use. It also proposes a novel mixed-integer linear programming (MILP) model for home energy management (HEM), incorporating distributed renewable energy, V2H/V2G capabilities, two-way ESS energy trading, and diverse DR strategies. This comprehensive approach assesses the impact of EV owner preferences and ESS availability on reducing total electricity costs through case studies.

Perspective of material evolution Induced by sinusoidal reflex charging in lithium-ion batteries

BackgroundLithium-ion batteries are globally prominent and extensively employed alternative energy sources with decisive applications. In depth understanding of influences of various charging and discharging cycles on electrode materials and life span of these batteries is critical as cycle-life and safety of lithium-ion batteries are closely related crystallinity of electrode materials. This study is a detailed investigation endeavor in observing the degree of damage to electrode materials under multiple charging and discharging cycles. Methodology: A constant current-sinusoidal reflex charging method (CC-Sinusoidal) was implemented to charge commercial cathode Lithium cobalt oxide (LiCoO2) electrodes and anode graphite electrodes in comparison to the conventional charging method of constant current-constant voltage (CC-CV). After 100, 300, and 500 cycles of charging and discharging, EIS, SEM, XRD, and Raman spectroscopies were used to compare the degree of electrode damage caused by different charging methods. Significant outcomesThe structure of positive LiCoO2 electrode of the battery was observed to be stable, with no significant change in both the charging methods after 500 cycles. The use of CC-CV charging method had caused severe damages to graphite electrode with generation of solid electrolyte interface (SEI) films. The CC-Sinusoidal charging method had maintained the electrode material in a relatively ideal state.

Flexible bidirectional pulse charging regulation achieving long-life lithium-ion batteries

Typical application scenarios, such as vehicle to grid (V2G) and frequency regulation, have imposed significant long-life demands on lithium-ion batteries. Herein, we propose an advanced battery life-extension method employing bidirectional pulse charging (BPC) strategy. Unlike traditional constant current charging methods, BPC strategy not only achieves comparable charging speeds but also facilitates V2G frequency regulation simultaneously. It significantly enhances battery cycle ampere-hour throughput and demonstrates remarkable life extension capabilities. For this interesting conclusion, adopting model identification and postmortem characterization to reveal the life regulation mechanism of BPC: it mitigates battery capacity loss attributed to loss of lithium-ion inventory (LLI) in graphite anodes by intermittently regulating the overall battery voltage and anode potential using a negative charging current. Then, from the perspective of internal side reaction, the life extension mechanism is further revealed as inhibition of solid electrolyte interphase (SEI) and lithium dendrite growth by regulating voltage with a bidirectional pulse current, and a semi-empirical life degradation model combining SEI and lithium dendrite growth is developed for BPC scenarios health management, the model parameters are identified by genetic algorithm with the life simulation exhibiting an accuracy exceeding 99%. This finding indicates that under typical rate conditions, adaptable BPC strategies can extend the service life of LFP battery by approximately 123%. Consequently, the developed advanced BPC strategy offers innovative perspectives and insights for the development of long-life battery applications in the future.

Thermoelectric generator powered timepiece circuit for rechargeable battery operation

The advent of digital technology has revolutionized the way we keep track of time. Digital watches have become an essential part of our daily lives and provide us with accurate and reliable time measurement. However, battery reliability is a long-standing issue in the digital watch industry. Batteries require frequent replacement and are a major source of waste. To solve this problem, a digital watch that runs on a lithium-polymer battery that is recharged by a voltage generated by a thermoelectric generator (TEG) placed on the hand. The proposed model uses TEG1-19913 that generates power in the range of 11.5 W to 14.5 W with hot end basking at 250 °C and a cold end between 30 °C and 50 °C. The TEG voltage is used to charge the lithium polymer battery, eliminating the need for conventional charging methods. The watch is designed to be compact and lightweight, so it can be worn comfortably for extended periods of time. The TEG is integrated into the watch strap and ensures that it is constantly in contact with the skin. The lithium-polymer battery used in the watch is a high-performance rechargeable battery that has high energy density and long life. In summary, the proposed digital watch is an innovative ecological solution to the problems associated with traditional battery-powered watches. The compact and light design of the watch combined with the energy-efficient display makes it a convenient and efficient timekeeping device.

A K-Additive Fuzzy Logic Approach for Optimizing FCS Sizing and Enhanced User Satisfaction

Traditional electric vehicle (EV) charging methods can lead to extended waiting times for users, resulting in decreased travel efficiency and user satisfaction, therefore impacting overall convenience. Moreover, a limited number of charging stations can lead to congestion, exacerbating waiting times, while an excessive number of stations incurs inefficient costs and reduces utilization. While prior research has primarily focused on sizing and allocating charging stations to enhance user performance, there has been comparatively less emphasis on optimizing waiting times and determining the optimal number of charging stations, which is crucial from the EV user’s perspective. This study introduces a K-additive fuzzy logic algorithm to predict the average waiting time and the optimal number of charging stations. The K-additive fuzzy inference system (K-FIS) defines membership functions, expert rules, and a formulation for achieving the optimal solution. The proposed approach integrates uncertain and independent input parameters into weighted control variables, addressing the objective function to optimize EV waiting times and costs represented by the number of charging stations. The scheme utilizes both Type 1 and Type 2 membership functions, offering a detailed comparison. To validate its efficiency, the proposed scheme undergoes a comparative study against related state-of-the-art approaches.

Intelligent, optimal charging with MSSC and PCM protocols for healthy and long life on Li-ion batteries

MSCC is one of the most efficient charging methods with the appropriate advantages over the CC/CV method most commonly used in the Li-ion battery charger market. Our approach to this optimal charging is based on the weak points of CC/CV charging, as well as the battery's reaction after each CC step in testing the new optimal current. Given the needs of the industrial market, which demands fast charging and safety against overcharging and side effects, we decided to develop a fast, optimal charging method aimed first and foremost at guaranteeing a long battery life cycle. Our intelligent charging strategy uses a combination of two charging protocols, MSSC and PCM, each with functionality and a communication link via an STM32 MCU. The principle is to find the optimum charging current for the battery at each stage of charging, depending on its state of health, and then apply the MSSC with a modern, optimized method based on methodological calculations, always respecting the temperature conditions.
 Finally, based on several experimental tests, we were able to prove that the optimal, intelligent method proposed in this article reduces charging time by 16.8% and temperature by 20%, compared with our own intelligent CC/CV+PCM method.

Reimagining E-mobility: A holistic business model for the electric vehicle charging ecosystem

Nowadays business has shifted from product-centric to customer-centric due to the industrial revolution. As a result, the customer’s problem and experience need to be studied and inspected thoroughly to find solutions. Charging stations implementing different charging technologies are reinforced in various topographical locations. Varied charging methods, including AC slow charging, AC fast charging, DC level 1 charging, DC level 2 charging, wireless charging is implemented so far to reduce the charging time. Various business models are established and reported by researchers to support the EV ecosystem. This paper presents one such business model for an electric vehicle (EV) charging system. Design Thinking is one of the problem-solving approaches discussed here. How to tackle the charging issues by implementing different technologies is also discussed. Different phases of Design Thinking are used to find the possible solution to the problems faced by customers. Different groups of customers’ problems and how the proposed solution can fulfil a major group of customers’ needs are discussed here.

Multi-objective optimization for multi-stage constant current charging for Li-ion batteries

Fast charging is a key challenge for the widespread adoption of electric vehicles (EVs), as it can make EVs more convenient and appealing to consumers. Therefore, different charging methods are proposed to enhance the performance of lithium-ion batteries (LIBs). Multi-stage constant current (MSCC) charging can improve LIB's performance in several aspects, including charging time, charged capacity, temperature rise, average temperature rise, and charging energy efficiency. However, achieving a multi-objective performance during LIB charging is challenging. In this paper, the Taguchi method is used to determine the multi-objective optimal (MOO) charging profile for the MSCC charging strategy. The Orthogonal experiments are designed and conducted to find the optimal solutions for each performance parameter for a five-stage constant current (5SCC) charging profile. A comparison is conducted among the performance-based selective charging profiles to validate the optimal charging profile. Furthermore, a comparison is made between the obtained MOO charging profile and the classical equivalent constant current constant voltage (CCCV) method. Experimental results demonstrated that the MOO charging profile reduces the charging time with comparable temperature rise to the CCCV, making it promising for the future alternative efficient EV charging. These findings highlight the effectiveness of the MSCC approach in improving LIB performance.

Optimization of Wireless Charging Techniques in Electric Vehicle Applications through Machine Learning

The integration of electric vehicles (EVs) into mainstream transportation systems is contingent upon the development of efficient and convenient charging technologies. Wireless charging, in particular, presents a promising solution to address the limitations of traditional plug-in charging methods. However, optimizing wireless charging techniques for EVs remains a complex challenge, with factors such as efficiency, alignment, and safety needing careful consideration. This paper explores the potential of leveraging machine learning (ML) algorithms to enhance the performance of wireless charging systems for EVs. By employing ML techniques, such as neural networks and genetic algorithms, in conjunction with real-time data analysis, the aim is to develop adaptive and intelligent charging systems capable of optimizing various parameters to improve efficiency, reliability, and user experience. This research paper discusses the current state of wireless charging technologies, explores the application of machine learning in optimizing these systems, and presents potential avenues for future research and development

Low-Carbon Economy Optimization of Integrated Energy System Considering Electric Vehicles Charging Mode and Multi-Energy Coupling

To realize the multi-energy coupling integrated energy system to meet the multi-class load demand and achieve the goal of low-carbon economic operation, a bi-level optimal configuration method for low-carbon economic operation of multi-energy coupling integrated energy system under different charging modes of electric vehicles is proposed. Firstly, an integrated energy system including cooling-heating-power-gas coupling is established. Then, within the level of intraday scheduling, factors such as ladder carbon trading mechanisms and different charging modes of electric vehicles are considered to achieve the lowest daily scheduling cost. In the configuration planning level, based on the daily operation cost, the equipment capacity is configured with the lowest equipment investment and annual operation costs. The bi-level model is solved by CPLEX solver and the optimal configuration scheme and scheduling results are obtained by mutual iteration. Finally, the impact of different charging methods of electric vehicles on the system economy and low-carbon performance is demonstrated through simulation examples. The results show that the charging method of electric vehicles and the carbon trading mechanism in this paper can significantly reduce carbon emissions and improve the system's operating cost. The proposed configuration approach can well achieve low-carbon economic operation of the multi-energy coupling integrated energy system.

Electric Vehicle Charging Infrastructure, Standards, Types, and Its Impact on Grid: A Review

The growth of EV penetration brings numerous benefits in economic and environmental aspects, but it also presents deployment opportunities and challenges of EV charging stations. The EV owners benefit from lower fuel and operating expenses compared to ICE vehicles because of higher efficiency of electric motors reaching it as high as 60–70%. The electric vehicles are intermittent load to the grid since the number of users charging the electric vehicle at different charging station at different time. Moreover, the increasing EV penetration leads to the increase in load requirement on charging stations and will place a heavier load on the grid, necessitating the exploration of alternative resources. So, it significantly effects on power quality of the distribution grid. This charging requirement needs to be effectively managed to ensure uninterrupted energy supply for charging EVs batteries. By employing a basic charging plan, the estimated system cost per vehicle per year in Denmark is $263. Implementation of smart charging, the system cost decreases to $36 per vehicle per year, resulting in substantial savings of $227 per vehicle per year. Controlled charging methods also effectively reduce system costs by 50% and decrease peak demand. An EV fleet has the potential for cost savings in the power system, amounting to $200–$300 per year per vehicle. The aim of the review is to address the impact on power quality of the distribution grid and study the nature of EV unbalanced loads in order to minimize impact on grid efficiently by managing the resources.

Power Efficiency using Bank Capacitor Regulator on Field Service Shoes with Fast Charge Method

Power efficiency is a key factor in military equipment, including field service boots used by personnel in various field situations that often demand durability and reliable electricity availability. This research focused on improving the power efficiency of field service shoes by using capacitor bank regulators and fast charging methods. By designing and implementing this system, this research aims to optimize the use of power sources, extend battery life, and improve personnel comfort in the field. The method used in this research is the fast charge method. The fast charge method enables faster battery charging, which is important in field situations with limited time availability. The findings of this research show that the capacitor bank regulator can keep the DC output stable despite instability in the input. The total power usage in the circuit is 0.20 W, and the power efficiency is about 60.61%. The research shows the potential of this voltage conversion circuit for efficient applications. Although it has not achieved maximum efficiency, the capacitor bank regulator can maintain output stability even in input voltage instability. This circuit can effectively cope with voltage conversion in various applications with further optimization.

Comparison of EV Fast Charging Protocols and Impact of Sinusoidal Half-Wave Fast Charging Methods on Lithium-Ion Cells

In electric vehicle fast charging systems, it is important to minimize the effect of fast charging on the grid and it is also important to operate the charging system at high efficiencies. In order to achieve these objectives, in this paper, a sinusoidal half-wave DC current charging protocol and a sinusoidal half-wave pulsed current charging protocol are proposed for the fast charging of Li-ion batteries. A detailed procedure is presented for implementing the following proposed methods: (a) a pre-defined half-sine wave current function and (b) a pulsed half-sine wave current method. Unlike the conventional full-wave sinusoidal ripple current charging protocols, the proposed study does not utilize any sinusoidal full-wave ripple. The performance of these new charging methods on Ni-Co-Al-type Li-cells is studied and compared with the existing constant current and positive pulsed current charging protocols, which have been discussed in the existing literature. In addition, the changes in the electrochemical impedance spectrograph of each cell are examined to study the effects of the applied charging methods on the internal resistance of the Li cell. Finally, the test results are presented for 250 life cycles of charging at 2C (C: charging rate) and the degradation in cell capacities are compared among the four different methods for the Ni-Co-Al-type Li cell.

Smartphone Fast Charger Analysis Based on RLC Circuit Transient Process

In today's era, the widespread adoption of mobile terminals, particularly smartphones, has been facilitated by the rapid advancements in information and communication technology. However, a notable drawback of smartphones is their high-power consumption, necessitating faster charging solutions to enhance user convenience. This paper focuses on the RLC circuit of fast chargers. Initially, it introduces the fundamental principles and associated protocols of fast charging technology, elucidating the operation of integrated circuits within fast chargers and highlighting the advantages of fast charging compared to conventional slow charging methods. Moreover, the paper conducts an in-depth analysis of the transient processes within the pivotal series RLC circuit in fast chargers, encompassing zero-input responses and sinusoidal AC excitation responses. The transient processes are categorized into overdamped, critically damped, or underdamped states based on circuit element parameters, with initial conditions and power supply phase determining whether the circuit transitions directly into a steady-state process when stimulated by sinusoidal AC. This research contributes to a deeper understanding of the RLC circuit within smartphone fast chargers and serves as a valuable reference for advancing the development of fast charging solutions.

Evaluation of hydrogen embrittlement in ODS-Cu, Cu–Cr–Zr, and Cu–Cr alloys using slow strain rate technique test

Precipitation-hardened Cu–Cr–Zr alloy is proposed as a heat sink material for various components of the ITER owing to its high strength, high conductivity, and superior resistance against neutron irradiation. Oxide-dispersion-strengthened copper (ODS-Cu) was selected as the candidate material. Hydrogen embrittlement of Cu–Cr–Zr, Cu–Cr, and ODS-Cu (GlidCop® CuAl60) alloys was evaluated using the slow strain rate technique (SSRT) in 0.1 M sodium sulfate (Na2SO4) solutions under cathodic hydrogen charging or after D2 gas exposure. Thermal desorption spectroscopy (TDS) measurements were performed to estimate the differences in the hydrogen-trapping sites using hydrogen charging methods. According to the TDS results, the quantity of hydrogen retained in ODS-Cu exceeded that in the other alloys by an order of magnitude because of hydrogen trapping at the grain boundaries and the particle/matrix interface. Cu–Cr–Zr alloys tend to trap more hydrogen than Cu–Cr alloys because of the addition of Zr. As a result of the SSRT, no hydrogen embrittlement was observed in any alloy, regardless of the hydrogen charging method. All alloys exhibited excellent hydrogen embrittlement resistance under the conditions adopted in this study.