Fast Charging Technology Research Articles

Recent status, key strategies and challenging perspectives of fast-charging graphite anodes for lithium-ion batteries

The fast-charging technology of graphite anode has a great significance for developing electric vehicle. This review summarizes the current advancements and challenging perspectives of graphite anode for achieving fast-charging lithium-ion batteries.

Transient thermal analysis of the thermal management of high-power fast charging module using phase change material

Fast charging technologies are now being developed, and the challenge of an efficient heat management solution for the charging module is aggravated. The transient thermal analysis model is firstly given to evaluate the novel thermal management system for the high power fast charging pile. Results show that adding the PCM into the thermal management system limits its thermal management performance in larger air convective coefficient and higher ambient temperature. However, applying the PCM exhibit a beneficial effect in the various liquid convective coefficients and heat generation powers. Increasing the liquid convective coefficient from 1098 W/(m2 K) to 2557 W/(m2 K), a highest temperature reduction of 27.01 °C is found. Adding the PCM to the thermal management system gives a maximum temperature reduction of 4.88 °C as the heat generation power increases from 60 W to 120 W, and the highest temperature of the charging module reduces from 100.05 °C to 94.29 °C with a decrease in maximum temperature of 5.76 °C as the shell emissivity increases from 0.1 to 0.9. A suitable PCM melting temperature is effective in controlling the temperature range of the charging module. These results will provide guidelines for the thermal management design of charging module, which is crucial for advancing the electric vehicles (EVs) adoption.

Experimental and modeling investigation on thermal risk evaluation of tabs for pouch-type lithium-ion battery and the relevant heat rejection strategies

Thermal safety is one of the primary requirements for electric vehicles (EVs). Overheating by an external or internal heat source will induce the onset of thermal runaway. An overheating risk caused by tabs of pouch-type lithium-ion batteries was reported and the relevant heat rejection strategies were investigated in this paper. The positive tab showed a much higher temperature rise than that in the body and the negative tab of pouch-type lithium-ion batteries. The temperature reached 70.4 °C in the beginning 100 s with a charge rate of 2 C-rate, showing a fast temperature response. Besides, the largest temperature difference between the charge and discharge process was about 20.2 °C (2 C-rate), which indicates that the positive tab in the charging process is more dangerous than that in discharging process. Moreover, an electro-thermal model was applied to investigate the potential risk of tabs in the pouch-type lithium-ion battery. An extreme temperature rise (∼ 350 °C) in the positive tab showed a potential thermal risk in a high charging rate (6C). And the temperature at the tab can only be controlled under a relatively high heat transfer coefficient (higher than 100 W·m−2·K−1). This work is meaningful for the development of a thermal management strategy in a battery pack with fast charging technologies.

Multiobjective optimal operation strategy for electric vehicle battery swapping station considering battery degradation

The study aims to analyze a futuristic view of the automobile industry conducive to the much-needed penetration of Electric Vehicles (EVs) as per the current environmental and economic scenario. The study suggests the roll-out of EVs in tandem with the supporting Charging Infrastructure, which is a prerequisite for adopting the former. Although transport electrification is a much-accentuated and researched solution to the deteriorating environment and plummeting conventional resources, the design, production, manufacturing, use, degradation, and disposal of an exponential number of lithium-ion batteries for the same have environmental, economic, and social impacts. Thus, emphasis has been made on the sustainable use of charging infrastructure that curbs unnecessary and early battery aging from fast charging technology. Battery swap requests at a Battery Swapping Station (BSS) can be served via batteries from either available battery stock or by charging previously incoming discharged batteries. The study suggests an optimal strategy for the same via a mathematical model representing the operation cost of a BSS consisting of three components, namely, cost of battery utilization, damage cost associated with different charging methods, and dynamic electricity cost. The solution to the multiobjective optimization problem gave the optimum number of batteries that should be used from the battery stock and the charging decision for incoming discharged batteries, given the possible charging options and the constraints on demand satisfaction. Finally, the results from two different optimization tools, Solver in MS Excel and Lingo software, were compared.

Life prediction model for lithium-ion battery considering fast-charging protocol

With the development of fast-charging technology, fast-charging protocols have been widely used in electric vehicles. However, charging the same type of lithium-ion batteries with different fast-charging protocols has an impact on the cycle life of the battery. Considering the impact of fast-charging protocols on battery life, this paper proposes a life prediction model for lithium-ion batteries that charge with fast-charging protocols. First, the charging-based features are extracted from charge data using dilated convolutional network. Second, the discharging-based features extracted from the discharge curve are enhanced using deep neural network. Finally, the charging-based features and the discharging-based features are merged and fed into random forest regression to predict the cycle life of lithium-ion batteries. Considering that hyperparameters of the model have great influence on the prediction performance, the Bayesian optimization algorithm is used to optimize the hyperparameters of random forest regression. Two public datasets are used for validation. The experimental results show that the proposed method is significantly superior to other existing algorithms for battery cycle life prediction. The relative importance of the charging-based features and the discharging-based features for predicting battery life is also explored.

Robust optimization for integrated planning of electric-bus charger deployment and charging scheduling

• Investigate an integrated planning problem for electric-bus systems. • Incorporate muliple practical factors and requirements of electric-bus operations. • Develop robust optimization model to address energy consumption uncertainty. • Conduct empirical study in Singapore and provide managerial insights for operators. Public transit (PT) operators have been replacing existing bus fleets with electric buses (EBs) to achieve carbon neutrality. To ensure a cost-effective EB operation with driving range anxiety, fast en-route charging technology has been adopted to recharge EBs during the dwell time. This study aims to determine an integrated robust planning for EB systems, by simultaneously optimizing en-route charger deployment, charging schedule and EB battery configuration, with the goal to minimize the total cost. A deterministic optimization model was first formulated that incorporates multiple practical factors such as weight-related energy consumption and charging capacity. Then we move forward to build robust optimization models to consider the energy consumption uncertainty. The developed models are transformed into equivalent and tractable formulations, which can be solved efficiently by off-the-shelf solvers. Lastly, numerical experiments demonstrate that the proposed models can provide an optimal and robust EB system planning solution for PT operators.

Numerical investigation on the polarization and thermal characteristics of LiFePO4-based batteries during charging process

• An electrochemical-thermal couple model is developed for pouch lithium-ion batteries. • Effects of charge rate on polarization and heat generation are numerically studied. • Sudden rises in total polarization are mainly linked to solid-phase diffusion polarization. • Over 85% of the heat in the cell core under 8C charging comes from irreversible heat. • Charge energy efficiency of the cell at different current levels is further analyzed. High-current charging exacerbates internal polarization and abnormal heat generation, stymieing the development of fast-charging technology for lithium-ion batteries. Based on battery disassembly and charge test experiments, an electrochemical-thermal coupling model was developed and validated in this paper. The variation patterns of various polarization and heat generation of pouch-type lithium iron phosphate (LFP) batteries at different charge rates and their influence mechanisms were investigated numerically. Results indicate that the changes in charge voltage profiles are strongly linked to total cell polarization, and excessive charge current aggravates internal polarization, with the average polarization voltage reaching 109.2 mV at 8C, which is 471.7% higher than at 1C. The polarization in the electrodes dominates the cell polarization, especially at the negative electrode. Activation polarization accounted for the largest share of electrode polarization, the change in polarization profiles in the initial and final stages depended mainly on the solid-phase diffusion polarization. Besides, the large cell temperature difference at high charge currents is attributed to the order of magnitude difference in heat generation rates between the positive tab and the cell core. The cell temperature rise is primarily due to heat production in the cell core, where the proportion of irreversible heat increases nonlinearly with the charge rate, exceeding 85% of the total heat generation at 8C. The charge energy efficiency reduces gradually with increasing charge rate and is only 0.948 at 8C. These findings will help to develop appropriate charging protection strategy for better battery operation and life.

Design of Battery Electric Bus System Considering Waiting Time Limitations

Battery electric bus (BEB) is getting increasing consideration from transit agencies as a sustainable public transportation alternative. Although BEBs' limited driving range and longer charging duration cause concern for bus operators, fast-charging technology is a potential remedy for extending the daily driving range of BEBs while simultaneously reducing the charging duration and battery size. However, increased queue length at the terminals for fast charging can also cause a problem in adhering to BEB schedules. In this context, a comprehensive analysis is required to plan and design the BEB system considering waiting time limitations, and finding the right trade-off between battery sizes and charging infrastructure. In this study, we developed a base optimization model, as well as its stochastic version, accounting for varying energy demand scenarios under different operating conditions. Our models determined the effects of waiting time limitations over the BEB battery sizes and charger design variables (location, size, and capacity) while minimizing the total cost of the BEB system. The sample average across all the scenarios is used to estimate the stochastic optimization model objective, which is then solved using the Lagrangian relaxation method. We implemented our model over a public bus subnetwork proposed for electrification in the city of New Delhi, India. The results suggest that considering waiting time limitations at a fast-charging station can affect the system design and will help bus operators abide by the service level agreements covering trip delay, frequency, daily mileage, and so forth, made with the transit agency.

Effects of Fast Charging Modes on Thermal Performance of Lithium‐Ion Battery

Fast charging technology can greatly increase the charging speed and shorten the charging time of electric vehicles, but the heat generation and temperature rise of the lithium‐ion battery during the fast charging process seriously affect its electrochemical characteristics and cycle life and even cause safety issues. Therefore, it is necessary to analyze the thermal performance of the lithium‐ion battery under fast charging conditions and investigate the effects of different fast charging modes on it. Herein, an NMC lithium‐ion cell is taken as the object, and the electrochemical–thermal coupling model is built and verified. Based on this model, the heat generations and temperature rises of the cell in different fast charging modes are analyzed and compared, including constant current (CC) charging, constant voltage (CV) charging, CC–CV charging, stage CC charging, and pulse charging. It is found that the peak temperature of the cell appears at different moments in the above charging modes. The peak temperature and total heat generation during CV charging are much greater than those during charging of other modes. The results can provide references for the design and selection of charging modes and battery thermal management systems toward fast charging technology.

Comparative Study of Novelty Thin-films for Li-ion Batteries

<p>The development of Li-ion batteries leads to high-density Li-ion battery technology as a storage system. to realize a Li-ion battery with a high energy density is to modify its anode, called a thin-film anode. The anode used is coated with a material thickness of 10 mm, increasing the cathode material that can be accommodated in one cell. This study aimed to analyze the Cu-powder and LTO materials used in Thin-film Li-ion batteries as a substitute for graphite because they offer higher capacity, chemical stability, fast charging technology (LTO), cheap, and environmentally friendly (Cu-powder). Based on XRD and FTIR tests, the material has a good crystal structure, and not many impurities are still contained in it. The SEM results showed that both particles showed uniformity in the shape of a single particle and were strengthened by the SEM-EDX test to review the quantity of each element present in the two materials. The electrochemical test results showed that Cu-powder material was better, with a specific capacity of 144.82 mAh g<sup>-1,</sup> higher than LTO (81.04 mAh g<sup>-1</sup>).</p>

Electrolyte inhomogeneity induced lithium plating in fast charging lithium-ion batteries

Fast charging capability of lithium-ion batteries is in urgent need for widespread economic success of electric vehicles. However, the application of the fast charging technology often leads to the inevitable lithium plating on the graphite anode, which is one of the main culprits that endanger battery safety and shorten battery lifespan. The in-depth understanding of the initiation of lithium metal nucleation and the following plating behavior is a key to the development of fast charging cells. Herein, we investigate the overlooked effect of the non-uniform distribution of electrolyte on lithium plating during fast charging. Prior lithium plating occurs on the saturated lithium-graphite compounds in the anode region with sufficient electrolyte since the lithium-ion transport is blocked in the anode region lacking electrolyte. The uniform distribution of electrolyte is crucial for the construction of safe lithium-ion batteries especially in fast charging scenarios.

Design of a Highly Efficient 20-kW Inductive Power Transfer System With Improved Misalignment Performance

Due to the urgent desire for a fast, convenient, and efficient battery charging technology for electric vehicle (EV) users, extensive research has been conducted into the design of high-power inductive power transfer (IPT) systems. However, there are few studies that formulate the design as a multiobjective optimization (MOO) research question considering both the aligned and misaligned performances and validate the optimal results in a full-scale prototype. This article presents a comprehensive MOO design guideline for highly efficient IPT systems and demonstrates it by a highly efficient 20-kW IPT system with the dc–dc efficiency of 97.2% at the aligned condition and 94.1% at 150-mm lateral misalignment. This achievement is a leading power conversion efficiency metric compared to IPT EV charging systems disseminated in today’s literature. Herein, a general analytical method is proposed to compare the performances of different compensation circuits in terms of the maximum efficiency, voltage/current stresses, and misalignment tolerance. An MOO method is proposed to find the optimal design of the charging pads, taking the aligned/misaligned efficiency and area/gravimetric power density as the objectives. Finally, a prototype is built according to the MOO results. The charging pad dimension and total weight, including the housing material, are 516*552*60 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> /25 kg for the transmitter and 514*562*60 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> /21 kg for the receiver. Correspondingly, the gravimetric, volumetric, and area power density are 0.435 kW/kg, 581 kW/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> , and 69.1 kW/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , respectively. The measured efficiency agrees with the anticipated value derived from the given analytical models.

A Novel DC-AC Fast Charging Technology for Lithium-Ion Power Battery at Low-Temperatures

There are several drawbacks for lithium-ion batteries at low temperatures, including weak electrolyte conductivity, low chemical reaction rate and greatly increased impedance. Thus, it is inefficient to charge lithium-ion batteries at low temperatures. This work proposes an AC incentive fast charging strategy at low-temperatures for lithium-ion batteries based on the analysis and comparison of the existing charging and heating methods. The charging speed, temperature variation, the capacity loss of the constant current constant voltage (CCCV) charging strategy and the proposed method with different current and frequency conditions are compared and analyzed. The results show that it takes about 1400 s for the proposed method to fully charge a lithium-ion battery in the case of 2.2 A current beginning at 25% state of charge (SOC). In addition, the temperature rises about 8 °C. In contrast, the charging time of the CCCV method is 400 s slower than the proposed method and the temperature of the CCCV method increases only about 2 °C. In the case of 1.5 A current beginning at 0% SOC, the charging time of the proposed method is 500 s faster than the CCCV method. The results indicate that the proposed charging method can significantly improve the charging efficiency of lithium-ion batteries at low temperatures.

Battery design toward fast charging technology: a parametric survey

Battery design toward fast charging technology: a parametric survey

Home health care and dialysis routing with electric vehicles and private and public charging stations

ABSTRACT This paper studies a joint multi-depot home health care and dialysis problem of routing and scheduling decisions of health specialists. The fleet consists of electric vehicles, which use both public and private charging stations. We formulate the problem as a mixed integer linear programming model. We describe a hybrid adaptive large neighborhood search (ALNS) algorithm, which integrates construction heuristic to generate initial solution and local search procedure based on variable neighborhood descent. The hybrid ALNS successfully combines existing heuristic mechanisms and introduces several new problem-specific procedures to effectively handle the complex structure of the problem. We conduct experiments on realistic benchmark instances to investigate various problem specifications, such as constructed teams, usage rate of fast and super-fast charging technologies, and public and private charging options. We analyze the performance of the hybrid ALNS and its mechanisms. The algorithm obtained good quality results on the complex optimization problem.

Ultrafast battery heat dissipation enabled by highly ordered and interconnected hexagonal boron nitride thermal conductive composites

Heat dissipation involved safety issues are crucial for industrial applications of the high-energy density battery and fast charging technology. While traditional air or liquid cooling methods suffering from space limitation and possible leakage of electricity during charge process, emerging phase change materials as solid cooling media are of growing interest. Among them, paraffin wax (PW) with large latent heat capacity and low cost is desirable for heat dissipation and thermal management which mainly hindered by their relatively low thermal conductivity and susceptibility to leakage. Here, highly ordered and interconnected hexagonal boron nitride (h-BN) networks were established via ice template method and introduced into PW to enhance the thermal conductivity. The composite with 20 wt% loading amount of h-BN can guarantee a highly ordered network and exhibited high thermal conductivity (1.86 W m−1 K−1) which was 4 times larger compared with that of random dispersed h-BN involved PW and nearly 8 times larger compared with that of bare PW. The optimal thermal conductive composites demonstrated ultrafast heat dissipation as well as leakage resistance for lithium-ion batteries (LIBs), heat generated by LIBs can be effectively transferred under the working state and the surface temperature kept 6.9 °C lower at most under 2–5 °C continuous charge-discharge process compared with that of bare one which illustrated great potential for industrial thermal management.

Review of Fast Charging for Electrified Transport: Demand, Technology, Systems, and Planning

As the number and range of electric vehicles in use increases, and the size of batteries in those vehicles increases, the demand for fast and ultra-fast charging infrastructure is also expected to increase. The growth in the fast charging infrastructure raises a number of challenges to be addressed; primarily, high peak loads and their impacts on the electricity network. This paper reviews fast and ultra-fast charging technology and systems from a number of perspectives, including the following: current and expected trends in fast charging demand; the particular temporal and spatial characteristics of electricity demand associated with fast charging; the devices and circuit technologies commonly used in fast chargers; the potential system impacts of fast charging on the electricity distribution network and methods for managing those impacts; methods for long-term planning of fast charging facilities; finally, expected future developments in fast charging technology and systems.

Efficient Management of Fast Charging Systems Based on a Real-Time Monitoring System

Fast charging technology is attracting attention due to the increase in the use of batteries such as EV (Electric Vehicle), LEV (Light Electric Vehicle) and ESSs (Energy Storage Systems). Fast charging of the battery has problems such as fire, heat, and performance degradation of the battery. In the case of fast charging, a large current is applied to the battery to charge it. For this reason, information of battery voltage, battery current and temperature is important when charging a battery. Excessive current, overvoltage, and overheating beyond the standard value can cause deterioration of battery performance and a direct cause of fire. Therefore, the condition of the battery must be operated in the condition that meets the battery standard. To overcome these problems, we are trying to solve problems such as battery overheating and accidents by applying real-time monitoring technology, User Mode and Auto Control Mode. In this paper, we propose a real-time monitoring system based on the PHPOC Wi-Fi Shield. It operates to efficiently manage the charger and battery status based on real-time data, and is verified through real-time monitoring of the proposed system.

Optimization and Analysis of Electric Vehicle Operation with Fast-Charging Technologies

This work presents three demos, which include Electric Buses (EBs) from four various brands with lengths of 12 m and 18 m and an Electric Truck (E-truck) for refuse collection. The technical operation of these EVs were analyzed to implement further operational cost optimization on the demo vehicles. The Electric Vehicles (EVs) were tested against superfast-charging solutions based on Pantograph (Type A &amp; Type B) on the route lines (and depots) and based on Combined Charging System Type 2 (CCS2, Combo2) from various brands to validate the interoperability among several vendors and support further EV integration with more affordable solutions. The optimization includes the calculation of the EBs’ consumption at various seasons and under various operating conditions in order to use optimum battery system design, heating system, optimum EB fleet operation and size and to find the charging solutions properly. The results showed that the EB consumption increases in some cases by 64.5% in wintertime due to heating systems, and the consumption in urban areas is more than that on the route lines outside cities. In the E-truck demo, where the electric heater was replaced with a heat-pump to optimize the energy consumption, it was found that the consumption of the heat-pump is about half of the electric heater under certain operating conditions. Under strict EB schedule, Pantograph charging solutions with power ratings of 300–600 kW have been adopted to charge the batteries of the EBs within 4–10 min. In order to minimize the cumulative costs of energy, (pantograph) charging infrastructure depreciation and battery degradation, as well as depot charging (at the bus operator’s depot), was adopted with a power level of 50–350 kW based on CCS2 and pantograph.

Consumers Choice Decision Towards Electric and Conventional Motorcycles

Abstract. Air pollution is one of the most pressing emerging issues in Indonesia. To reduce emissions, people need to shift from conventional to electric motorcycles (EM). However, the number of conventional motorcycles (CM) in Indonesia is still far above electric, and there is no certainty whether the market will adopt it. Therefore, this research aims to identify significant factors that influence consumers’ decision in choosing electric or conventional motorcycles and to identify preferred motorcycle type, as well as to calculate the elasticity of each factor. Choice modeling analysis is used to estimate the probability of choosing motorcycles and the attributes that influence the decision. Data is collected through an online survey sent to 470 respondents. This research used three methods in processing the data: factor analysis, multinomial logistic regression, and demand elasticities analysis. Based on the result of this research, it is found that the significant factors are purchase price, charging times, driving range, and attitude towards each motorcycle type. Additionally, it is found that most of the respondents prefer electric motorcycles to conventional ones. The results suggested that motorcycles manufacturers should consider selling EM with lower prices, develop fast charging technology, and improve driving range, while the government should provide incentives for EM users. Therefore, this research supports findings to decrease air pollution in Indonesia by increasing the use of EM. Keywords: Electric vehicles, motorcycles, choice modeling, significant factors, stated preference