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This paper presents a bibliometric analysis of battery state estimation in electric vehicles. In this paper, a quick study is performed on the top global research contributors, funding agencies, and affiliate universities or institutes performing research on this topic while also finding the top keyword searches and top authors based on the most citations in the field of electric vehicles. Trend analysis is done by using the SCOPUS and Web of Science (WOS) databases (DB) from the period of 2000 to 2021. Battery state estimation plays a major role in the battery present state based on past experience. Battery available charge and health knowledge is a must for range estimation and helps us acknowledge if a battery is in useful condition or needs maintenance or replacement. A total of 136 documents in SCOPUS and 1311 documents in Web of Science were analyzed. Through this bibliometric analysis, we learn the top authors, country, publication journal, citation, funding agency, leading documents, research gap, and future trends in this research direction. The author Xiong Rui has the most publications, and he is working at the Beijing Institute of Technology, China. The most common institution is the Beijing Institute of Technology, and China is the most highly contributing country in this research. Most of the publications are conference types in SCOPUS DB and article types in WOS DB. The National Natural Science Foundation of China provides the most funding. The journal Energies has the most publications related to this field. The most cited works are by the authors M.A. Hannan and L.G. Lu in SCOPUS and WOS DB, respectively. A statistical analysis of the top ten countries' productivity results is also discussed. [ABSTRACT FROM AUTHOR]

An electric vehicle is a type of vehicle that is propelled by an electric motor fuelled by a battery. Electric vehicles are gaining popularity worldwide because of increasing environmental awareness and various benefits like less dependency on fossil fuel and they are considered an efficient and sustainable mode of transportation. This research presents a thorough overview and a bibliometric analysis of studies published related to consumer's adoption/ purchase intentions of Electric vehicles (EVs) from 1994 to 2023. The Scopus database was utilized to extract the papers as it is considered the largest database of peer-reviewed academic publications. The VOS Viewer software was used for the bibliometric analysis of networks between authors, institutions, countries, publications, journals, and keyword occurrence. The study was performed on 1 April 2023, which yielded a total of 140 documents after exclusion using the selected keywords. The findings indicate a considerable increase in EV adoption intention-related publications during the past six years. China is the world leader in this field of research, providing the maximum number of papers and involving the most prominent authors and research organizations. Whereas, Wang Z. has been the most productive author with a maximum number of publications in the area. Sustainability (Switzerland) journal stands out as the most prolific journal with the most publications. This analysis will help academicians better understand historical trends, current challenges, and prospective future research topics in the area of electric vehicle adoption/purchasing intentions. [ABSTRACT FROM AUTHOR]

A predictive model for the spatiotemporal distribution of electric vehicle (EV) charging load is proposed in this paper, considering multimodal travel behavior and microscopic traffic simulation. Firstly, the characteristic variables of travel time are fitted using advanced techniques such as Gaussian mixture distribution. Simultaneously, the user's multimodal travel behavior is delineated by introducing travel purpose transfer probabilities, thus establishing a comprehensive travel spatiotemporal model. Secondly, the improved Floyd algorithm is employed to select the optimal path, taking into account various factors including signal light status, vehicle speed, and the position of starting and ending sections. Moreover, the approach of multi-lane lane change following and the utilization of cellular automata theory are introduced. To establish a microscopic traffic simulation model, a real-time energy consumption model is integrated with the aforementioned techniques. Thirdly, the minimum regret value is leveraged in conjunction with various other factors, including driving purpose, charging station electricity price, parking cost, and more, to simulate the decision-making process of users regarding charging stations. Subsequently, an EV charging load predictive framework is proposed based on the approach driven by electricity prices and real-time interaction of coupled network information. Finally, this paper conducts large-scale simulations to analyze the spatiotemporal distribution characteristics of EV charging load using a regional transportation network in East China and a typical power distribution network as case studies, thereby validating the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

Solid-state hydrogen storage technology has emerged as a disruptive solution to the "last mile" challenge in large-scale hydrogen energy applications, garnering significant global research attention. This paper systematically reviews the Chinese research progress in solid-state hydrogen storage material systems, thermodynamic mechanisms, and system integration. It also quantitatively assesses the market potential of solid-state hydrogen storage across four major application scenarios: on-board hydrogen storage, hydrogen refueling stations, backup power supplies, and power grid peak shaving. Furthermore, it analyzes the bottlenecks and challenges in industrialization related to key materials, testing standards, and innovation platforms. While acknowledging that the cost and performance of solid-state hydrogen storage are not yet fully competitive, the paper highlights its unique advantages of high safety, energy density, and potentially lower costs, showing promise in new energy vehicles and distributed energy fields. Breakthroughs in new hydrogen storage materials like magnesium-based and vanadium-based materials, coupled with improved standards, specifications, and innovation mechanisms, are expected to propel solid-state hydrogen storage into a mainstream technology within 10–15 years, with a market scale exceeding USD 14.3 billion. To accelerate the leapfrog development of China's solid-state hydrogen storage industry, increased investment in basic research, focused efforts on key core technologies, and streamlining the industry chain from materials to systems are recommended. This includes addressing challenges in passenger vehicles, commercial vehicles, and hydrogen refueling stations, and building a collaborative innovation ecosystem involving government, industry, academia, research, finance, and intermediary entities to support the achievement of carbon peak and neutrality goals and foster a clean, low-carbon, safe, and efficient modern energy system. [ABSTRACT FROM AUTHOR]

The paper presents a novel charging load prediction model for electric vehicles that takes into account traffic conditions and ambient temperature, which are often overlooked in conventional EV load prediction models. Additionally, the paper investigates the impact of disordered charging on distribution networks. Firstly, the paper creates a traffic road network topology and speed-flow model to accurately simulate the driving status of EVs on real road networks. Next, we calculate the electric vehicle power consumption per unit kilometer by considering the effects of temperature and vehicle speed on electricity consumption. Then, we combine the vehicle's main parameters to create a single electric vehicle charging model, use the Monte Carlo method to simulate electric vehicle travel behavior and charging, and obtain the spatial and temporal distribution of total charging load. Finally, the actual traffic road network and typical distribution network in northern China are used to analyze charging load forecast estimates for each typical functional area under real vehicle–road circumstances. The results show that the charging load demand in different areas has obvious spatial and temporal distribution characteristics and differences, and traffic conditions and temperature factors have a significant impact on electric vehicle charging load. [ABSTRACT FROM AUTHOR]

With the expansion of China's automobile market and the increase in the proportion of electric vehicles, the influence of the automobile industry on water resources has been increasingly, and as a result, water resources will become an important factor restricting the development of the electric vehicle industry in China. Until now, there are still no in-depth studies on the influences of the water footprint of electric vehicles. The paper establishes a life cycle assessment model by which to analyze the reduction potential of the water footprint of various types of passenger vehicles in their operation. The paper also compares the water footprint of passenger vehicles under different power structures, revealing the potential influence of developing electric vehicles on the demand of water resources. The results show that at the base year (2019), the plug-in hybrid electric vehicles and battery electric vehicles consume more water than the gasoline-based internal combustion engine vehicles do, while water consumption of the hybrid electric vehicles and fuel cell vehicles is lower than that of the gasoline-based internal combustion engine vehicles; as for the year 2035, even after the proportion of renewable energy generation increases, the water withdrawal and consumption of the battery electric vehicles and plug-in hybrid electric vehicles will still be larger than those of the gasoline-based internal combustion engine vehicles. [ABSTRACT FROM AUTHOR]

Developing electric vehicle (EV) energy storage technology is a strategic position from which the automotive industry can achieve low-carbon growth, thereby promoting the green transformation of the energy industry in China. This paper will reveal the opportunities, challenges, and strategies in relation to developing EV energy storage. First, this paper clarifies the strategic value and potential of developing EV energy storage under the carbon neutrality goal. Second, this paper demonstrates strategic opportunities and challenges during the development. Third, this paper proposes methods for creating a good market environment and business models. Finally, this paper suggests that relevant policies and regulations should be formulated and charts the course of technology development. The results show that EV energy storage technology has potential in terms of technology, the scale of development, and the user economy. The proposal of the carbon neutrality goal, the increasing market share of EVs, lower-cost and higher-efficiency batteries, etc., have all further accelerated the development of EV energy storage. The EV energy storage field should focus on developing battery technology, make advancements toward delivering longer cycle lives and improving the safety and availability of battery materials, and ramp up the R&D efforts with respect to developing vehicle-to-grid (V2G) management technologies. Simultaneously, it is necessary to create a business ecosystem centered on V2G operating platforms, constituting a process to which various players can contribute and achieve mutually beneficial results. It is also essential to formulate top-level strategic plans across industries and organizations, develop an electricity-trading mechanism as soon as possible, and promote the implementation of technical standards related to EV energy storage. [ABSTRACT FROM AUTHOR]

With the extensive promotion of new energy vehicles, the number of electric vehicles (EVs) in China has increased rapidly. Electric vehicles are densely parked in garages, which means parking garages contain a large amount of idle energy storage resources. How to make this idle energy storage in garages participate in power system dispatch and evaluate the network loss and system carbon emissions considering electric vehicle energy storage has become an important research topic. The uncertainty around parking habits for electric vehicles causes it to be difficult to predict compared with the traditional energy storage system. Therefore, it is necessary to study its influence on the synergistic effect of loss reduction and carbon reduction as energy storage access. The benefits of new energy power generation output growth, energy waste reduction, and carbon emission reduction brought by loss reduction measures can be well reflected in the loss reduction index system of a power system in a low-carbon scenario. In this paper, a large amount of parking information in a certain area is collected, and the approximate parking habits of all vehicles in the simulated garage are obtained by the Monte Carlo method. Then, the load aggregation model is established, which is incorporated into the power system as an energy storage model. The synergy of loss reduction and carbon reduction is considered in this paper and comprehensively optimizes the strategy of integrating electric vehicles into the power system from the perspectives of electricity and carbon. In the scenarios of carbon flow calculation and network loss calculation, the YALMIP and CPLEX of MATLAB are applied, with various constraints input for simulation, so that the benefit evaluation method of carbon reduction and loss reduction under a coordinated transportation–electricity network is obtained. [ABSTRACT FROM AUTHOR]

The innovation ecosystem of the new energy vehicle industry is highly complex and spans several sectors; it is important to increase the resistance of the new energy vehicle industry network. This paper explores regional resilience in the context of China's new energy vehicle industry. Using patent cooperation data from 2011 to 2021, we construct a three-stage urban collaborative innovation network and analyze its structural characteristics. We also develop a resilience evaluation index system to measure the resilience of the network and its nodes. Furthermore, we propose a framework for resilience analysis that operates at the network, community, and node levels. Through our analysis of the network's resilience characteristics and evolution, we investigate the driving mechanisms behind its formation using the exponential random graph model (ERGM). Empirical results demonstrate that the urban collaborative innovation network is expanding and strengthening, with increased resilience and the ability to withstand uncertainty. Notably, the distribution of node resilience exhibits spatial heterogeneity, with cities in the eastern and central regions demonstrating higher resilience than those in other areas. Furthermore, the study finds that economic development and investment in education and technology can enhance network connections and resilience. Additionally, this paper reveals a strong dependence of inter-city cooperation on geographical proximity. [ABSTRACT FROM AUTHOR]

High-voltage heat release from batteries can cause safety issues for electric vehicles. Relevant scientific research work is carried out in the laboratory. The battery safety of laboratory experiments should not be underestimated. In order to evaluate the safety performance of batteries in the laboratory testing of driving conditions of electric vehicles, this paper simulated and compared the discharge characteristics of two common batteries (lithium iron phosphate (LFP) battery and nickel–cobalt–manganese (NCM) ternary lithium battery) in three different operating conditions. The operating conditions are the NEDC (New European Driving Cycle), WLTP (World Light Vehicle Test Procedure) and CLTC-P (China light vehicle test cycle) for normal driving of electric vehicles. LFP batteries have a higher maximum voltage and lower minimum voltage under the same initial voltage conditions, with a maximum voltage difference variation of 11 V. The maximum current of WLTP is significantly higher than NEDC and CLTC-P operating conditions (>20 A). Low current discharge conditions should be emulated in teaching simulation and experiments for safety reasons. The simulation data showed that the LFP battery had good performance in maintaining the voltage plateau and discharge voltage stability, while the NCM battery had excellent energy density and long-term endurance. [ABSTRACT FROM AUTHOR]

Implementing industrial policies to develop the new energy vehicle industry and improve technological innovation related to new energy vehicles is essential for countries dealing with environmental pollution and climate change. This paper first examines the impact of a demand-side industry policy related to new energy vehicles on the technological innovation level of supply-side vehicle enterprises. Regarding the new energy vehicle purchase tax exemption policy implemented by the Chinese government in 2014 as a quasi-experiment, this paper constructs a multi-period difference-in-differences (DID) model to identify the impact of the demand-side preferential tax policy on the technological innovation level of vehicle enterprises. In our DID design, 178 enterprises are in the treatment group and 166 enterprises in the control group, with 3,440 balanced panel data of observations. The results show that this policy can significantly promote the technological innovation of new energy vehicle enterprises. This promotion effect is greater in magnitude in large-scale enterprises, high-tech enterprises, and enterprises producing passenger vehicles. Theoretically, we believe that the demand-side tax exemption policy mainly indirectly promotes the technological innovation level of automobile enterprises through the signal channel and profit channel. [ABSTRACT FROM AUTHOR]

With China's vigorous implementation of the two-carbon policy. the automotive industry is transitioning from traditional to alternative energy sources. Accurate forecasting of new energy vehicle sales can provide statistical support for policy planning. This paper proposed a grey Lotka-Volterra model based on an HP filter to forecast new energ vehicle sales trends. The proposed model overcomes the limitations of the original model in forecasting cyclical data and improves its applicability in small sample data systems. And the competitive forecasting model allows us lo explore the market competition or cooperation between various vehicle types. Compared to the two existing models, the new model perfbrms better in forecasting vehicle sales. The study further applies the LCA method to assess the scale of energy consuniption and GHG emissions in the automotive sector. The prediction and evaluation results show that new energy vehicle sales will surpass traditional fuel vehicles by 2035 and dominate the vehicle market before 2050. Unfurtunately, vehicle electrification has not significantly reduced the transportation industry's environmental concerns. To fully utilize the potential for enet·gy-savings and emission-reduction of new energy vehicles, it is urgent to pursue technological advancements in battery production and power-generating structure. [ABSTRACT FROM AUTHOR]

Energy conservation and emission reduction are important policies vigorously promoted in China. With the continuous popularization of the concept of green transportation, electric vehicles have become a green transportation tool with good development prospects, greatly reducing the pressure on the environment and resources caused by rapid economic growth. The development status of electric vehicles has a significant impact on urban energy security, environmental protection, and sustainable development in China. With the widespread application of new energy vehicles, charging piles have become an important auxiliary infrastructure necessary for the development of electric vehicles. They have significant social and economic benefits, so it is imperative to build electric vehicle charging piles. There are many factors to consider in the scientific layout of electric vehicle charging stations, and the location selection problem of electric vehicle charging stations is a multiple-attribute group decision-making (MAGDM) problem. Recently, the Combined Compromise Solution (CoCoSo) technique and CRITIC technique have been utilized to deal with MAGDM issues. Spherical fuzzy sets (SFSs) can uncover the uncertainty and fuzziness in MAGDM more effectively and deeply. In this paper, on basis of CoCoSo technique, a novel spherical fuzzy number CoCoSo (SFN-CoCoSo) technique based on spherical fuzzy number cosine similarity measure (SFNCSM) and spherical fuzzy number Euclidean distance (SFNED) is conducted for dealing with MAGDM. Moreover, when the attribute weights are completely unknown, the CRITIC technique is extended to SFSs to acquire the attribute weights based on the SFNCSM and SFNED. Finally, the SFN-CoCoSo technique is utilized for location selection problem of electric vehicle charging stations to prove practicability of the developed technique and compare the SFN-CoCoSo technique with existing techniques to further demonstrate its superiority. [ABSTRACT FROM AUTHOR]

Since 2014, the electric vehicle industry in China has flourished and has been accompanied by rapid growth in the power battery industry led by lithium-ion battery (LIB) development. Due to a variety of factors, LIBs have been widely used, but user abuse and battery quality issues have led to explosion accidents that have caused loss of life and property. Current strategies to address battery safety concerns mainly involve enhancing the intrinsic safety of batteries and strengthening safety controls with approaches such as early warning systems to alert users before thermal runaway and ensure user safety. In this paper, we discuss the current research status and trends in two areas, intrinsic battery safety risk control and early warning methods, with the goal of promoting the development of safe LIB solutions in new energy applications. [ABSTRACT FROM AUTHOR]

Taking new energy vehicle (NEV) listed enterprises from 2010 to 2018 as a research sample, this paper empirically analyzes the innovative impact of VC on NEV enterprises by applying the difference-in-difference (DID) model. The results indicate that the intervention of VC has a positive and significant impact on the green technological innovation in NEV enterprises, an impact which is reflected in a significant increase in the number of green invention and green utility model patent applications. Compared with state-owned NEV enterprises, VC plays a more significant role in promoting the green technological innovation of private and foreign NEV enterprises. In the NEV industry chain, VC has significantly promoted green technological innovation of upstream and midstream NEV enterprises. From the perspective of VC, it also finds that, compared with independent and local VC, it is the syndicated and non-local VC that have a more positive and significant impact on green technological innovation in the NEV enterprises. Besides, the high-reputation of VC has not had an "incubating" effect on green technological innovation in NEV enterprises. [ABSTRACT FROM AUTHOR]

Developing new energy vehicles is vital to promote green development and the harmonious coexistence of humans and nature. It is also the only way to help China move from a significant automobile country to a powerful automobile country. Based on the background of the "recession" of government subsidies and considering the importance of green credit in promoting green and low-carbon transformation, this paper constructs a four-party evolutionary game model that includes government, automotive companies, banks, and consumers to analyze the stability of the strategic choices of various parties in the development process of the new energy vehicle industry. It uses MATLAB simulation tools to analyze the impact of relevant factors on system stability. The research shows that: (1) The government's subsidy mechanism significantly promotes the development of the new energy vehicle industry. Still, there is a subsidy threshold, beyond which the effect will weaken and quickly bring financial pressure. (2) With the gradual decline of government subsidies, the bank's green credit policy has a specific policy complementary effect on the decline of government subsidies. (3) Considering that costs and benefits are the main influencing factors for automotive companies and consumers' strategic choices, the impact of factors such as the punishment of violations, adjustment of subsidy policies, and consumers' environmental awareness must also be paid attention to. [ABSTRACT FROM AUTHOR]

Virtual power plant (VPP) is a comprehensive demand response (DR) technology to aggregate various power supply and consumption resources to help stabilise power grid fluctuations and reduce CO2 emissions. Fast‐charging electric vehicles (EVs) with higher charging power and shorter charging time are the most potential high‐quality DR resources of VPP in the future. In this paper, a new 'spatial‐temporal' bi‐layer optimal control strategy is proposed to solve the daily real‐time DR dispatching problem of large‐scale EVs including fast‐charging ones in a multi‐area VPP oriented to China's dual carbon target. This proposed bi‐layer strategy has two main contributions in both spatial and temporal domains. One is that, compared with the limited geographical area in traditional VPP, the upper layer of the proposed strategy considers the DR problem of EVs in a VPP with multiple geographical areas and establishes a spatial optimisation model of EVs DR considering both energy and carbon transaction costs of the overall VPP. The other is that rather than traditional slow‐charging EVs DR control with 1‐h temporal interval, the lower layer of the proposed strategy adds fast‐charging EVs in the real‐time orderly charging and discharging DR control by a shorter temporal interval of 15 min and designs two different charging and discharging price stimulation scenarios. The simulation results in the last section of this paper show that the proposed 'spatial‐temporal' bi‐layer optimal control strategy can effectively guide the charging and discharging behaviours of EVs in both spatial and temporal domains of a multi‐area VPP, achieving lower energy and carbon transaction cost and smaller load fluctuations. [ABSTRACT FROM AUTHOR]

This paper proposes a framework for generating a battery test profile that accounts for the complex operating conditions of electric vehicles, which is essential for ensuring the durability and safety of the battery system used in these vehicles. Additionally, such a test profile could potentially accelerate the development of electric vehicles. To achieve this objective, the study utilizes a simplified longitudinal dynamics model that incorporates various factors such as the drivetrain efficiency, battery system energy conversion efficiency, and regenerative braking efficiency. The battery test profile is based on the China light-duty vehicle test cycle-passenger car (CLTC-P) and is validated through testing on an electric vehicle with a chassis dynamometer. The results indicate a high degree of consistency between the generated and measured profiles, confirming the efficacy of the simplified longitudinal dynamics model. [ABSTRACT FROM AUTHOR]

China's New Energy Vehicle (NEV) industry has entered an accelerated development stage, with the technology innovation efficiency becoming an essential factor affecting the speed of its development. Therefore, to explore ways to improve the efficiency of technology innovation, this paper divides the technology innovation process into two stages: the research and development (R&D) stage and the commercialization stage. This paper introduces a framework for evaluating the technology innovation efficiency of NEV enterprises based on data envelopment analysis (DEA), meta-frontier, and tobit regression. Then, the technology innovation efficiencies of 45 vehicle, battery, and motor & electronic control NEV enterprises are analyzed. The results show that: (i) During the survey period, the overall technology innovation capability of Chinese new energy vehicle enterprises is not strong, especially regarding economic transformation. However, the general development trend is on the rise. (ii) Different types of enterprises have different technology gap ratios in the two stages. The technology innovation efficiency level of motor and electronic control enterprises is relatively weak in the new energy vehicle industry. (iii) Many measures can be implemented to help improve technology innovation efficiency: encouraging the large-scale development of enterprises, reasonably increasing the shareholding ratio of significant shareholders, improving the ratio of capital investment, stimulating the vitality of innovation within the enterprise, and optimizing the number of employees. [ABSTRACT FROM AUTHOR]

Low-carbon travel is an important part of low-carbon cities and low-carbon transportation, and low-carbon transportation is an inevitable choice to slow down the growth of carbon emissions in China. All countries in the world are actively promoting new energy vehicles and attach great importance to the application of the new energy industry in urban transportation. Commuting is an important part of urban life, and the choice of travel behavior has an important impact on traffic and environmental protection. Taking the Xi'an metropolitan area as an example, this paper expounds on the integrated development path of the industrial chain of new energy + travel in the metropolitan area and clarifies the energy transformation model of the integrated development of low-carbon transportation and energy. From the perspective of green and low-carbon, 1000 commuters were interviewed using a questionnaire survey, and the cumulative prospect model was used to verify the internal mechanism affecting commuters in metropolitan areas to choose new energy commuting. The results of the study show that new energy transportation modes play an important role in the low-carbon economy, and under different scenarios and assumptions, there are significant differences in the cumulative prospect values of the subway, new energy buses and fuel private cars, and corresponding optimization measures are proposed to increase the proportion of new energy commuting trips. The results will help further promote the development of a low-carbon economy and energy integration in the field of transportation and provide a reference for the sustainable development of public transportation. [ABSTRACT FROM AUTHOR]

China has been able to deploy electric vehicles at an unprecedented speed and scale. This paper explores the underlying policies during six years of sector formation, and it identifies a change in policy-regime after three years. The analysis of evolution of the policy-regimes indicates that creating, transferring, and sharing knowledge among the principal actors was key to catching up. The changing policy-regime enabled a minimum threshold of technology development required for deployment. Nevertheless, it was insufficient for pushing the sector to the global technology frontier. Key to the sector's relative success was the government's responsiveness to sectoral development and its ability to address production, demand, and knowledge issues simultaneously. In addition, it created synergies between policies designed to address environmental concerns and foster economic development concurrently. However, fast deployment required heavy subsidies and important policy initiatives came with potential pitfalls that may hamper international competitiveness of the sector. [ABSTRACT FROM AUTHOR]

Battery swapping for electric vehicle refueling is reviving and thriving. Despite a captivating sustainable future where swapping batteries will be as convenient as refueling gas today, a tension is mounting in practice (beyond the traditional "range anxiety" issue): On one hand, it is desirable to maximize battery proximity and availability to customers. On the other hand, capacitated urban power grids may curb decentralized charging at a slow speed. To reconcile this tension, some cities are embracing an emerging infrastructure network: Decentralized swapping stations replenish charged batteries from centralized charging stations. It remains unclear how to design such a network or whether pooling charging demands will save costs or batteries. In this paper, we model this new urban infrastructure network. This task is complicated by non-Poisson swaps and by the intertwined stochastic operations of swapping, charging, stocking, and circulating batteries among swapping and charging stations. We tackle these complexities by deriving analytical models, which enrich the classical batched repairable-inventory theory. We next propose a joint location and repairable-inventory model for citywide deployment of hub charging stations, with a nonconvex nonconcave objective function. We solve this problem exactly by exploiting submodularity and combining constraint-generation and parameter-search techniques. Even for solving convexified problems, our algorithm brings a speedup of at least three orders of magnitude relative to the Gurobi solver. The major insight is twofold: The benefit of pooling charging demands alone is not enough to justify the adoption of the "swap-locally, charge-centrally" network; instead, the main justification is that faster charging accessible at centralized charging stations significantly reduces the system-wide battery stock level. In a broader sense, this work deepens our understanding of how mobility and energy are coupled toward enabling smart cities. This paper was accepted by Chung Piaw Teo, optimization. Funding: Y. Zhang acknowledges the support from the National Natural Science Foundation of China [Grants 71871023, 72271029, and 72061127001]. W. Qi acknowledges the support from the National Natural Science Foundation of China [Grants 72272014 and 72188101] and the Natural Sciences and Engineering Research Council of Canada [Grant RGPIN-2019-04769]. N. Zhang acknowledges the support from the China Scholarship Council [202106030140]. Supplemental Material: The data files and online appendices are available at https://doi.org/10.1287/mnsc.2023.4731. [ABSTRACT FROM AUTHOR]

Under the carbon peaking and carbon neutrality goals background in China, cities are the main force of energy consumption and carbon emission, and their low‐carbon transition development has become the primary task of urban planning. The transitional development of cities not only puts forward higher requirements for the output proportion of new energy, but also puts forward higher requirements for the flexibility of energy system. This paper proposes an optimization model of urban energy system considering the uncertainty output of new energy and new energy vehicles. The uncertainty and operational flexibility of electric vehicles are taken into account at the planning level by using stochastic optimization method. The model considers the expansion and retirement of new energy units and various conversion devices in urban energy system, and ensures the achievement of carbon peaking and carbon reduction goals by imposing constraints on electric vehicles. The case results show that this model can effectively improve the economy and new energy consumption rate of urban energy system, and can meet the carbon reduction demand. [ABSTRACT FROM AUTHOR]

To explore the impact of promotion of electric vehicles on carbon emissions in China, this paper used the principal component analysis (PCA)-logistic regression model to predict the demand for traditional vehicles, and used the scenario analysis method to analyze the proportion of electric vehicles in traditional vehicles qualitatively. Then this paper calculated the carbon emissions during the power generation process based on the existing power structure. In addition, the IPCC carbon emission calculation method is used to compare the CO2 emissions produced by electric vehicles and fuel vehicles with similar vehicle quality while driving the same distance and consuming different energy sources. The results showed that the CO2 emissions of electric vehicles accounted for only 37.05% of fuel vehicles. By 2050, the annual electricity demand of electric vehicles will be 828.7, 776.9, and 752.1 billion kWh under the radical scenario, the reference scenario, and the negative scenario, respectively. According to the current power structure, the carbon emissions will be 1.2, 1.1, and 1 billion tons, respectively. The rapid growth of electric vehicles has a substantial impact on the grid load. Studying the changes in CO2 emissions from energy substitution is significant to formulate the development strategy of the automobile industry and adjust energy structure policies. [ABSTRACT FROM AUTHOR]

This paper reviews existing policies for supporting the treatment of electric vehicle (EV) battery waste in China, and identifies some of their major shortcomings that policy makers may like to consider while making policy decisions. The shortcomings of existing policies identified in this paper include: 1) no clear provisions for historical and orphan batteries; 2) no target for battery collection; 3) unclear definition of the scope of authority among various central and local agencies involved in the regulation of waste battery treatment; 4) unclear requirements for data auditing and verification for tracking the entire life cycle of EV batteries; 5) limited consideration of the challenges to ensure stakeholder cooperation; and 6) no explicit specification of the mechanisms for financing waste battery treatment. This paper also makes some practical policy suggestions for overcoming these shortcomings. [ABSTRACT FROM AUTHOR]

Fossil fuel usage has a great impact on the environment and global climate. Promoting new energy vehicles (NEVs) is essential for green and low-carbon transportation and supporting sustainable development. Lithium-ion power batteries (LIPBs) are crucial energy-storage components in NEVs, directly influencing their performance and safety. Therefore, exploring LIPB reliability technologies has become a vital research area. This paper aims to comprehensively summarize the progress in LIPB reliability research. First, we analyze existing reliability studies on LIPB components and common estimation methods. Second, we review the state-estimation methods used for accurate battery monitoring. Third, we summarize the commonly used optimization methods in fault diagnosis and lifetime prediction. Fourth, we conduct a bibliometric analysis. Finally, we identify potential challenges for future LIPB research. Through our literature review, we find that: (1) model-based and data-driven approaches are currently more commonly used in state-estimation methods; (2) neural networks and deep learning are the most prevalent methods in fault diagnosis and lifetime prediction; (3) bibliometric analysis indicates a high interest in LIPB reliability technology in China compared to other countries; (4) this research needs further development in overall system reliability, research on real-world usage scenarios, and advanced simulation and modeling techniques. [ABSTRACT FROM AUTHOR]

Despite the rapid development of electric vehicles (EVs), the limited range and accessibility of charging infrastructure are still obstacles to the development of EVs. At present, the Chinese government has made great efforts to set up charging stations and the most popular construction mode of charging stations in China is to divide a certain proportion of parking spaces in the parking lot to build charge piles. The proportion for every parking lot is the same and recommended by the government, which is a one-size-fits-all construction strategy. Nevertheless, with the growth of EVs, some challenges arise such as how to improve the accessibility of charging facilities in hot parking lots. The current work addresses this challenge by correctly forecasting the charging demand of EVs based on simulation. In particular, in this paper, based on agent simulation technology, electric vehicle agent, fuel vehicle agent and parking lot agent are established to predict the charging demand and the Wulin business district of Hangzhou City is used as an example to predict the charging demand of nine public parking lots. Simulation results show that under the current number of EVs, this one-size-fits-all setting strategy can meet the demand with high accessibility. However, with the increasing of EVs, the spatial distribution of charging demand will be more uneven and a decline in system overall benefits will appear, considering both EVs charging and fuel vehicles parking. Given all this, an optimization method based on GA (Genetic Algorithm) is put forward and an optimized setting strategy is proposed. [ABSTRACT FROM AUTHOR]

Pollution usually accumulates on the surface of the insulator rapidly on high‐speed electric multiple units (EMUs) under operation condition, and the flashover can occur frequently, especially when the EMUs is running on a high‐altitude line. To solve the problem, this paper proposes the calculation method of insulator withstand voltage under the condition of non‐uniform fouling distribution of high‐speed airflow based on the characteristics of high altitude of Lanzhou‐Xin Line in China, and gives the design and test verification of insulator support insulator for 3500‐km altitude. The design and test verification of the supporting insulator of the rolling stock applicable to 3500 km altitude are presented. The result shows that the insulator should be reliable operation on 4430‐km high altitude area if the insulator structure height is 430 mm, the creep distance is 1250 mm. The anti‐pollution performance is fine in high‐speed wind if the radiuses of the large and small shed of the insulator are 196 and 145 mm, respectively, and the shed spacing is 45 mm. The 50‐Hz withstand voltage of the developed insulator is 131 kV and the light impulse voltage is 228 kV which is suitable for lines running on 3500 m. This research provides a theoretical basis and data to support the safety of high‐speed rolling stock in high‐altitude areas. [ABSTRACT FROM AUTHOR]

Massive online reviews of new energy vehicles in China are deemed crucial by companies, as they offer valuable insights into user demands and perceptions. An effective analysis enables companies to swiftly adapt and enhance their products while upholding a positive public image. Nonetheless, the sentiment analysis of online car reviews can pose challenges due to factors such as incomplete context, abrupt information bursts, and specialized vocabulary. In this paper, an enhanced hybrid model is introduced, combining Enhanced Representation through kNowledge IntEgration (ERNIE) and a deep (Convolutional Neural Network) CNN, to tackle these challenges. The model utilizes fine-tuned ERNIE for feature extraction from preprocessed review datasets, generating word vectors that encompass comprehensive semantic information. The deep CNN component captures local features from the text, thereby capturing semantic nuances at multiple levels. To address sudden shifts in public sentiment, a channel attention mechanism is employed to amplify the significance of crucial information within the reviews, facilitating comment relationship classification and sentiment prediction. The experimental results demonstrate the efficacy of the proposed model, achieving an impressive accuracy rate of 97.39% on the test set and significantly outperforming other models. [ABSTRACT FROM AUTHOR]

Regarding the need to decrease carbon emissions, the electric vehicle (EV) industry is growing rapidly in China; the charging needs of EVs require the number of EV charging stations to grow significantly. Therefore, many refueling stations have been modified to integrated energy stations, which contain photovoltaic systems. The key issue in current times is to figure out how to operate these integrated energy stations in an efficient way. Therefore, an effective scheduling model is needed to operate an integrated energy station. Photovoltaic (PV) and energy storage systems are integrated into EV charging stations to transform them into integrated energy stations (PE-IES). Considering the demand for EV charging during different time periods, the PV output, the loss rate of energy storage systems, the load status of regional grids, and the dynamic electricity prices, a multi-objective optimization scheduling model was established for operating integrated energy stations that are connected to a regional grid. The model aims to simultaneously maximize the daily profits of the PE-IES, minimize the daily loss rate of the energy storage system, and minimize the peak-to-valley difference of the load in the regional grid. To validate the effectiveness of the model, simulation experiments under three different scenarios for the PE-IES were conducted in this research. Each object weight was determined using the entropy weight method, and the optimal solution was selected from the Pareto solution set using an order-preference technique according to the similarity to an ideal solution (TOPSIS). The results demonstrate that, compared to traditional charging stations, the daily revenue of the PE-IES stations increases by 26.61%, and the peak-to-valley difference of the power load in the regional grid decreases by 30.54%, respectively. The effectiveness of PE-IES is therefore demonstrated. Furthermore, to solve the complex optimization problem for PE-IES, a novel multi-objective optimization algorithm based on multiple update strategies (MOMUS) was proposed in this paper. To evaluate the performance of the MOMUS, a detailed comparison with seven other algorithms was demonstrated. These results indicate that our algorithm exhibits an outstanding performance in solving this optimization problem, and that it is capable of generating high-quality optimal solutions. [ABSTRACT FROM AUTHOR]

Electric vehicles are rapidly popping up in the market as a new alternative to fossil fuels, in order to reduce carbon emissions in urban areas. However, the improper placement of charging piles has impeded the development of electric vehicles. In this paper, 12 indicators from 4 categories, namely economy, environment, cost, and service quality are selected to form an index system for evaluating the location of electric vehicle charging piles. The entropy weight-TOPSIS method is also applied for the same purpose. On the basis of the evaluation, this paper proposes a set coverage model and adopts a greedy heuristic algorithm to find out the optimal location of charging piles. Finally, the paper verifies the reasonability and feasibility of this model by studying the existing location of electric vehicle charging piles in northeast China. The evaluation is based on the Liaoning Province Electric Vehicle Big Data Supervision Platform, which has data that are official and scientifically based. The set coverage model proposed, based on the evaluation, is a new solution to finding out the optimal location of electric vehicle charging piles across China. This study aims to provide a theoretical basis for the development of this new energy industry. [ABSTRACT FROM AUTHOR]

• A life cycle analysis on recycling and secondary use of lithium-ion batteries. • Based on the recycling in China, the LCA of different methods has been established. • Compared to other recovery, the secondary use has the lowest environmental impact. • Secondary use has the greatest impact on assessment results in dynamic situations. With the rapid development of the global new energy vehicle industry, how to minimize the environmental impact of the recovery has become a common concern and urgent concern. China is a major production and consumption market for electric vehicles, there are no specific and extensive resource and environmental assessment system for batteries. In this paper, the retired Electric vehicles lithium-ion batteries (LIBs) was the research object, and a specific analysis of the recycling treatment and gradual use stages of power batteries were based on life cycle assessment. Different battery assessment scenarios were established according to the development of battery recycling in China. The results showed that the secondary use has the optimal performance compared to the full-component physical, pyrometallurgical and hydrometallurgy recycling. The results showed that direct recycling has a GWP of 0.037 kg-CO 2 eq·kg LIB-1, which is lower than others. Secondary use of LIB accounts for the most emission reductions with Global warming (GWP) as 12.134 kg-CO 2 eq·kg LIB-1. The secondary use has the greatest impact on the assessment results, especially in dynamic scenarios. Through a comprehensive comparison of different recycling technologies, the secondary use, increasing the recycling rate, reducing resource, energy consumption and pollution emissions. [ABSTRACT FROM AUTHOR]

At present, two subsidy policies, which are based on electric vehicle (EV) consumers and EV charging station firms, have been widely implemented in different areas in China to promote EV adoption. However, the effectiveness of subsidy policies is significantly influenced by the indirect network and herd effects, depicting the positive impacts of the numbers of energy infrastructure firms and the sales of vehicles on consumers' utilities, respectively. Taking the aforementioned effects into consideration, this study examines the optimal subsidy policies by developing a Stackelberg game model. The game model analyzes the interaction and decisions of multiple stakeholders (i.e., consumers, energy infrastructure firms, EV and gasoline vehicle manufacturers, and the government). Interestingly, we find that a stronger herd effect will promote EV sales when the unit production cost of EVs is low; however, it will hinder EV sales when the unit production cost is high. Besides, we compare the effectiveness of the two subsidy policies for promoting EV adoption, reducing environmental impacts, and increasing the social welfare. Findings show that the effectiveness of subsidy policies highly depends on the extent of the indirect network and herd effects. Specifically, compared with EV consumers-based subsidy policy, EV charging station firms-based subsidy policy will be more effective in only two conditions: a weak indirect network effect and a strong herd effect. Otherwise, the EV consumers-based subsidy policy will be more effective. The findings of the paper are helpful in enhancing the effectiveness of subsidy policy in China. • Government subsidy cannot always promote electric vehicle adoption. • The indirect network and herd effects affect the effectiveness of subsidy policy. • A stronger herd effect will not always promote electric vehicle sales. • Either consumers or charging station investors can be the best subsidy object. [ABSTRACT FROM AUTHOR]

The promotion policies of the new energy vehicle (NEV) industry have evolved over time along with its rapid development in China. The NEV market has advanced to a new level where it complies with international practices and fully accommodates competition. Studying the market implications of the NEV promotion policy adjustment is of significant theoretical and practical value given the subsidy withdrawal, technological advancement, and sales growth. Based on interrupted time series analysis, this paper used 60 monthly time points from January 2017 to December 2021 to construct a time-series data set. Taking promotion policy adjustment as a policy variable, this paper estimated the market effect disparities of promotion policies in major cities in China through counterfactual analysis, and the special phenomenon of NEV sales climbing caused by subsidy withdrawal was further analyzed. Furthermore, the study findings were verified by robustness and heterogeneity tests. The result showed that: 1 After several adjustments, the national NEV promotion policy achieved remarkable results in the first-tier and new first-tier cities and other developed areas in general. 2 The key factor to promote the NEV market was technological advancement, and the essence of subsidy withdrawal was to promote more rapid technological innovation among relevant enterprises by raising the threshold of subsidy technology and eliminating backward production capacity. It was the subsidy withdrawal that led to sales growth. 3 The policy of relaxing curbs on NEV purchases failed to significantly promote the sales of NEVs and did not seem to be unsustainable, so it should not be regarded as a key promotion policy in the future. It is suggested that the pertinent departments shift their promotion policies in favor of the user side, increase investment in NEV technology research and development, accelerate the elimination of backward production capacity through policies and regulations, adjust the license number plate support policy for new energy vehicles in due course, and further improve the double-credit policy. [ABSTRACT FROM AUTHOR]

The development of new energy vehicles has become an important means by which China can continue to grow as a major automobile manufacturing powerhouse while joining the worldwide effort to tackle climate change. This paper uses Chinese‐listed new energy vehicle companies during 2015–2019 as the research sample and examines the impact of government subsidies on enterprise innovation, with the technical background of CEOs as an important moderating factor. We also analyze the extent of this moderating role within different institutional environments and corporate ownership structures. The results show that government subsidies can encourage new energy vehicle enterprises to increase innovation investment, and CEOs' technical backgrounds can strengthen this relationship. Compared with regions with better institutional environments, the moderating effect of CEOs' technical backgrounds is more obvious in regions with poor institutional environments, and when compared with state‐owned enterprises, the effect is more obvious in the private sector. We propose a list of government and internal enterprise policies that would make use of the insights gained from our research results. [ABSTRACT FROM AUTHOR]

The electrification of the transportation sector is a pivotal strategy to curb carbon emissions from traditional fossil fuel-powered vehicles. China, the world's largest electric vehicle (EV) market, leads this transformative shift. This paper aims to unravel the past decade's development story of the EV industry in China. We first provide a comprehensive overview of the EV development trend in China, including analysis of market structures, regional development variations, technology advancements, and the development of the essential infrastructure. We then summarize the different forms of subsidy programs, both monetary and non-monetary, designed to promote EV at both central and local levels, and evaluate the effectiveness of these programs and their contribution to reducing carbon emissions. We conclude by highlighting key aspects that could enhance the efficiency of subsidy programs and further propel the development of the EV industry. [ABSTRACT FROM AUTHOR]

With the continuous development of intelligent transportation technologies, new ways of energy usage in transportation continue to emerge, which puts forward new requirements for the planning and design of energy systems. However, comprehensive analyses on the characteristics of transportation energy systems and the development trend of energy usage patterns brought by intelligent technologies have rarely been carried out so far. This paper explores this subject by reviewing the recent development and utilization of intelligent technologies in the transportation system and its impacts on energy usage. This review is carried out from three aspects, covering the representative intelligent transportation and energy technologies on vehicles, infrastructures and systems. The scope is limited within road, railway and water transport domains, with a focus on the recent developments in China as a representative. In terms of vehicles, the development trend of the power systems for new energy vehicles, the characteristics of energy usages in electric vehicles and the effects on energy saving and emission reduction are summarized. In terms of infrastructures, new technologies on smart road, smart port, intelligent railway energy system and the usage of clear energy on electric grid for transportation are reviewed, with the consideration of their potential influences on energy usages and the energy consumption characteristics of typical facilities also being analyzed. As for the transportation system, this review has focused on intelligent and connected transportation systems, train control and autonomous systems, and intelligent shipping system, with the emphasis on the energy saving and emission reduction effects of applying these intelligent technologies. The overall development trend of the transportation energy system is then analyzed based on the above materials, in particular, the future energy usage patterns in transportation system are given and the major challenges and obstacles approaching the future scenarios are also identified. [ABSTRACT FROM AUTHOR]

Copyright of China Population Resources & Environment is the property of Shandong Normal University 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.)

Comprehensively understanding how the policy influences the sustainability transition of the automotive industry is a critical focus in recent years. This paper focuses on the dual-credit policy, an underexplored but critical policy in China, and examines how it would influence the transition of automotive industry. To achieve this goal, an SD model is developed to simulate the effect of policy parameters on the policy objectives by considering the interaction of production, technology and market. The findings reveal that this policy can in general promote the sustainable development of the automotive industry by greatly decreasing its overall energy consumption. However, its impact on the market share of new energy vehicles is limited. Based on the results, some policy suggestions are proposed so as to improve the effectiveness of the dual-credit policy. [ABSTRACT FROM AUTHOR]

The development of electric vehicles (EVs) is not only a necessary path for China to move from a big country to a powerful country in automobile industry, but also a strategic measure to achieve the goal of "peak carbon dioxide emissions" and "carbon neutrality." However, in the low and high temperature environment, EVs may face problems such as a large reduction in cruising range, slow charging and poor safety, which decrease the attractiveness of EVs to consumers and hinder the EV adoption. However, existing research rarely pays attention to the impact of temperature on the EV adoption. Based on the panel data of electric vehicle sales in 20 Chinese provinces from 2010 to 2018, this paper uses interaction fixed effect (FE) model to test the effect of temperature on the EV adoption and explains the causes of regional differences in EV adoption. The study has the following findings. Firstly, EV sales show an inverted U-shaped trend with the change of temperature. Secondly, compared to extreme high temperature, extreme low temperature has a greater negative impact on the EV adoption. Thirdly, the negative impact of extreme temperature on battery electric vehicles (BEVs) is greater than that of plug-in hybrid electric vehicles (PHEVs). Finally, temperature will make consumers' behavior adaptive by affecting their expectations. These findings can provide policy makers, department of urban planning and building, EV technology and quality inspection department, non-governmental organizations, and EV manufacturer, aiming at accelerating the market proliferation of EVs, with theoretical basis and targeted insights. [ABSTRACT FROM AUTHOR]

Copyright of Railway Standard Design is the property of Railway Standard Design 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.)

China has developed a preliminary policy system for the development of new energy vehicles regarding the law, electricity price, grid-connected standards, project management, and financial support, however, defects remain in the policy and market environment, market mechanism, control technology, infrastructure, etc. We analyze new energy vehicles based on the analysis of basic data such as the number of electric vehicles and charging facilities, focusing on industrial development strategies, related subsidies, and tax policies. First, this paper summarizes the development status of China's new energy vehicles in different scenarios. In 2021, China's new energy vehicle production was 3545 thousand, and sales amounted to 3521 thousand. According to preliminary estimates, the number of new energy vehicles will exceed 15 million in 2030. The research route for the development of new energy vehicle bottlenecks is proposed. Secondly, we analyze foreign and Chinese policies on different stages and construct the implementation path for the healthy and stable development of China's new energy vehicles. By comparing the basic indicators, related policies, and related innovation activities of new energy vehicles in China, we conclude that the development of the national electric vehicle industry needs to be increased in terms of government policies, business model innovation, and public awareness. [ABSTRACT FROM AUTHOR]

Prompted by the urgency of reducing greenhouse gas emissions in the transport sector, the Chinese government has set ambitious targets for the uptake of electric vehicles. To achieve these targets is however a challenging task, due to various barriers in the uptake of electric vehicles, at both micro- and macro-levels. A range of monetary and non-monetary incentives has been implemented, or being considered for implementation, to overcome these barriers. This paper reviews these incentives with a view to assess the extent to which they are likely to remove the barriers in the uptake of electric vehicles. The review suggests that the primary focus of these incentives is to remove the micro-level barriers, such as high upfront costs, poor technical performance, and insufficient charging infrastructure. Limited attention has been paid to the macro-level barriers (for example, fragmented authority and local protectionism), despite ample evidence suggesting that these barriers could significantly impede the uptake of electric vehicles. Further, these incentives have tended to rely on regulation-based measures to remove the barriers. Only in the recent years, there appears to be a gradual shift towards market-based measures. This shift could improve the effectiveness of electric vehicle policies. The effectiveness of these policies could be enhanced if one recognizes the underlying macro-level barriers that are likely to protract or distort the implementation of market-based measures. This paper also provides some recommendations to remove these macro-level barriers. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are widely recognized as low-carbon transportation that adopts green and clean technology with contributing to mitigating global climate change. However, it appears that the practice in using EVs has not gained widespread popularity despite the promotion of various incentives with the presence of various restricting factors and challenges. In conducting this study in the context of China, we hypothesize that restricting factors have varying impacts on promoting EVs in China, where the adoption of EVs is of great potential. This paper identifies these restricting factors by applying AHP-FCE integrated approach, and these factors are classified into five dimensions, namely, technical, infrastructural, economic, governance and social. The results indicate that the top five restricting factors are security issues, limited driving range, long charging time, improper distribution of charging stations and lack of sharing between charging piles respectively. Our research contributes to a better understanding of EV restricting factors and their significance, which offers the assistance in the formulation of policies and decisions in order to promote effectively EVs in China. • The promotion of EVs is of great potential in China for mitigating global climate change. • Explore the RFPEVs in China using AHP-FCE integrated approach. • The RFPEVs in China can be classified into five dimensions, namely, technical, infrastructural, economic, governance and social. • The technical and infrastructural related are the most important constraints. • The main three important restricting factors are security issues, limited driving range, long charging time. [ABSTRACT FROM AUTHOR]

With the rise of electric vehicles and fast charging technology, electric vehicle load forecasting has become a concern for electric vehicle charging station planners and operators. Due to the non-stationary nature of traffic flow and the instability of the charging process, it is difficult to accurately predict the charging load of electric vehicles, especially in sudden major events. In this article, We proposes a high-precision EV charging load forecasting model based on mRMR and IPSO-LSTM, which can quickly respond to the epidemic (or similar emergencies). Firstly, the missing data in the original EV charging load data are supplemented, and the abnormal data are corrected. Based on this, a factor set is established, which included five epidemic factors, including new confirmed cases, the number of moderate risk areas, the number of high risk areas, epidemic situation and epidemic prevention policies of the city, and other factors such as temperature. Secondly, the processed load data and other data in the influencing factor set are normalized, and the typical characteristic curve is established for personalized processing of the relevant data of epidemic factors, so as to improve the sensitivity of load response to epidemic changes and the ability to capture special data (peak and valley values and turning points of load). Then the maximum relevant minimum redundancy (mRMR) is used to select the optimal feature set from the set of influencing factors. Then, the processed load data and its corresponding optimal selection are input into the IPSO-LSTM model to obtain the final prediction result. Finally, taking the relevant data of EV charging load in a city in China from November 2021 to April 2022 (the city experienced two local epidemics in December 2021 and March 2022 respectively) as an example, the model is evaluated and compared with other models under the forecast period of 1 h. Meanwhile, the performance of the model under different foresight periods (2 h, 4 h, 6 h) is compared and analyzed. The results show that the model has good stability and representativeness, and can be used for EV charging load prediction under the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

New energy vehicle (NEV) policies involve extensive and complex aspects. NEV policies have been an important issue of academic interest in the academic research community. The current research of the NEV policy has the key significance of inducing experience and guiding the future. This study conducts a comprehensive bibliometric analysis through quantitative research methods to summarize the development and evolution of NEV policy in recent years. Using Citespace visualization tools, we reviewed 2919 papers collected from the Web of Science, identified three stages in the development of the research field, and summarized features relevant to the policy in history. The most influential countries, institutions, authors, keywords, and references have been examined. Through burst detection and cluster analysis, we analyzed historical trends and trajectories in this area of research. In the data we collected, a number of indicators are related to China, indicating that China's NEV policy has a representative significance in the field of NEV policy research. Consequently, we further collected the relevant research from China, in order to summarize the policy reasons behind the rapid development of NEVs in China, and help researchers to have a better understanding of the frontiers of NEVs. [ABSTRACT FROM AUTHOR]

Electric vehicles and gasoline vehicles are substitutes for each other, and the cost of fuel is an important factor when consumers are faced with choices. Understanding the influence of changes in gasoline prices and charging prices on electric vehicle sales is of reference significance for promoting electric vehicles in the private sector. This paper uses data covering 212 prefecture-level cities from January, 2020, to August, 2022, for analysis, and the results show that different income groups have different sensitivities to the difference in oil and electricity prices. Additionally, changes in gasoline prices and charging prices will significantly affect electric vehicle sales in low-income and middle-income cities, electric vehicle sales in high-income cities will not be affected. Compared with nonpilot cities, residents of pilot cities are more sensitive to fuel price changes, indicating that the policy basis has a certain positive effect on the promotion of electric vehicles. It is recommended to consider the income status of regional residents when formulating policies for the use of electric vehicles. At the same time, publicity efforts should be increased to highlight the gap between the cost of fuel vehicles and electric vehicles. [ABSTRACT FROM AUTHOR]

This perspective paper elaborates on how the burden of environmental issues on public health and the economy led China's government to declare its revised environmental policies or "war on pollution". It explains the importance of photovoltaic solar (PV), electric vehicles (EV), and carbon capture and storage (CCS) in helping China to mitigate its environmental concerns while maintaining economic growth. China already leads PV solar and EV manufacturing; however, it has not made a tangible contribution to CCS technology yet. On the other hand, CCS is far behind its envisaged role in contributing to the reduction of greenhouse gas emissions and supporting countries to meet their net carbon zero targets. China's existing coal power plants are good candidates to be retrofitted with CCS. Similar to PV and EV technologies, China could influence this technology globally, by reducing the uncertainties, demonstrating the viability, and driving the costs lower. China's revised policies have been effective and shown global impacts, but their implementations remain as strong as the political will behind them. [ABSTRACT FROM AUTHOR]

Electric vehicles have the advantages of zero emissions and high energy efficiency. They have a broad potential in today's social life, especially in China where they have been widely used. In the current situation, whereby the storage capacity of electric vehicles is continually increasing and the requirements for grid stability are getting higher and higher, V2G technology emerges to keep up with the times. Since the electric vehicle charging station is a large-scale electric vehicle cluster charging terminal, it is necessary to pay attention to the status and controllability of each charging pile. In view of the lack of attention to the actual operation of the electric vehicle charging station in the existing vehicle–network interaction mode, the charging state of the current electric vehicle charging station is fixed. In this paper, deep learning is used to establish a load perception model for electric vehicle charging stations, and K-means clustering is used to optimize the load perception model to realize random load perception and non-intrusive load monitoring stations for electric vehicle charging. The calculation example results show that the proposed method has good performance in the load perception and controllability evaluation of electric vehicle charging stations, and it provides a feasible solution for the practical realization of electric vehicle auxiliary response. [ABSTRACT FROM AUTHOR]

With the promotion of the pilot development of distributed whole county roof photovoltaics in China, problems such as power consumption, energy regional balance, and grid stability have become prominent. In this paper, an application mode of electric vehicle (EV) charging network and distributed photovoltaic power generation local consumption is studied. The management idea of two-layer and four model has been established, including the regional distributed photovoltaic output model, electricity consumption model, EV consumption model, and regional grid load dispatching model, which can realize the scheduling of the energy flow formed by photovoltaic, induce the charging of EVs, and make the photovoltaic consumption in office building areas and residential building areas complementary. Firstly, according to the randomness of photovoltaic power generation and EV charging, the dynamic response capability, power support capability, effective convergence time, system stability, system failure rate, and other characteristics of regional loads are comprehensively analyzed, and the grid energy management model of EV charging network and distributed photovoltaic is proposed. Secondly, according to certain statistical characteristics, the distributed photovoltaic will be concentrated, and EV charging will be prioritized to achieve nearby consumption. Finally, different scenarios are described, and the scenarios of charging in the park, community life, and power supply service are selected for analysis. This mode is intended to guide the consumption of new energy through economic leverage, which can realize the unified regulation of distributed energy convergence, consumption and storage. [ABSTRACT FROM AUTHOR]