Blockchain technology in the renewable energy sector: A co-word analysis of academic discourse

The transformative potential of blockchain technology in the renewable energy sector is increasingly gaining recognition for its capacity to enhance energy efficiency, enable decentralized trading, and ensure transaction transparency. However, despite its growing importance, there exists a significant knowledge gap in the holistic understanding of its integration and impact within this sector. Addressing this gap, the current study employs a pioneering approach, marking it as the first comprehensive bibliometric analysis in this field. We have systematically examined 390 journal articles from the Web of Science database, covering the period from 2017 through the end of February 2024, to map the current landscape and thematic trajectories of blockchain technology in renewable energy. The findings highlight several critical thematic areas, including blockchain's integration with smart grids, its role in electric vehicle integration, and its application in sustainable urban energy systems. These themes not only illustrate the diverse applications of blockchain but also its substantial potential to revolutionize energy systems. This study not only fills a crucial gap in existing literature but also sets a precedent for future interdisciplinary research in this domain, bridging theoretical insights with practical applications to fully harness the potential of blockchain in the renewable energy sector.

Electric vehicle charging stations: Model, algorithm, simulation, location, and capacity planning

The transition to sustainable transportation is imperative in mitigating environmental impacts, with electric vehicles (EVs) at the forefront of this shift. Despite their environmental benefits, the global adoption of EVs is curtailed by challenges such as nascent battery technology, high costs, and insufficient charging infrastructure. This study addresses the optimizing electric vehicle charging station (EVCS) locations as a critical step toward enhancing EV adoption rates. Thus, establishing efficient charging stations is critical to meet the increasing demand. By integrating location modeling with demand forecasts and market penetration, we propose a comprehensive approach to determine optimal locations and capacities for EVCS. Firstly, review existing literature, highlighting the significance of facility location models in optimizing EV charging infrastructure and identifying gaps in addressing demand and market penetration. Our methodology uses a genetic algorithm to solve the p-median problem for location selection and Arena 14 simulation software to model station traffic and optimize charging unit types and quantities. The model prioritizes public areas, considering potential demand points and station locations to propose optimal charging areas. Results indicate that our model minimizes travel distances and waiting times, offering a scalable solution adaptable to future EV market growth. This study contributes to the field by presenting a sustainable and economical model for EVCS placement and capacity planning, underlining the importance of a robust charging network in the broader adoption of electric transportation. The findings suggest that proactive infrastructure development, guided by accurate demand predictions and optimized location strategies, can significantly enhance the feasibility and attractiveness of EVs, supporting global efforts towards a cleaner, more sustainable transportation system.

Are electric vehicles really the optimal option for the transportation sector in China to approach pollution reduction and carbon neutrality goals?

Profound worldwide fleet electrification is thought to be the primary route for achieving the target of carbon neutrality. However, when and how electrification can help mitigate environmental impacts and carbon emissions in the transport sector remains unclear. Herein, the overall life-cycle environmental impacts and carbon saving range of two typical A-class vehicles in China, including electric vehicle (EV) and internal combustion engine vehicle (ICEV), were quantified by the life cycle assessment model for endpoint damage with localization parameters. The results showed that the EV outperformed the ICEV for the total environment impact after a travel distance of 39,153 km and for carbon emissions after 32,292 km. The ICEV was more carbon-friendly only when the driving distance was less than 3229 km/a. Considering a full lifespan travel distance of 150,000 km, the whole life-cycle average environmental impacts of EV and ICEV were calculated as 8.6 and 17.5 mPt/km, respectively, but the EV had 2.3 times higher impacts than the ICEV in the production phase. In addition, the EV unit carbon emission was 140 g/km, 46.8% lower than that of the ICEV. Finally, three potential reduction scenarios were considered: cleaner power mix, energy efficiency improvement and composite scenario. These scenarios contributed 19.1%, 13.0% and 32.1% reductions, respectively. However, achieving carbon peak and neutrality goals in China remains a great challenge unless fossil fuels are replaced by renewable energy. The research can provide scientific reference for the method and practice of emission reduction link identification, eco-driving choice and emission reduction path formulation.

Hybrid genetic algorithm-simulated annealing based electric vehicle charging station placement for optimizing distribution network resilience

Rapid placement of electric vehicle charging stations (EVCSs) is essential for the transportation industry in response to the growing electric vehicle (EV) fleet. The widespread usage of EVs is an essential strategy for reducing greenhouse gas emissions from traditional vehicles. The focus of this study is the challenge of smoothly integrating Plug-in EV Charging Stations (PEVCS) into distribution networks, especially when distributed photovoltaic (PV) systems are involved. A hybrid Genetic Algorithm and Simulated Annealing method (GA-SAA) are used in the research to strategically find the optimal locations for PEVCS in order to overcome this integration difficulty. This paper investigates PV system situations, presenting the problem as a multicriteria task with two primary objectives: reducing power losses and maintaining acceptable voltage levels. By optimizing the placement of EVCS and balancing their integration with distributed generation, this approach enhances the sustainability and reliability of distribution networks.

Health benefits of vehicle electrification through air pollution in Shanghai, China

Vehicle electrification has been recognized for its potential to reduce emissions of air pollutants and greenhouse gases in China. Several studies have estimated how national-level policies of electric vehicle (EV) adoption might bring very large environmental and public health benefits from improved air quality to China. However, large-scale adoption is very costly, some regions derive more benefits from large-scale EV adoption than others, and the benefits of replacing internal combustion engines in specific cities are less known. Therefore, it is important for policymakers to design incentives based on regional characteristics - especially for megacities like Shanghai - which typically suffer from worse air quality and where a larger population is exposed to emissions from vehicles. Over the past five years, Shanghai has offered substantial personal subsidies for passenger EVs to accelerate its electrification efforts. Still, it remains uncertain whether EV benefits justify the strength of incentives. The purpose of our study is to evaluate the health and climate benefits of replacing light-duty gasoline vehicles (ICEVs) with battery EVs in the city of Shanghai. We assess health impacts due to ICEV emissions of primary fine particulate matter, NOx, and volatile organic compounds, and to powerplant emissions of NOx and SO2 due to EV charging. We incorporate climate benefits from reduced greenhouse gas emissions based on existing research. We find that the benefit of replacing the average ICEV with an EV in Shanghai is US$6400 (2400-14,700), with health impacts of EVs about 20 times lower than the average ICEV. Larger benefits ensue if older ICEVs are replaced, but replacing newer China ICEVs also achieves positive health benefits. As Shanghai plans to stop providing personal subsidies for EV purchases in 2024, our results show that EVs achieve public health and climate benefits and can help inform policymaking strategies in Shanghai and other megacities.

Barriers to adoption of electric vehicles in Texas

Sustainable mobility options such as electric vehicles (EVs) have the potential to improve the quality of life for Americans as well as those in other countries, as they can enhance the quality of the air we breathe, while reducing greenhouse gas emissions, fossil fuel consumption, and the adverse impacts of global warming. Despite their many benefits, however, the demand for EVs remains low. Therefore, this study aims to identify the barriers that affect the widespread EV adoption in the United States. Seventeen barriers were identified from the literature, and a questionnaire survey was designed and distributed to potential consumers of EVs. The survey yielded 733 responses, and various statistical tests like cluster analysis and chi-squared tests were performed. The results revealed that the high purchase price of the vehicle, high battery replacement cost, and the lack of public infrastructures for charging them were the primary concerns. The results also revealed that middle-aged men with high education and income are more enthusiastic about adopting EVs. The results presented in this study indicate a range of developments that different stakeholders could implement. To surmount the economic barriers to EV adoption, policymakers should strengthen incentives countrywide, and automakers should introduce more affordable EVs to the market. To overcome the challenges associated with charging, it is necessary to make investments in rapid charging infrastructure along the primary toll routes.

Extending the electric vehicle battery first life: Performance beyond the current end of life threshold

Presently, Electric Vehicle batteries are considered to have reached the End of Life once their State of Health falls to 70-80%. However, this criteria is universal to all battery capacities and not based on the specific application requirements. To evaluate whether the End of Life can be extended below the current threshold, the impact of the Internal Resistance increase needs to be addressed. In this sense, this study employs a degradation aware electrothermal model to evaluate the battery performance for different use cases. The findings reveal that capacity constraints are the main cause of the End of Life, followed by power constraints. However, this is highly dependent on the battery capacity. Large capacity batteries tend to reach the End of Life for capacity constraints, whereas smaller ones show power limitations first. The temperature increase has not shown to be a restriction for any of the cases simulated. The decline in performance is for most cases (37.5% of the simulated ones) noticed below 70% State of Health, supporting that the first-life of most batteries can be extended without compromising the vehicle's performance. This is especially the case for most average drivers using large battery capacities, currently emerging on the market. The methodology proposed for the simulated cases can be extended to real time operation in the Battery Management System. Estimating the End of Life in this way can support the maximization of the first-life and only requires an appropriate use of the available data.

A multi-scale lifecycle and technoeconomic framework for higher education fleet electrification

Transportation accounts for one-quarter of all energy related greenhouse gas emissions. As it pertains to transport electrification, higher education institutions-such as universities-can model solutions that affect broader society. Despite this, higher education's role in fleet electrification adoption has been understudied. We, therefore, modeled an archetypical higher education institution to analyze the carbon and economic payback periods of three electrification scenarios (Business-as-Usual, Targeted Electrification, and Full Electrification) using a cradle-to-grave lifecycle and technoeconomic approach. Given the archetypical higher education institution fleet of 368 vehicles, results show an economic ratio plateau point of about 8 years at 20 fuel-based cars replaced by electric vehicles and a carbon payback period peak of roughly 10 months at 50 fuel-based cars replaced. We then performed a multi-scalar analysis by leveraging implementation theory. We find that higher education institutions that adhere to the tenets of implementation theory are poised to be pro-environmental change agents in many regions and countries. The methods and findings herein can be adapted to other institutions, regardless of fleet size, and can bolster relevant decision-making outcomes now.

Exploring the state of health of electric vehicle batteries at end of use; hierarchical waste flow analysis to determine the recycling and reuse potential

With the increasing adoption of electric vehicles, their end-of-life management is a timely matter. This requires recognizing the upcoming volume of retired electric-vehicle-batteries to the waste stream. The projection is further useful if we have an estimation of the remaining value within them to categorize the recycling or repurposing potential to allow appropriate policy development and facility planning. This qualification assessment is neglected in the current literature. Neglecting the health status of retired batteries in estimating their residual value might end up over or underestimating their reuse and recycling potential. This study aims to provide a hierarchical battery waste estimation based on their health and age of disposal in Ireland. These two factors are the fundamental parameters in determining the feasibility of repurposing or recycling retired batteries. Identifying this information, we defined three reuse scenarios with different state-of-health limits. Results indicate almost 50%, 30%, and below 10% repurposing potential in the year 2050 when setting a repurposing threshold of above 80%, 85%, and 90%, respectively. The authors also highlight the effect of non-regional repurposing on the recycling potential.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13243-024-00137-4.

Will changes in charging and gasoline prices affect electric vehicle sales? Evidence from China

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.

Life cycle assessment of electric vehicles: a systematic review of literature

This study addresses the pressing need to evaluate the life cycle assessment (LCA) of electric vehicles (EVs) in comparison to traditional vehicles, amid growing environmental concerns and the quest for sustainable transportation alternatives. Through a systematic four-stage literature review, it strives to provide essential insights into the environmental impact, energy consumption, and resource utilization associated with EVs, thereby informing well-informed decisions in the transition to more sustainable transportation systems. The study's findings underscore a compelling environmental advantage of EVs. They emit a staggering 97% less CO2 equivalent emissions when compared to petrol vehicles, and a significant 70% less compared to their diesel counterparts, rendering them a crucial instrument in the battle against climate change. These environmental benefits are intricately linked to the adoption of clean energy sources and advanced battery technology. Furthermore, the study highlights the potential for additional emissions reduction through the extension of EV lifespans achieved by recycling and advanced battery technologies, with Li-ion batteries enjoying a second life as secondary storage systems. However, challenges remain, most notably the scarcity of rare earth materials essential for EV technology. The study's policy recommendations advocate for a swift shift towards clean energy sources in both EV production and usage, substantial investments in advanced battery technology, and robust support for recycling initiatives. Addressing the rare earth material shortage is paramount to the sustained growth and viability of EVs, facilitating a greener and more sustainable future in the realm of transportation.

The optimization of an EV decommissioned battery recycling network: A third-party approach

In this paper, we solve the urgent problem to construct a recycling network of decommissioned batteries of Electric Vehicles (EVs) and clarify the recycling entities that will be responsible for its reverse logistics (RL) process. We consider the third-party recycling entities to develop a recycling network and conduct a case-study of Xi'an, a key industry of EVs in China to provide a reference for the government and enterprises to develop recycling plans. We scientifically optimize our recycling network, which will have a significant impact on the environmental and economic benefits of electric vehicles (EVs) in Xi'an in the future. Specifically, we consider the costs of transportation, construction, operation, recycling, packaging, and emission, as well as the profits achieved through sales revenue and subsidy offerings. We collect the actual data of potential facility locations in Xi'an, predict the quantity of decommissioned batteries in the future, and develop a fuzzy-based model to solve the optimal results of battery traveling path and distribution in the recycling process network. Our results show that with the rapid growth of the number of decommissioned batteries, third-party revenues will reach about 53.08 billion by 2035. When the facilities split the recycling process load appropriately, the network has increase in revenue while the utilization rate of facilities will decrease. We expect that splitting will be a major trend in the future development of recycling network in Xi'an. Finally, a sensitivity analysis finds that with the environmentally conscious and safe operation of recycling, the negative impact on the third-party enterprises' revenue will be small. Our proposed methodology can serve as a critical framework for other cities and governments to plan their recycling networks and formulate regulations, reflecting on the realistic projection of the scale of decommissioned batteries of EVs and the potential siting and sizing of the recycling facilities.

Electric vehicle parameter identification and state of charge estimation of Li-ion​ batteries: Hybrid WSO-HDLNN method

This manuscript proposes a hybrid method for measuring the battery's dynamic electrical response as it is compressed by an external-force. The proposed hybrid technique is the wrapper of the War Strategy Optimization algorithm and Hierarchical Deep Learning Neural Network, commonly called as WSO-HDLNN technique. The main aim of the proposed method is to lessen the battery-voltage error. The War Strategy Optimization method detects the parameters of the battery method. The Hierarchical Deep Learning Neural Network is used to predict the dynamic-electrical-response of the battery when it deforms during external-force. By using the proposed method, the estimated voltage and measured voltage error are reduced, and identifies the parameter effectively. Finally, the proposed method is done in the MATLAB platform and it is compared with different existing approaches. The error of the proposed method is 4 mV, the Jellyfish Search Optimizer method error is 6 mV, the Heap-based Optimizer method error is 12 mV, and the Grey Wolf Optimizer method error is 14 mV. The proposed method time is 0.7 s The proposed method shows better results in all methods, like Jellyfish Search Optimizer, Heap-based Optimizer, and Grey Wolf Optimizer, The proposed method provides less computation time and error than the existing one is proved from the simulation outcome.

Layered energy-saving speed planning and control method for electric vehicle on continuous signal lights road

Emergency start-stop in front of signal lights is one of the main reasons for additional energy consumption and ride discomfort of Electric Vehicle (EV). Existing research on this issue rarely takes into account both energy consumption and ride comfort. Therefore, the layered energy-saving speed planning and control method is proposed. The upper is the layer of energy-saving speed planning. This layer reduces energy consumption of EV by reducing the number of stops on continuous signal lights road and minimizing the range of speed change. On this basis, the sinusoidal variable speed curve is used to smooth the acceleration process to improve ride comfort. Finally, the energy-saving speed considering ride comfort is obtained. This layer makes up for the issue that existing research rarely takes into account both energy consumption and ride comfort of EV, and is an extension and innovation of existing research. The lower is the layer of Model Predictive Controller (MPC)-based speed control. Based on the longitudinal dynamics model of EV, the MPC-based speed controller is established to control EV to track the energy-saving speed. The controller is easy to understand and implement, and it is also suitable for other research on EV, which has certain application value. The simulation results show that under various working conditions, the maximum energy consumption of EV passing through continuous signal lights road without stopping is 604.29 kJ/km, and the minimum is 244.76 kJ/km. The energy consumption is lower than that of actual road test, and it can be saved by 23.18 % compared with the method in the same field. The maximum Root Mean Square of accelerations (R M S a ) is 0.25 m/s2, and the minimum is 0.10 m/s2. The values of R M S a above are lower than 0.315 m/s2, which indicates that the ride comfort is good. The utilized method can reduce energy consumption of EV, improve its range and ride comfort, which has important reference significance for promoting the development of EV.

Improvement and application of electromagnetic vibration and noise suppression method for electric vehicle motor

Motor induced Electromagnetic Vibration and Noise (EVN) are mainly affected by Radial Electromagnetic Force Wave (REFW) and related harmonic amplitude. Therefore, in the past discussion on the suppression of motor induced EVN, it usually starts from this aspect. For this reason, this study proposes a method to suppress EVN. Firstly, the influence of the quantity of rotor slots on the function of Induction Motor (IM) is analyzed; Then, the optimization strategy of rotor slot fit is proposed according to the results; Finally, an optimization strategy for the skewness of IM is proposed. Based on the above contents, the experiment realized the suppression of EVN induced by electric vehicle motor. The experimental results show that the parameters of the motor are optimal when the quantity of rotor slots is 53. It is better to weaken the harmonic amplitude related to the low-order REFW. The peak values of the motor using the research strategy at the second and third vibration modes are - 35 db Hz and - 38 db Hz respectively, which are lower than those of the traditional motor. To sum up, the strategies proposed in the study can remarkably suppress the EVN of IM and improve the function of electric vehicles, which will promote the electric vehicle industry 's development.

Carbon mitigation and health effects of fleet electrification in China's Yangtze River Delta

Fleet electrification is one of the most promising strategies to mitigate carbon emissions and improve air quality. This study provides a comprehensive analysis of the currently unclear CO2 mitigation and human health benefits from electric vehicle (EV) adoption and energy decarbonization in the Yangtze River Delta (YRD) region by integrating fleet modeling, emission projection, air quality modeling and health risk assessment. Based on future socioeconomic trajectories, we project that the total vehicle stock in the YRD region will peak at 107-117 million around 2045-2050. The transition to EVs combined with largely renewable energy in the YRD region can potentially reduce CO2 emissions by 870 Tg in 2060 and brings along substantial health co-benefits with ∼360 avoided premature deaths per million from reduced PM2.5 and O3 concentrations. This study further explores the NO2-attributable burden from road transportation and reveals that fleet electrification could yield greater NO2-attributable health benefits than those from reduced PM2.5 and O3, especially in traffic-dense urban areas. Those findings indicate that China's near-term energy development plans (35% renewable energy) have created the conditions for large-scale EV adoption. Our results imply that the benefits of EVs exhibit substantial spatial heterogeneity, underscoring the importance of region-specific EV incentive policies, and hint that policymakers should prioritize densely populated megacities to maximize the potential for public health gains.

A bibliometric review on electric vehicle (EV) energy efficiency and emission effect research

Electric vehicles have received extensive attention due to their unique energy efficiency and good emission reduction effects. While a large-scale of electric vehicles are gradually replacing traditional fuel vehicles, it is necessary to ensure the energy efficiency of electric vehicles and the effectiveness of their emission reduction effects. This study conducted a bibliometric analysis of scientific publications on energy efficiency and emission reduction effects of electric vehicles from 2003 to 2022, using a variety of bibliometric tools such as R Studio, biblioshiny and VOSviewer. The results showed the gradual elimination of traditional energy vehicles, where electric vehicles play an important role in connecting energy efficiency and emission control. The results also showed the top publication outlets, citations trackers, authors with thematic evaluation of energy efficiency and emission reduction effects of electric vehicles. The contribution of the study is manifold. The academic contribution of the present study is the bibliometric analysis which will help academicians to get a quick overview of the most popular journals, top collaborators, documents, authors, and scientific knowledge structure. Secondly, policy makers, environmentalists, researchers, and academician will definitely get a pathway how they should go for future research. Finally, this study suggests more researches trend to focus on the sales of electric vehicles, automobile exhaust emissions, sensitivity analysis of electric vehicles, energy storage analysis to improve the energy efficiency of electric vehicles, and V2G related to the energy efficiency of electric vehicle clusters.

Temporal variations of volatile organic compounds inside the cabin of a new electric vehicle under different operation modes during winter using proton transfer reaction time-of-flight mass spectrometry

Transportation is globally becoming more vehicle-dependent as public awareness towards the health risks caused by cabin-emitted volatile organic compounds (VOCs) increases. Therefore, the need for quantifying their concentration increases as well. This study measured the real-time VOCs in a new mini-truck-type electric vehicle cabin using a proton transfer reaction time-of-flight mass spectrometry under varying cabin heating conditions during winter. A total of 246 ions were detected between m/z 30 and 250, 82 of which were quantified. The total ion count in the cabin was double that of the ambient air. Morning-to-noon concentration of total VOCs increased 2.5 times in the cabin under solar exposure (164.47-405.92 µg·m^-3). Additionally, 12 VOCs that either had higher indoor-to-outdoor ratios or globally regulated chosen to investigate the effects of cabin air conditions. Heater operation immediately increased concentrations of some VOCs by 54.62%. Furthermore, blocking solar exposure from windows reduced VOC emissions during heater off and on scenarios by 35.49% and 65.42%, respectively, indicating that window coverage also provided insulation against heat loss. Finally, the fresh air reduced cabin VOCs by 62.83% due to ambient air inflow. However, cabin concentrations remained higher than those of ambient air.

Life cycle water footprint of electric and internal combustion engine vehicles in China

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.

The economic and environmental impacts of shared collection service systems for retired electric vehicle batteries

One of the impending consequences of the rapid penetration of electric vehicles (EVs) is that a substantial amount of expired EV batteries will present an increasing waste collection and management problem, particularly in the urban context. Motivated by a lack of research on this issue, this paper comprehensively evaluates the relative benefits of shared versus non-shared collection systems, where the service outlets are not exclusive to specified automakers. Using a mixed-integer optimization model, the analysis features spatiotemporal and multiple stakeholder complexities. Based on the historical monthly EV sales data from 2016 to 2021, a representative case study of Beijing, China is conducted, including 16 district centers, 32 major automobile manufacturers, 153 collection service outlets and 4 disposal centers. The results show that a shared collection service system leads to higher profitability, higher collection rates, increased environmental benefits and improved facility utilization. Consequently, this research contributes to supply chain liberalization to foster the efficient waste management of EV batteries. With a further model extension, it can also provide decision support for the policy-making of more countries.

The alternative path for fossil oil: Electric vehicles or hydrogen fuel cell vehicles?

New energy vehicles are accelerating to substitute for internal combustion engine vehicles (ICEVs) and fossil oil. Although most literature acknowledges this trend, few compare two specific substitutable paths in terms of the operation system, namely electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs). This paper makes a comparative analysis of EVs and HFCVs in power sources, fuel storage and transportation, fuel supply infrastructure construction, and the cost and use of vehicles. Our findings indicate that electric passenger vehicles have more advantages in economy, safety, and environmental impact, in comparison with hydrogen fuel cell passenger vehicles. Nevertheless, great efforts should still be made to develop advanced rapid charging technology, shorten charging time, and accelerate charging infrastructure construction. Then, it is just around the corner for EVs to gradually take over from traditional motor vehicles driven by oil. In contrast, popularizing hydrogen fuel cell passenger vehicles faces several insurmountable obstacles in the short run, such as the high hydrogen production price, complicated storage process, and expensive hydrogen refueling station infrastructure. However, hydrogen fuel cell commercial vehicles have unique application scenarios. The dislocation and complementarity principle in different scenarios of EVs and HFCVs is supposed to be firmly grasped.

A systematic review of geographic information systems based methods and criteria used for electric vehicle charging station site selection

Many studies have incorporated particular models with various methods and algorithms to resolve the site selection problem for electric vehicle charging stations (EVCS). This paper systematically reviews research that evaluates geographic information systems (GIS) based EVCS location techniques and the variables used for decision making. We classify and characterize those techniques and variables to determine important linkages within the literature. A variety of databases were referenced to extract research published from 2010 to March 2023 pertinent to this specific location optimization problem, and 74 papers were selected after thorough evaluation. The models used in each paper were examined along with the methods for selecting variables and ranking alternate locations. Site selection for EVCS requires a multi-criteria decision making approach to meet the sustainability, efficiency, and performance goals of communities adopting electric vehicle mobility. Our results indicate that map algebra and data overlay methods have been used more frequently with GIS-based analysis than other techniques, while geographic and demographic variables are commonly the most significant site selection characteristics. The reviewed methods have most often been applied to urban locations; however, the transfer of these techniques to a rural EVCS site selection problem has been rarely explored in the current literature. This research assessment contributes relevant guidance for the application of methodologies useful in policymaking and provides recommendations for future research based on these findings.

A critical review on renewable battery thermal management system using heat pipes

The critical review presented here exclusively covers the studies on battery thermal management systems (BTMSs), which utilize heat pipes of different structural designs and operating parameters as a cooling medium. The review paper is divided into five major parts, and each part addresses the role of heat pipes in BTMS categorically. Experimental studies, numerical analyses, combined experimental and numerical investigations, optimum utilization of a phase-change material (PCM) with a heat pipe (HP), oscillating heat pipe (OHP), and micro heat pipes combined with PCM for Li-ion BTMS using heat pipes are presented. The usage of HP's and PCM can keep the temperature of the battery system in the desirable limit for a longer duration compared to other traditional and passive methods. More emphasis is made on how one can achieve a suitable cooling system design and structure, which may tend to enhance the energy density of the batteries, improve thermal performance at maximum and minimum temperature range. Arrangement of battery cells in a pack or module, type of cooling fluid used, heat pipe configuration, type of PCM used, working fluid in a heat pipe, and surrounding environmental conditions are reviewed. According to the study, the battery's effectiveness is significantly influenced by temperature. The usage of flat HPs and heat sink proves to be the best cooling method for keeping the battery working temperature below 50 °C and reduces the heat sink thermal resistance by 30%. With an intake temperature of 25 °C and a discharge rate of 1 L per minute, an HP that uses water as a coolant is also effective at regulating battery cell temperature and maintaining it below the permissible 55 °C range. Using beeswax as a PCM in HPs reduces the temperature of BTMS by up to 26.62 °C, while the usage of RT44 in HPs reduces the temperature of BTMS by 33.42 °C. The use of fins along with copper spreaders drastically decreases the temperature capability of HPTMS by 11 °C. MHPA shows excellent performance in controlling the battery temperature within 40 °C. The effective thermal management can be done by incorporating heat pipe alone or by coupling with liquid cooling or metal plate. However, extensive and extended research is required to improve thermal management to safely and effectively use the battery for day-to-day applications.

[E-scooter, e-bike and bicycle injuries in the same period-A prospective analysis of a level 1 trauma center]

BACKGROUND

The actual number of accidents in e‑scooter drivers in Germany seems to be significantly higher than the current figures from the Statistisches Bundesamt suggest. This epidemiological study examines e‑scooter injuries and compares them with e‑bike and bicycle injuries.

OBJECTIVE

In order to create a comparable database on the dangers of e‑scooters, e‑bikes and bicycles, the typical injury patterns were analyzed and prevention options derived from them.

MATERIAL AND METHODS

All accidents involving e‑scooters, e‑bikes and bicycles that were presented via the university emergency room of a level 1 trauma center between 15 June 2019 and 31 October 2020 were prospectively investigated.

RESULTS

In our study, 68 accidents in e‑scooter drivers were included, of which only 11.8% (n = 8) were recorded by the police. Significantly more of them were male than female (p = 0.032) with a mean age of 31.1 (±13) years. At the same time, we registered 34 accidents in e‑bike riders and 356 in cyclists. In all three groups, most injuries occurred to the head, followed by injuries to the upper extremities. Significantly more e‑scooter drivers had an ISS ≥ 16 than in the group of injured cyclists (p = 0.016). E‑scooter riders who had an accident had a significantly longer length of stay in hospital, than e‑bike riders (p = 0.003) and cyclists (p = 0.001), 52.9% (n = 18) of e‑bike riders and 53.3% (n = 113) cyclists wore a helmet, compared to only 1.5% (n = 1) of e‑scooter riders. The most common cause of accidents among e‑bike riders (17.7%; n = 6) and cyclists (10.4%; n = 37) was slipping away on tram rails, while for e‑scooter riders it was colliding with a curb (7.4%; n = 5).

CONCLUSION

The three patient collectives examined showed different causes and profiles of injuries. The reasons for an increased proportion of seriously injured people compared to cyclists are electromobility, driving under the influence of alcohol and inadequate wearing of a helmet on e‑scooters when head injuries dominate. 73.5% (n = 50) of the e‑scooter accidents recorded by us were not registered by the police and therefore do not appear in the current statistics of the statistisches Bundesamt. As a result, a much higher number of e‑scooter accidents can be assumed. Preventive measures could include the introduction of compulsory helmets, a higher number of traffic controls and the expansion of bike tracks.

Vehicle emissions of primary air pollutants from 2009 to 2019 and projection for the 14th Five-Year Plan period in Beijing, China

Over the past decade, the emission standards and fuel standards in Beijing have been upgraded twice, and the vehicle structure has been improved by accelerating the elimination of 2.95 million old vehicles. Through the formulation and implementation of these policies, the emissions of carbon monoxide (CO), volatile organic compounds (VOCs), nitrogen oxides (NO_x), and fine particulate matter (PM_2.5) in 2019 were 147.9, 25.3, 43.4, and 0.91 kton in Beijing, respectively. The emission factor method was adopted to better understand the emissions characteristics of primary air pollutants from combustion engine vehicles and to improve pollution control. In combination with the air quality improvement goals and the status of social and economic development during the 14th Five-Year Plan period in Beijing, different vehicle pollution control scenarios were established, and emissions reductions were projected. The results show that the emissions of four air pollutants (CO, VOCs, NO_x, and PM_2.5) from vehicles in Beijing decreased by an average of 68% in 2019, compared to their levels in 2009. The contribution of NO_x emissions from diesel vehicles increased from 35% in 2009 to 56% in 2019, which indicated that clean and energy-saving diesel vehicle fleets should be further improved. Electric vehicle adoption could be an important measure to reduce pollutant emissions. With the further upgrading of vehicle structure and the adoption of electric vehicles, it is expected that the total emissions of the four vehicle pollutants can be reduced by 20%-41% by the end of the 14th Five-Year Plan period.

A multi-criteria decision-making framework for electric vehicle supplier selection of government agencies and public bodies in China

Electric vehicle deployment shows promising potentials in promoting cleaner energy utilization and reducing carbon emission. Due to increasing carbon neutral pressure and market competition from transportation sector, government agencies and public bodies (GAPBs) have emphasized the significance of electric vehicle adoption through supplier selection. Consequently, GAPBs must consider a reasonable criteria system and a comprehensive supplier selection framework and rationally select the electric vehicle supplier that matches their practical needs in terms of economic, social, environmental, and technical factors. This paper provides insights into electric vehicle supplier selection (EVSS) from the perspective of GAPBs using an integrated multi-criteria decision-making (MCDM) framework based on best-worst method (BWM) and fuzzy ViseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Initially, 14 critical factors from economic, social, environmental, and technical dimensions are identified as the criteria by literature review and experts' opinions. Then, a comprehensive decision framework using the integrated MCDM approach is proposed. To validate the applicability and feasibility of the proposed framework, a case study is launched and analyzed. It emerges that bad environmental record, cost, quality, service, and environmental initiatives are the most important criteria in EVSS for GAPBs with the weight values of 0.1995, 0.1172, 0.1219, 0.0708, and 0.2553. The comparative analysis and the sensitivity analysis are performed for verifying the reliability of the proposed framework. The work helps to understand the electric vehicle supplier selection criteria and makes methodological decision-making support for GAPBs.

Load distribution structure of rear bumper beam to enhance vehicle body energy absorption in rear-end collisions

OBJECTIVE

This research focused on FMVSS301, which is required for higher energy absorption as a regulation for rear-end collisions. Since they are offset collisions, the deformation of the non-collision side frame, which does not directly contact the barrier, is less than on the collision side. The reason is that the rear bumper beam with curvature is deformed into a straight shape by the load from the barrier, resulting in an asymmetrical load distribution from the barrier that is biased toward the collision side. Therefore, the objective of this research was to construct a new bumper beam structure that reduces the difference in the load input to both frames and increases the energy absorption of the non-collision side frame.

METHOD

The basic principle is to generate a counterforce against the lateral loads during transmitting the load from barrier to the frames. To achieve this, a bow-shaped rear bumper beam structure was devised. The rear bumper beam corresponds to the bow and the newly added connection plate to the string. The lateral load increase is suppressed and load distribution to the rear frame is maintained.

RESULTS

The designed rear bumper beam and rear components equipped with the rear bumper beam were both prepared and evaluated by drop test. With testing of the rear bumper beam, it was demonstrated that the load in the lateral direction, which conventionally generates over 80 kN, could be canceled. Tests of the rear component demonstrated that load distribution to the rear frame could be maintained, and the energy absorption of the non-collision side frame could be enhanced by 35 times. The total energy absorption of the barrier and the two frames was demonstrated to increase 2.9 times.

CONCLUSION

The bow-shaped rear bumper beam was designed to distribute the load evenly to the collision and non-collision side frames, and to deform both frames, thereby achieving a higher energy absorption of the entire vehicle body. This is expected to be applicable to electric vehicles and FCVs, which require more energy absorption with increased vehicle weight.

Are first responders prepared for electric vehicle fires? A national survey

Transitioning to electric vehicles (EVs) will create both opportunities and challenges. Although some programs and resources related to EVs have been made available to first responders, it remains unknown whether our first responders are well prepared for traffic incidents that involve EVs and whether there are any organizational and geographic disparities in preparedness. To answer these questions, a national survey was conducted to collect feedback on responders' incident management knowledge and training experiences related to EVs, as well as their attitudes and concerns towards EVs. Over 1000 first responders across the country participated in the survey, and the survey had representation from all 50 states and Washington DC. Over 40% of first responders reported never receiving EV-related safety training. Paramedics or EMS are associated with the highest odds of not receiving EV-related training, followed by law enforcement. Geographically, FEMA Region 8 (e.g., Montana and North Dakota) is associated with the highest percentage of not receiving EV training. Regarding EV fire tactics, more than half (57%) of law enforcement officers said they do not know any; responders from towing & recovery also have little knowledge compared to firefighters. Statistical modeling was conducted to explore correlates of responders' EV safety training and knowledge of EV fire tactics. The survey also provided insights about the challenges and risks of managing EV-involved incidents. In summary, responders are greatly concerned about the risks that EVs can pose to their community, and actions must be taken now.

Application of photovoltaic panels in electric vehicles to enhance the range

There is a significant increase in the number of alternative energy sources and electric vehicles. Therefore, there is a growing need for new technical solutions to increase the distance that an electric vehicle can travel on a single charge. The aim of this study is to assess the possibility of mileage increasing of an electric vehicle by means of commercially available solar energy technologies that require minimal investment. The considered electric car can be recharged from solar panels mounted on its roof during parking stages. Photovoltaic modules can contribute to the vehicle's propulsion or energize its accessories, such as ventilation, air conditioner, heated passenger seats, interior lighting. The results demonstrate feasibility of the proposed solutions for both cases with and without sun-tracking adjustments of solar panels. The calculations show that the vehicle-integrated photovoltaic panels can provide energy for up to 6.32% of the range on a full charge of the battery during the sunniest summer months and up to 1.16% of the range during the least sunny winter months, for the given conditions.

Terminated local subsidy on electric vehicle adoption during the COVID-19 pandemic: The case of Chongqing City

Chongqing, one of the four municipalities directly under the Central Government in China, terminated local subsidies for electric vehicles (EVs) on June 26, 2019. Shortly after the termination, EV adoption in China was affected by the coronavirus disease (COVID-19) pandemic. However, little research studies on whether the terminated local subsidy has a lasting impact on EV adoption, especially during the pandemic. Using EV adoption data from Chongqing and 44 other cities in China, this study aims to fill this gap by first proposing a new method to estimate the unobservable data of the treated unit in the preintervention periods to obtain accurate results. This study then also estimates unobservable data for more conservative results. The findings show that the terminated subsidy has had a significant positive impact on EV adoption during the COVID-19 pandemic compared to the situation where a local subsidy was never provided. The results show that in Chongqing, during the first five months of the pandemic, terminated local subsidy helped reduce the loss of EV adoption by approximately 3141 units when accurately estimated, and approximately 1696 units when more conservatively estimated. These findings help to understand the role of subsidies both during implementation and after their termination.

Recent advances on air heating system of cabin for pure electric vehicles: A review

Due to the environmental protection and energy shortage, the electric vehicles (EV) is gradually replacing traditional fuel vehicles. EV generally use more energy for air conditioning system, especially EV have almost no waste heat from engine to be discharged to the passenger compartment to achieve thermal comfort in heating condition. The energy consumption of the heating system for EV will decrease the maximum mileage. Therefore, the energy saving technology for heating system is developing and applied for EV. The article introduced the advance of conventional and emerging heating system for the EV. The positive temperature coefficient (PTC) heater is a convenient heating method used in EV, but PTC heater has some defects such as low efficiency. The heat pump (HP) system is gradually replacing PTC. However, HP has various problems to be overcome, such as the heating capacity and efficiency in low temperature environment. In addition, other novel technologies are proposed to reduce the energy consumption. This article reviews the literature of novel heating methods for EV, introduces adsorption air conditioning systems (AAC), fuel combustion (FC), heat storage (HS), waste heat recovery (WHR), thermoelectric effect (TE) and magnetocaloric effect (ME).

© 2017 Elsevier Inc. All rights reserved.

Comparison of total PM emissions emitted from electric and internal combustion engine vehicles: An experimental analysis

Electric vehicles (EVs) are regarded as zero emission vehicles due to the absence of exhaust emissions. However, they still contribute non-exhaust particulate matter (PM) emissions, generated by brake wear, tire wear, road wear, and resuspended road dust. In fact, because EVs are heavier than internal combustion engine vehicles (ICEVs), their non-exhaust emissions are like to be even higher. While total PM emissions, including exhaust and non-exhaust PM emissions, from ICEVs and EVs have been compared based on the emission factors (EFs) listed in national emission inventories, there have been no comparisons based on experimental determinations. In this study, exhaust and non-exhaust emissions generated from a gasoline ICEV, diesel ICEV, and EV were experimentally investigated. The results showed that the EFs for the total PM emissions of ICEVs and EV were dependent on the inclusion of secondary exhaust PM, the brake pad type, and the regenerative braking intensity of the EV. When only primary exhaust PM emissions were considered in vehicles equipped with non-asbestos organic (NAO) brake pads, the total PM₁₀ EF of the EV (47.7-49.3 mg/V·km) was 10-17 % higher than those of the gasoline ICEV (42.3 mg/V·km) and diesel ICEV (43.2 mg/V·km). However, in vehicles equipped with low-metallic (LM) brake pads, the total PM₁₀ EF of the EV (49.2-57.7 mg/V·km) was comparable or lower than those of the gasoline ICEV (56.3 mg/V·km) and diesel ICEV (57.2 mg/V·km). When secondary PM emissions were included, the EF was always significantly lower for the EV than ICEVs. The total PM₁₀ EF of the EV (47.7-57.7 mg/V·km) was lower than those of the gasoline ICEV (56.5-70.5 mg/V·km) and diesel ICEV (58.0-72.0 mg/V·km). Since secondary PM particles are mostly of submicron size, the EFs of the PM_2.5 fraction of the ICEVs (28.7-33.0 mg/V·km) were two times higher than those of the EV (13.9-17.4 mg/V·km).

Global declarations on electric vehicles, carbon life cycle and Nash equilibrium

Universal environmental policies adopt strategies that enhance and encourage the production and usage of electric vehicles (EVs). Universal cooperation is evident in the framework of agreements or protocols so as to successfully lead countries towards the predetermined goals. The question is whether this trend can reduce global warming or CO₂ emissions worldwide. By adopting game theory, this study analyses electricity carbon life cycle in leading EV countries. Results show that although the spread of EVs in Europe and the USA can mitigate carbon emissions, the production and use of electric vehicles in some countries, such as China and India, become a new source of such emissions. This reverse effect is due to the emission of greenhouse gases from electricity sources in these countries. Game theory also suggests that countries with unclean electricity sources should reconsider their plans to produce and use EVs. This study confirms that although carbon emission and global warming are global problems, regional and local policies can be substituted with a single comprehensive approach for an effective means of CO₂ emission reduction.

Impact of COVID-19 on private driving behavior: Evidence from electric vehicle charging data

The COVID-19 pandemic has given rise to a major impact on traffic mobility. To implement preventive measures and manage transportation, understanding the transformation of private driving behavior during the pandemic is critical. A data-driven forecasting model is proposed to estimate daily charging demand in the absence of the COVID-19 pandemic by leveraging electric vehicle (EV) charging data from four cities in China. It serves as a benchmark for quantifying the impact of the COVID-19 pandemic on EV charging demand. A vector autoregressive (VAR) model is then used to investigate the dynamic relationship between the changes in charging demand and potential influencing factors. Potential influencing factors are selected from three aspects: public health data, public concern, and the level of industrial activity. The results show that the magnitude of the decline in EV charging demand varied by city during the pandemic. Furthermore, COVID-19 related factors such as daily hospitalizations and national confirmed cases are the primary causes of the decline in charging demand. The research framework of this paper can be generalized to analyze the changes in other driving behaviors during the pandemic. Finally, three policy implications are proposed to assist other countries in dealing with similar events and to stimulate the recovery of the transport system during the post-pandemic period.

Estimation of end-of-life electric vehicle generation and analysis of the status and prospects of power battery recycling in China

With the development of the electric vehicle (EV), vehicle end-of-life (EOL) management has become a significant challenge. This study sets two EV sales scenarios (low and high), compares the impact of two battery replacement methods (buying a new vehicle or replacing the battery) on future EOL EV production, and predicts the difference in the amount of EOL EV battery production under two probability functions (normal and Weibull's distributions). The results show that when the EV power battery is retired and the vehicle owner chooses to buy a new vehicle, the predicted scrap quantity under low sales and high sales (HS) scenarios in 2030 is 4.3 and 5.3 million, respectively. Replacing the battery and continuing to use the vehicle will mean fewer EOL vehicles are generated. Considering the construction of an EOL EV battery recycling management system in China is still in the exploratory period, it is necessary to encourage vehicle owners to replace the battery and continue to use the vehicle. Under a HS scenario, the predicted number of EOL EV batteries in 2030 is 3.8-7.4 million. In the next 10 years, the issue of EV recycling should be raised to the same level as the issue of EV popularisation.

Global electric vehicle adoption: implementation and policy implications for India

Present transport system of conventional vehicle in India has faced challenges due to enormous amount of air pollution, health hazards to human, rising oil price, insufficient indigenous fossil fuel reserve, heavy expenditure on oil import, energy insecurity, etc. Electrical vehicle (EV) is considered to be alternatives of conventional vehicles that can overcome these shortcomings. The aim of the study is to get an overview of the electric vehicle policies of government of India and its state governments to find out their relevance and impact on EV adoption in India. Exploratory research is used in present case to carry out the study. Currently, the EV industry in India is in preliminary condition and in growing stage. Government of India has framed policies such as "NEMMP 2020," "FAME-I," "FAME-II," and Vehicle Scrappage policy. Seventeen of its state governments have framed EV policy. These policies facilitated various types of incentives, infrastructure development, fund allocation, research and development, production, and sales. This will have strong impact on EV demand generation, conversion of conventional vehicles to e-vehicle resulting E-mobility transformation and EV hub in the region that is at par with other EV-developed countries in the world. However, lack of policy and technology availability in the domain of disposal and reprocessing of Li-ion battery is found to be a future limitation of EV prospect in Indian context which needs to be looked into.

Well-to-wheel greenhouse gas emissions of electric versus combustion vehicles from 2018 to 2030 in the US

CONCISE ABSTRACT

Electric vehicles (EVs) can reduce transportation-related greenhouse gas (GHG) emissions, given the planned electric grid decarbonization. Regulations can also reduce internal combustion engine vehicle's (ICEVs) emissions by mandating increased fuel economies or ethanol-gasoline mixes. Factors such as fuel economy, electricity grid mix, vehicle choice, and temperature affect EV GHG emissions relative to ICEVs, and successfully decarbonizing the transportation sector depends on understanding their combined effects. We use life-cycle assessment to compare the EV and ICEV well-to-wheel GHG emissions in the United States and four other states from 2018 to 2030. We found lower emissions for EVs than ICEVs in most conditions considered. In New York state, where natural gas power plants replace nuclear energy, GHG emissions of electricity generation increase over time after 2020. Future ICEVs can have comparable emissions to EVs due to fuel economy increase. Therefore, EV and ICEV can together lower transportation GHG emissions at a faster pace.

EXTENDED ABSTRACT

Transportation-related greenhouse gas (GHG) emissions can be reduced by (a) increasing the share of electric vehicles (EVs) and (b) reducing GHG emissions of internal combustion engine vehicles (ICEVs) by mandating increased fuel economies or ethanol-gasoline mixes. Factors, such as fuel economy, electricity grid mix, vehicle choice, and temperature affect EVs' relative GHG emissions compared to ICEVs, and understanding their combined effect is necessary for a successful decarbonization of the transportation sector. We used life-cycle assessment to evaluate the simultaneous effect of the above-mentioned factors on the well-to-wheel GHG emissions of EVs and ICEVs from 2018 to 2030. The analysis was performed for the United States (US) average and state-level for Arizona, California, New York, and Oregon. Our results showed lower GHG emissions for EVs than ICEVs for most conditions considered. GHG emissions are expected to decrease in the US on average by 5% for EVs and 27% for ICEVs in 2030 compared to 2018. In 2030, the ICEV well-to-wheel GHG emissions were comparable to those of the EVs in the US average and Arizona. EVs perform best in California and Oregon throughout the considered period. In regions, such as New York, EVs driven 2021 and after will have higher GHG emissions than ICEVs, as natural gas power plants are replacing nuclear energy. While EV GHG emissions decrease over time due to grid decarbonization, future ICEVs can lower the GHG emissions, especially for larger vehicles, where EVs might not be the best option. Therefore, EV and ICEV can together lower transportation GHG emissions at a faster pace.

The efficient operating parameter estimation for a simulated plug-in hybrid electric vehicle

Hybrid electric vehicles (HEVs) and plug-in HEVs (PHEVs) are indispensable tools in reducing greenhouse gas emissions to fight the twin evils of pollution and climate change. In these vehicles, battery replacement and fuel costs are the major recurring costs over a lifetime. Hence, there is a growing attempt to develop strategies that reduce the long-run expenditure in these vehicles without compromising on performance levels. Further, an increase in the fuel economy is also required for the effective penetration of these vehicles in society. Here, the authors attempt to identify the optimal operating values for battery state of charge (SoC), power ratings of motor, and fuel converter to increase the battery life and fuel economy without degrading the vehicle performance. The simulations have been carried out on Ford C-Max Energi (2016) as a representative for PHEVs based on the Urban Dynamometer Driving Schedule (UDDS) and Highway (HWY) driving cycles. The software used for these simulations is the future automotive systems technology simulator (FASTSim), developed by the National Renewable Energy Laboratory (NREL). In this paper, firstly, the effect of important parameters like battery SoC, fuel converter power, and motor power on HEVs' driving range, battery life, fuel economy, cost, and charge-depleting range has been analyzed. Based on this analysis, the optimal values of the parameters have been estimated. These parameters have resulted in improvements of driving range by 4.3% and battery life by 18% at a minute cost of a 1% decrease in the charge-sustaining battery life and a 0.4-s increase in the time the car takes to hit 60 mph from the rest. This paper presents a simple, effective, and new approach that explores the effect of altering the existing design parameters on vehicle performance, without manipulating, adding, or deleting any component or controller. This can further be extended to study the impact of various other parameters in the proposed work and opens a way to explore other parameters that exist in various other components of XEVs (where X can be H/PH//F). This study will help in achieving optimal cost reduction in these vehicles.

Assessment of end-of-life electric vehicle batteries in China: Future scenarios and economic benefits

A better understanding of the waste of end-of-life batteries from electric vehicles (EVs) is a basis for their sustainable management. This study aims to estimate the waste of end-of-life EV batteries during 2006-2040 in China and to analyze the opportunities and challenges of subsequent utilization, based on a developed numerical model, real market data, and elaborately developed scenarios. The result shows that end-of-life batteries would increase from 0.1 to 7.8 thousand tons during 2012-2018, and then to 1500-3300 thousand tons in 2040. Of the waste streams, around 50% are estimated to be metal materials, representing great opportunities for battery recycling for material recovery. Economically, battery recycling for energy storage is estimated to create more economic benefits compared with that for material recovery solely (147.8 versus 76.9 billion US dollars). However, the supply of end-of-life batteries can hardly meet the demand for renewable energy storage in the near future, and a spatial mismatch of the supply and demand of energy storage capacity exists between the eastern and western regions in China. Accordingly, this study highlights national coordination for the rational layout of the collection, disassembly, and remanufacture facilities for the second use of end-of-life EV batteries in China.

Comparative analysis of non-exhaust airborne particles from electric and internal combustion engine vehicles

This paper evaluates the effect of the electrification of the small, medium, and large internal combustion engine (ICE) passenger cars on the levels of total particulate matter (PM). The total mean PM₁₀ and PM_2.5 emission factors (EFs) on urban, rural, and motorway roads are in the range of 26.13 - 39.57 mg km^-1 veh^-1 and 13.39 - 18.44 mg km^-1 veh^-1, respectively, from small to large ICE passenger cars. Correspondingly, the total mean PM₁₀ and PM_2.5 non-exhaust EFs on urban, rural, and motorway roads range from 27.76 to 43.43 mg km^-1 veh^-1 and 13.17 -19.24 mg km^-1 veh^-1 from equivalent small to large electric vehicles (EVs) without regenerative braking. These results show that the total non-exhaust PM from the equivalent EVs may exceed all PM from ICE passenger cars, including exhaust particle emissions, which are dependent mainly on the extent of regenerative braking, followed by passenger car type and road type. PM₁₀ EFs for equivalent EVs without regenerative braking on urban, rural, and motorway roads are all higher than those from ICE cars. As for PM_2.5, most of the equivalent EVs require different extents of regenerative braking to reduce brake emissions to be in line with all particle emissions from relative ICE cars.

Impacts of COVID-19 on the electric vehicle industry: Evidence from China

Electric vehicle development is critical to achieve the sustainable goals, while the hit of COVID-19 strikes the market and brings challenges to the whole industry. China, among one of the earliest regions affected by COVID-19 and takes a great part in the global electric vehicle market, is attracting growing attention on its post-pandemic trends in the electric vehicle industry. This paper provides a comprehensive analysis of COVID-19 impacts on China's electric vehicle industry from both the demand side and the supply side. Both challenges and opportunities for China's electric vehicle development are revealed with emerging trend analysis. It is found that the COVID-19 outbreak has reduced electric vehicle sales in the short-term, but may also stimulate future electric vehicle demand especially for large electric cars with better performance. Meanwhile, travel restrictions caused by COVID-19 have interrupted electric vehicle material supplies that relying on imports, accelerating domestic substitute exploitation and inventory improvement for critical parts. Additionally, massive lockdowns for controlling COVID-19 have disrupted productions and operations, which tends to expel small brands out of the competitive market, concentrating China's electric vehicle industry to the leading brands. Finally, the social distancing trend after pandemic is bringing challenges to traditional EV distribution channels with dealers, pushing automakers to develop innovative online selling channels. These impacts are likely to lead to a reformation of China's electric vehicle industry towards a more advanced and reliable future.

A novel fault tolerant control approach based on backstepping controller for a five phase induction motor drive: Experimental investigation

The five phase induction motor (FPIM) is a very suitable choice for different industrial applications which require high reliability. This is due to the ability of the motor to keep operating even with open stator phases. However, to ensure the right operation and for achieving the desired dynamic performance in terms of reduced torque fluctuations, a fault tolerant control (FTC) methodology must be applied. Because of this, the paper introduces a novel FTC approach for the FPIM drive based on a backstepping controller. The derivation and explanation of the proposed technique are presented and analyzed in a systematic manner. The validation of the proposed FTC strategy has been carried out experimentally using a dSPACE 1104 control board. The test results approve the validity of the designed controller in achieving the control targets which ensures the highest system reliability of the drive that is mostly required in different automotive and industrial applications.

Evaluating the electric vehicle popularization trend in China after 2020 and its challenges in the recycling industry

In recent years, China has started to develop electric vehicles (EVs) and has become the largest EV market in the world since 2015. Accordingly, the lithium-ion battery (LiB) industry has also been developing quickly in China. However, the Chinese government has decided to cancel the subsidy policy on EVs, which makes the EV market in China unpredictable in the future. Moreover, there will be a considerable number of end-of-life (EoL) EVs and waste LiBs generated in China. These wastes should be appropriately recycled to avoid resource waste or pollution problems. Nevertheless, the quantity and type of EoL EVs and waste LiBs has not been obtained. This research aims at unravelling the trend of EV sales and the volume and type of EoL EVs and waste LiBs in China. We found that it is fair to predict that EVs will increase as the Chinese government has planned even without the subsidy policy. Moreover, we estimated the number of EoL EVs and waste LiBs number based on their calendar lifespan and found that there will be 1.36 million EoL EVs and 11.36 million waste LiBs generated in China in 2030. Furthermore, most of these waste LiBs will be of the nickel cobalt manganese oxide type of ternary LiBs. However, due to the flow of second-hand vehicles from economically developed cities to less economically developed cities, only 400,000 EoL EVs and 3.4 million waste LiBs will be recycled through the formal recycling route. Such information is necessary when evaluating the environmental effect or profitability of the EoL EV and waste LiB recycling industry.

Light electric vehicle charging strategy for low impact on the grid

The alarming increase in the average temperature of the planet due to the massive emission of greenhouse gases has stimulated the introduction of electric vehicles (EV), given transport sector is responsible for more than 25% of the total global CO₂ emissions. EV penetration will substantially increase electricity demand and, therefore, an optimization of the EV recharging scenario is needed to make full use of the existing electricity generation system without upgrading requirements. In this paper, a methodology based on the use of the temporal valleys in the daily electricity demand is developed for EV recharge, avoiding the peak demand hours to minimize the impact on the grid. The methodology assumes three different strategies for the recharge activities: home, public buildings, and electrical stations. It has been applied to the case of Spain in the year 2030, assuming three different scenarios for the growth of the total fleet: low, medium, and high. For each of them, three different levels for the EV penetration by the year 2030 are considered: 25%, 50%, and 75%, respectively. Only light electric vehicles (LEV), cars and motorcycles, are taken into account given the fact that batteries are not yet able to provide the full autonomy desired by heavy vehicles. Moreover, heavy vehicles have different travel uses that should be separately considered. Results for the fraction of the total recharge to be made in each of the different recharge modes are deduced with indication of the time intervals to be used in each of them. For the higher penetration scenario, 75% of the total park, an almost flat electricity demand curve is obtained. Studies are made for working days and for non-working days.

Structure design and coordinated control of electromagnetic and frictional braking system based on a hub motor

A new type of built-in composite electromagnetic and frictional braking structural scheme and its corresponding coordinated control strategy were proposed to enhance the braking effects for the electric vehicle. Fuzzy control theory was applied to design the coordinated control strategy for the electromagnetic and frictional braking system. In comparison to lower braking strength and moderate braking strength, the slip ratio of high braking strength was maintained at near 0.15. It effectively avoided the wheel getting locked and provided relatively large braking torque in the process of braking. The integrated system using a fuzzy control strategy can effectively shorten the braking time, enhance the braking safety in the braking process.

Recent progress in battery electric vehicle noise, vibration, and harshness

As battery electric vehicle (BEV) market share grows so must our understanding of the noise, vibration, and harshness (NVH) phenomenon found inside the BEVs which makes this technological revolution possible. Similar to the conventional vehicle having encountered numerous NVH issues until today, BEV has to face many new and tough NVH issues. For example, conventional vehicles are powered by the internal combustion engine (ICE) which is the dominant noise source. The noises from other sources were generally masked by the combustion engine, thus the research focus was on the reduction of combustion engine while less attention was paid to noises from other sources. A BEV does not have ICE, automatic transmission, transfer case, fuel tank, air intake, or exhaust systems. In their place, there is more than enough space to accommodate the electric drive unit and battery pack. BEV is quieter without a combustion engine, however, the research on vehicle NVH is even more significant since the elimination of the combustion engine would expose many noise behaviors of BEV that were previously ignored but would now seem clearly audible and annoying. Researches have recently been conducted on the NVH of BEV mainly emphasis on the reduction of noise induced by powertrain, tire, wind and ancillary system and the improvement of sound quality. This review paper will focus on recent progress in BEV NVH research to advance the BEV systems in the future. It is a review for theoretical, computational, and experimental work conducted by both academia and industry in the past few years.

Long-term production technology mix of alternative fuels for road transport: A focus on Spain

Road transport is one of the main sources of greenhouse gas emissions due to the current dependence on fossil fuels such as diesel and gasoline. This situation needs to be changed through the retirement of fossil fuels and the implementation of alternative fuels and vehicles such as biofuels, battery electric vehicles, and fuel cell electric vehicles fuelled by hydrogen. Nevertheless, the environmental suitability of alternative fuels is conditioned by how they are produced. Through the case study of Spain, this article prospectively assesses - from a techno-economic and carbon footprint perspective- the production technology mix of alternative fuels from 2020 to 2050. The proposed energy systems optimisation model includes a large number of production technologies regarding biofuels (bioethanol, biodiesel, synthetic diesel/gasoline, and hydrotreated vegetable oil), electricity, and hydrogen. The combined study of these fuels provides a relevant framework to discuss the targets established for the road transport sector with a high level of detail not only regarding fuel type but also technology breakdown. The results show the relevance of second-generation biofuel production technologies in fulfilling the future biofuel demand. Regarding the extra electricity demand associated with the penetration of electric vehicles, the results suggest a key role of wind- and solar-based technologies in meeting such a need. Concerning hydrogen as an option to decarbonise the transport system, even though steam methane reforming is the most mature and cost-competitive production technology, hydrogen production would be satisfied through electrolysis in order to avoid relying on fossil resources as the main feedstock. Overall, this integrated approach to the long-term production technology mix of alternative fuels for road transport is expected to be relevant to a wide range of decision-makers willing to prospectively assess road transport systems from a technology perspective.

Environmental concerns and switching toward electric vehicles: geographic and institutional perspectives

Smog pollution deteriorates environmental quality and has severe health risks. This affects the daily lives of people in China, particularly in urban areas. Along with other factors, a large portion for smog comes from transportations, making it dense and more hazardous in urban areas. The Chinese government aims to reduce air pollution by promoting electric vehicles and green modes for mobility along with other environmental protection measures. The study explores the switching intentions of people from motorized vehicles to electric vehicles by integrating push-pull-mooring model and institutional theory. The study incorporates environmental quality, regulative environment, alternative attractiveness, normative environment, self-(decision)efficacy, and willingness to pay into an integrated framework. The study further analyzes the green behavior of consumers by extending switching intentions for electric vehicles. The integrated framework explains mooring as the most influential factor followed by normative environment from pull factors and environmental quality from push factors. The effect of regulative environment remains weak and significant, but the effect of alternative attractiveness remains weak and insignificant. The switching intentions strongly and significantly explain green behavior. Furthermore, mooring moderates the relationship between push factors, some of the pull factors, and switching intentions.

Indirect Carbon Emissions and Energy Consumption Model for Electric Vehicles: Indian Scenario

The environment-friendly nature of E-vehicles (electric vehicles) coupled with higher energy efficiency has increased their popularity in the automotive industry. A detailed study has been conducted in this article to evaluate the role of the energy mix for electricity generation at the charging locations in secondary C emissions from E-vehicles. The E-vehicle market is booming in India. Evaluation of indirect C emissions was conducted for 3 energy mix scenarios in India, and the results showed that in the present energy mix scenario, E-vehicle emissions will be more than that of conventional-fuel-based vehicles. An energy consumption model for the E-vehicle was also developed in this article using MATLAB Simulink, by considering road slope and driving conditions as input parameters. The developed model was tested for 3 driving conditions, namely (i) Flat road at a constant speed, (ii) Extra Urban Driving Cycle (EUDC), and (iii) Real-time driving condition, to estimate the relation between the energy consumption pattern and the driving range with road slope. Simulation results showed variation in the driving range of the E-vehicles regarding input parameters like road slope and vehicle speed. Therefore, this model could serve as an effective tool for establishing charging stations at strategic locations. Integr Environ Assess Manag 2020;16:998-1007. © 2020 SETAC.

Construction of electric vehicle driving cycle for studying electric vehicle energy consumption and equivalent emissions

This paper proposes an effective and scientific method for the construction of a representative driving cycle for electric vehicles (EV) and takes it as a foundation for studying the energy consumption and equivalent emissions for EV. First, a test route is developed through the analysis of the topology of the Xi'an road structure and traffic flow. Second, the vehicle driving pattern data is gathered through an integrated method of chase car method and on-board method. The velocity-acceleration (V-A) grid method is used to divide speed and acceleration data into micro-states. Third, the proposed driving cycle construction method incorporates the Markov chain and Monte Carlo (MCMC) simulation method. Then, a filter process is designed to screen out the most representative driving cycle. Finally, the comparison of the simulation result and test results shows the constructed EV driving cycle is in line with reality, and estimating the EV's energy consumption per kilometer, driving range, and equivalent emissions under official driving cycles results in large relative errors. Therefore, the construction of a real-world driving cycle for specific cities or areas is necessary to evaluate energy consumption, driving range, and equivalent emissions of EV.