• Energy Research
• US close
• CN close
• IT close
• CA close
• Transport Research close

Electric vehicles are an important part of governments’ environmental policies, and therefore understanding the factors affecting their market share is very important. So, this research is designed to investigate the factors affecting electric vehicle adoption, considering the effects of the COVID-19 pandemic and sustainable development level. Effective factors have been investigated in three categories. One is the characteristics of electric vehicles; the other is the impact of the COVID-19 pandemic on demand for these vehicles; and finally, the impact of the level of sustainable development of countries on adopting electric vehicles. Our analysis method is based on grey econometric and grey regression methods. The results show that vehicle dimensions, battery warranty conditions, battery life, and charging facilities are effective factors in the field of vehicle characteristics that can increase the adoption of electric vehicles. Also, the analysis shows that the COVID-19 pandemic has reduced the adoption of electric vehicles. Finally, we have shown that the market share of electric vehicles is higher in countries with a higher sustainable development level because of better economic, social, and cultural infrastructures.

The Africa Infrastructure Country Diagnostic (AICD) has gathered and analyzed extensive data on infrastructure in more than 40 Sub-Saharan countries, including Cape Verde. The results have been presented in reports covering several sectors—ICT, irrigation, power, transport, water and sanitation— and various policy areas, including investment needs, fiscal costs, and sector performance. This report presents the key AICD findings for Cape Verde, allowing the country’s infrastructure situation to be benchmarked against that of its African peers. Given that Cape Verde is a relatively well- off middle-income country, its performance will be benchmarked against that of other middle-income countries in Africa. Detailed comparisons will also be made with immediate regional neighbors in the Economic Community of West African States (ECOWAS), and where relevant, with other island states that face a similar set of infrastructure challenges.

The dual-motor EV (Electric Vehicle) is increasingly favored by manufacturers for its excellent performance in terms of power and economy. How to further reduce its energy consumption and make full use of the dual-motor energy recovery is an important support to improve the overall vehicle economy and realize the “dual carbon” strategy. For the dual-motor EV architecture, the motor model, power battery loss model and vehicle longitudinal braking force model are established and the energy recovery-dominated regenerative braking torque distribution (RBD) rule of the dual motors is designed. Based on genetic algorithm (GA) theory and taking into account SOC, vehicle speed and braking intensity, a regenerative-braking torque optimization method is proposed that integrates energy recovery and braking stability. The braking intensity of 0.3 and the initial vehicle speed of 90 km/h are selected for verification. Compared with the rule method, the energy recovery and stability are improved by 22.8% and 4.8%, respectively, under the genetic algorithm-based and energy recovery-dominated regenerative-braking torque distribution (GA-RBD) strategy. A variety of conditions are selected for further strategy validation and the result shows that compared with the rule-based method, both energy recovery and braking stability are improved as braking speed and braking intensity increase under the GA-RBD strategy.

In Eastern Boundary Upwelling Systems nutrient-rich waters are transported to the ocean surface, fuelling high photoautotrophic primary production. Subsequent heterotrophic decomposition of the produced biomass increases the oxygen-depletion at intermediate water depths, which can result in the formation of oxygen minimum zones (OMZ). OMZs can sporadically accumulate hydrogen sulfide (H2S), which is toxic to most multicellular organisms and has been implicated in massive fish kills. During a cruise to the OMZ off Peru in January 2009 we found a sulfidic plume in continental shelf waters, covering an area >5500 km(2), which contained ∼2.2×10(4) tons of H2S. This was the first time that H2S was measured in the Peruvian OMZ and with ∼440 km(3) the largest plume ever reported for oceanic waters. We assessed the phylogenetic and functional diversity of the inhabiting microbial community by high-throughput sequencing of DNA and RNA, while its metabolic activity was determined with rate measurements of carbon fixation and nitrogen transformation processes. The waters were dominated by several distinct γ-, δ- and ε-proteobacterial taxa associated with either sulfur oxidation or sulfate reduction. Our results suggest that these chemolithoautotrophic bacteria utilized several oxidants (oxygen, nitrate, nitrite, nitric oxide and nitrous oxide) to detoxify the sulfidic waters well below the oxic surface. The chemolithoautotrophic activity at our sampling site led to high rates of dark carbon fixation. Assuming that these chemolithoautotrophic rates were maintained throughout the sulfidic waters, they could be representing as much as ∼30% of the photoautotrophic carbon fixation. Postulated changes such as eutrophication and global warming, which lead to an expansion and intensification of OMZs, might also increase the frequency of sulfidic waters. We suggest that the chemolithoautotrophically fixed carbon may be involved in a negative feedback loop that could fuel further sulfate reduction and potentially stabilize the sulfidic OMZ waters.

The present study aims to evaluate the difference in the fluid-dynamic behavior of an overtopping wave energy converter under the incidence of irregular waves based on a realistic sea state when compared to the incidence of regular waves, representative of this sea state. Thus, the sea data of three regions from the Rio Grande do Sul coast, Brazil, were considered. Fluent software was employed for the computational modeling, which is based on the finite volume method (FVM). The numerical generation of waves occurred through the imposition of the velocity boundary conditions using transient discrete values through the WaveMIMO methodology. The volume of fluid (VOF) multiphase model was applied to treat the water–air interaction. The results for the water amount accumulated in the device reservoir showed that the fluid-dynamic behavior of the overtopping converter has significant differences when comparing the two proposed approaches. Differences up to 240% were found for the water mass accumulated in the overtopping device reservoir, showing evidence that the results can be overestimated when the overtopping device is analyzed under the incidence of the representative regular waves. Furthermore, for all studied cases, it was possible to approximate the water volume accumulated over time in the overtopping reservoir through a first-degree polynomial function.

The COVID-19 pandemic has tremendously affected the whole of human society worldwide. Travel patterns have greatly changed due to the increased risk perception and the governmental interventions regarding COVID-19. This study aimed to identify contributing factors to the changes in public and private transportation mode choice behavior in China after COVID-19 based on an online questionnaire survey. In the survey, travel behaviors in three periods were studied: before the outbreak (before 27 December 2019), the peak (from 20 January to 17 March 2020), and after the peak (from 18 March to the date of the survey). A series of random-parameter bivariate Probit models was developed to quantify the relationship between individual characteristics and the changes in travel mode choice. The key findings indicated that individual sociodemographic characteristics (e.g., gender, age, ownership, occupation, residence) have significant effects on the changes in mode choice behavior. Other key findings included (1) a higher propensity to use a taxi after the peak compared to urban public transportation (i.e., bus and subway); (2) a significant impact of age on the switch from public transit to private car and two-wheelers; (3) more obvious changes in private car and public transportation modes in more developed cities. The findings from this study are expected to be useful for establishing partial and resilient policies and ensuring sustainable mobility and travel equality in the post-pandemic era.

Recently, a traction blockade in the depots of numerous electric multiple units (EMUs) of high-speed railways has occured and resulted in some accidents in train operation. The traction blockade is caused by the low-frequency oscillation (LFO) of the vehicle–grid (EMUs–traction network) system. To suppress the LFO, a scheme of EMUs line-side converter based on the H∞ control is proposed in this paper. First, the mathematical model of the four-quadrant converter in EMUs is presented. Second, the state variables are determined and the weighting functions are selected. Then, an H∞ controller based on the dq coordinate is designed. Moreover, compared with the simulation results of traditional proportional integral (PI) control, auto-disturbance rejection control (ADRC) and multivariable control (MC) based on Matlab/Simulink and the RT-LAB platform, the simulation results of the proposed H∞ control confirm that the H∞ controller applied in EMUs of China Railway High-Speed 3 has better dynamic and static performances. Finally, a whole cascade system model of EMUs and a traction network is built, in which a reduced-order model of a traction network is adopted. The experimental results of multi-EMUs accessed in the traction network indicate that the H∞ controller has good suppression performance for the LFO of the vehicle–grid system. In addition, through the analysis of sensitivity of the H∞ controller and the traditional PI controller, it is indicated that the H∞ controller has better robustness.