Simulation of Electric Vehicle Charging Points Based on Efficient Use of Chargers and Using Recuperated Braking Energy from Trains

Electric vehicles represent an innovation in mobility that can help significantly reduce greenhouse emissions and mitigate climate change. However, replacing internal combustion with electric vehicles is not enough. This replacement needs to be complemented with a change in the energy mix of individual countries towards renewable energy sources and efficient use of electricity generated as a secondary product. Recuperative braking energy from trains can serve as one source of such secondary energy. Following an analysis of recuperative energy generated and analysis of charging requirements of individual electric vehicles, the paper proposes a model of a charging site near train stations. Using this energy to charge electric vehicles helps to reduce energy consumption from the electricity grid and thus reduce carbon emissions. Compared to other articles, the proposed model ensures the efficient use of recuperative braking energy from trains by using the variable charging power function; thereby, the installation of additional battery storage is eliminated. Our model results show that the benefits of a car park with a reservation system near train stations increase the car park efficiency, provide a sufficient number of private charging points, contribute to efficient use of recovered energy, and reduce carbon emissions.

Wireless power transfer system with enhanced efficiency by using frequency reconfigurable metamaterial

The wireless power transfer (WPT) system has been widely used in various fields such as household appliances, electric vehicle charging and sensor applications. A frequency reconfigurable magnetic resonant coupling wireless power transfer (MRCWPT) system with dynamically enhanced efficiency by using the frequency reconfigurable metamaterial is proposed in this paper. The reconfigurability is achieved by adjusting the capacitance value of the adjustable capacitor connected in the coil of the system. Finite element simulation results have shown that the frequency reconfigurable electromagnetic metamaterial can manipulate the direction of the electromagnetic field of the system due to its abnormal effective permeability. The ultra-thin frequency reconfigurable metamaterial is designed at different working frequencies of 14.1 MHz, 15 MHz, 16.2 MHz, 17.5 MHz, 19.3 MHz, 21.7 MHz and 25 MHz to enhance the magnetic field and power transfer efficiency (PTE) of the system. Frequency reconfigurable mechanism of the system with the frequency reconfigurable metamaterial is derived by the equivalent circuit theory. Finally, further measurement which verifies the simulation by reasonable agreement is carried out. PTE of the system by adding the metamaterial are 59%, 73%, 67%, 66%, 65%, 60% and 58% at different working frequencies. PTE of the system with and without the metamaterial is 72% and 49% at the distance of 120 mm and the frequency of 15 MHz, respectively.

Impacts of COVID-19 on Electric Vehicle Charging Behavior: Data Analytics, Visualization, and Clustering

COVID-19 pandemic has infected millions and led to a catastrophic loss of lives globally. It has also significantly disrupted the movement of people, businesses, and industries. Additionally, electric vehicle (EV) users have faced challenges in charging their vehicles in public charging locations where there is a risk of COVID-19 exposure. However, a case study of EV charging behavior and its impacts during the SARS-CoV-2 is not addressed in the existing literature. This paper investigates the impacts of COVID-19 on EV charging behavior by analyzing the charging activity during the pandemic using a dataset from a public charging facility in the USA. Data visualization of charging behavior alongside significant timelines of the pandemic was utilized for analysis. Moreover, a cluster analysis using k-means, hierarchical clustering, and Gaussian mixture models was performed to identify common groups of charging behavior based on the vehicle arrival and departure times. Although the number of vehicles using the charging station was reduced significantly due to lockdown restrictions, the charging activity started to pick up again since May 2021 due to an increase in vaccination and easing of public restrictions. However, the charging activity currently still remains around half of the activity pre-pandemic. A noticeable decline in charging session length and an increase in energy consumption can be observed as well. Clustering algorithms identified three groups of charging behavior during the pandemic and their analysis and performance comparison using internal validation measures were also presented.