Application Design Aiming to Minimize Drivers’ Trip Duration through Intermediate Charging at Public Station Deployed in Smart Cities

Today, smart cities are turning to electric transport, carpooling and zero emission zones. The growing number of electric vehicles on the roads makes it increasingly necessary to have a public charging infrastructure. On the other hand, the main limitations of electric vehicles are the limited range of their batteries and their relatively long charging times. To avoid having problems to recharge, electric vehicle drivers must plan their journeys more thoroughly than others. At the goal of optimizing trip time, drivers need to automate their travel plans based on a smart charging solution, which will require the development of new Vehicle-to-Grid applications that will allow at the charging stations to dynamically interact with the vehicles. In this paper, we propose an architecture based on an algorithm allowing the management of charging plans for electric vehicles traveling on the road to their destination, in order to minimize the duration of the drivers&rsquo journey including waiting and charging times. The decision taken by the algorithm based on the exploration of the data of each public supply station according to its location, number of vehicles in the queue, number of charging sockets, and rates of service. Document type: Articl

Stability and Threshold of a Stochastic SIRS Epidemic Model with Vertical Transmission and Transfer from Infectious to Susceptible Individuals

The aim of this paper is to generalize the nonlinear incidence rate of a stochastic SIRS (susceptible-infected-recovered-susceptible) epidemic model. Our basic model was enriched with the hypotheses of vertical transmission and transfer from infected to susceptible individuals, to approach the reality. Our analysis showed that the model is well-posed. Under some conditions imposed on the intensity of the white noise perturbation, the global stability of the system is proven. Furthermore, the threshold of our model which determines the extinction and persistence of the disease is established. Numerical examples are realized to prove the rigor of our theoretical results

Stationary Distribution and Dynamic Behaviour of a Stochastic SIVR Epidemic Model with Imperfect Vaccine

We consider a stochastic SIVR (susceptible-infected-vaccinated-recovered) epidemic model with imperfect vaccine. First, we obtain critical condition under which the disease is persistent in the mean. Second, we establish sufficient conditions for the existence of an ergodic stationary distribution to the model. Third, we study the extinction of the disease. Finally, numerical simulations are given to support the analytical results

Ergodic Stationary Distribution of a Stochastic Hepatitis B Epidemic Model with Interval-Valued Parameters and Compensated Poisson Process

Hepatitis B epidemic was and is still a rich subject that sparks the interest of epidemiological researchers. The dynamics of this epidemic is often modeled by a system with constant parameters. In reality, the parameters associated with the Hepatitis B model are not certain, but the interval in which it belongs to can readily be determined. Our paper focuses on an imprecise Hepatitis B model perturbed by Lévy noise due to unexpected environmental disturbances. This model has a global positive solution. Under an appropriate assumption, we prove the existence of a unique ergodic stationary distribution by using the mutually exclusive possibilities lemma demonstrated by Stettner in 1986. Our main effort is to establish an almost perfect condition for the existence of the stationary distribution. Numerical simulations are introduced to illustrate the analytical results

Predicting potential scenarios for wastewater treatment under unstable physical and chemical laboratory conditions: A mathematical study

This research aims to highlight and examine an example of physical complexity. By taking into account the interference between the components of a bio-reactor chemostat, we introduce a mathematical system with a general functional response that describes the wastewater treatment. This model is disturbed by a new class of fluctuations in the hybrid form which simulates certain unstable chemical and environmental variations. We merge between the polynomial white noise and quadratic jumps to offer an excellent overview of the complexity induced in wastewater treatment. Analytically, we present a surrogate framework to get the acute sill between stationarity and bacteria eradication. Our analysis enriches and improves many works by proposing an unfamiliar form of perturbation and unifying the criteria of said asymptotic characteristics. Numerically, we audit the accuracy of our sill in two non-standard cases: quadratic noise and cross perturbation. We demonstrate that the increased order of perturbation has a significant effect on the elimination of bacterial living time. Furthermore, we numerically show that the steady density function modifies its geometric form at some quantities of noise. This result highlights that the sources of complex fluctuations play an active role in the transient dynamics of real-life systems

Application Design Aiming to Minimize Drivers’ Trip Duration through Intermediate Charging at Public Station Deployed in Smart Cities

Today, smart cities are turning to electric transport, carpooling and zero emission zones. The growing number of electric vehicles on the roads makes it increasingly necessary to have a public charging infrastructure. On the other hand, the main limitations of electric vehicles are the limited range of their batteries and their relatively long charging times. To avoid having problems to recharge, electric vehicle drivers must plan their journeys more thoroughly than others. At the goal of optimizing trip time, drivers need to automate their travel plans based on a smart charging solution, which will require the development of new Vehicle-to-Grid applications that will allow at the charging stations to dynamically interact with the vehicles. In this paper, we propose an architecture based on an algorithm allowing the management of charging plans for electric vehicles traveling on the road to their destination, in order to minimize the duration of the drivers’ journey including waiting and charging times. The decision taken by the algorithm based on the exploration of the data of each public supply station according to its location, number of vehicles in the queue, number of charging sockets, and rates of service

Dynamical bifurcation of a sewage treatment model with general higher-order perturbation

In this research, we expose new results on the dynamics of a high disturbed chemostat model for industrial wastewater. Due to the complexity of heavy and erratic environmental variations, we take into consideration the polynomial perturbation. We scout the asymptotic characterization of our proposed system with a general interference response. It is demonstrated that the long-run characteristics of the chemostat process are classified by using the threshold classification approach. If the critical sill is strictly negative, the bacteria will disappear exponentially, indicating that the chemostat wastewater process is not running (excluded scenario), otherwise, the stationarity and ergodicity properties of our model are verified (practical scenario). The theoretical arsenal of this work offers a comprehensive overview of the industrial wastewater behavior under general hypotheses and introduces novel technical aspects to deal with other perturbed systems in biology. Numerically, we audit the accuracy of our threshold in three particular situations: linear, quadratic and cubic perturbations. We establish that the increasing order of disturbance has a passive influence on the extinction time of bacteria. This finding highlights that complex noise sources fulfill a significant role in the transient dynamics of chemostat systems