Overview on Digital Twin for Autonomous Electrical Vehicles Propulsion Drive System

The significant progress in the electric automotive industry brought a higher need for new technological innovations. Digital Twin (DT) is one of the hottest trends of the fourth industrial revolution. It allows representing physical assets under various operating conditions in a low-cost and zero-risk environment. DTs are used in many different fields from aerospace to healthcare. However, one of the perspective applications of such technology is the automotive industry. This paper presents an overview of the implementation of DT technology in electric vehicles (EV) propulsion drive systems. A general review of DT technology is supplemented with main applications analysis and comparison between different simulation technologies. Primary attention is given to the adaptation of DT technology for EV propulsion drive systems.

Impact of Charging on Battery Life and Battery Degradation in Electric Vehicles

Electrical vehicles are the future of the world; hence, there is a necessity to pave the way for the upcoming technology and to ensure its contribution to the society fairly. Nevertheless, if the EVs completely replaced the fuel-based cars, more EV charging stations would be needed which might develop overconsumption of the main grid power causing remarkable instability. Consequently, the micro grids become the solution to this problem, in which they are defined as relatively small networks of energy sources and loads at the distribution level that aim to provide electricity to remote locations where the charging stations are located. In this chapter, the EV is considered as a load to the micro grid indirectly through the EV charging stations. Thus, micro grid loads will be retrieved from experimental data of an actual prototype electric vehicle to reflect on the battery degradation in a micro-grid connected system.

Optimal Power Dispatch in Energy Systems Considering Grid Constraints

As a consequence of the increasing share of renewable energies and sector coupling technologies, new approaches are needed for the study, planning, and control of modern energy systems. Such new structures may add extra stress to the electric grid, as is the case with heat pumps and electrical vehicles. Therefore, the optimal performance of the system must be estimated considering the constraints imposed by the different sectors. In this research, an energy system dispatch optimization model is employed. It includes an iterative approach for generating grid constraints, which is decoupled from the linear unit commitment problem. The dispatch of all energy carriers in the system is optimized while considering the physical electrical grid limits. From the considered scenarios, it was found that in a typical German neighborhood with 150 households, a PV penetration of ∼5 kWp per household can lead to curtailment of ∼60 MWh per year due to line loading. Furthermore, the proposed method eliminates grid violations due to the addition of new sectors and reduces the energy curtailment up to 45%. With the optimization of the heat pump operation, an increase of 7% of the self-consumption was achieved with similar results for the combination of battery systems and electrical vehicles. In conclusion, a safe and optimal operation of a complex energy system is fulfilled. Efficient control strategies and more accurate plant sizing could be derived from this work.

SDN-Enabled 3C Resource Integration in Green Internet of Electrical Vehicles

With the advocacy of green renewable energy, Electric Vehicles (EVs) have gradually become the mainstream in the automobile market. Due to the finite edge resources of the Internet of EVs, this paper integrates idle communication, caching and computational resources of EVs to enrich the available resources for vehicular task migration. Considering the limited capacity and resources of EVs, a distributed lightweight imitation learning-based efficient Task cOoperative migration Policy Integrating 3C resource policy, named TOPIC, is proposed to maximize the obtained quality of service. The experimental results based on the real-world traffic dataset of Hangzhou (China) demonstrate the QoS obtained based on the expert policy and agent policy of TOPIC is about 3 times higher than other representative policies.

PV-EV Integrated Home Energy Management Considering Residential Occupant Behaviors

Rooftop photovoltaics (PV) and electrical vehicles (EV) have become more economically viable to residential customers. Most existing home energy management systems (HEMS) only focus on the residential occupants’ thermal comfort in terms of indoor temperature and humidity while neglecting their other behaviors or concerns. This paper aims to integrate residential PV and EVs into the HEMS in an occupant-centric manner while taking into account the occupants’ thermal comfort, clothing behaviors, and concerns on the state-of-charge (SOC) of EVs. A stochastic adaptive dynamic programming (ADP) model was proposed to optimally determine the setpoints of heating, ventilation, air conditioning (HVAC), occupant’s clothing decisions, and the EV’s charge/discharge schedule while considering uncertainties in the outside temperature, PV generation, and EV’s arrival SOC. The nonlinear and nonconvex thermal comfort model, EV SOC concern model, and clothing behavior model were holistically embedded in the ADP-HEMS model. A model predictive control framework was further proposed to simulate a residential house under the time of use tariff, such that it continually updates with optimal appliance schedules decisions passed to the house model. Cosimulations were carried out to compare the proposed HEMS with a baseline model that represents the current operational practice. The result shows that the proposed HEMS can reduce the energy cost by 68.5% while retaining the most comfortable thermal level and negligible EV SOC concerns considering the occupant’s behaviors.

Two-Coil Receiver for Electrical Vehicles in Dynamic Wireless Power Transfer

Dynamic wireless power transfer (DWPT) of electric vehicles (EVs) is the future of urban mobility. The DWPT is often based on a series of short track pads embedded in road pavement that wirelessly transfers electrical energy to EVs equipped with a pickup coil for battery charging. An open problem with this technology is the variation of the coupling factor as a vehicle switches from one transmitting coil to another during its motion. This can cause a significant change in power with possible power spikes and holes. In order to overcome these issues, a new architecture is here proposed based on two pick-up coils mounted in the vehicle underneath. These identical receiver coils are placed in different positions under the vehicle (one in front and the other in the rear) and are activated one at a time so that inductive coupling is always good enough. This innovative configuration has two main advantages: (i) it maintains a nearly constant coupling factor, as well as efficiency and transferred power, as the vehicle moves along the electrified road; (ii) it significantly reduces the cost of road infrastructure. An application is presented to verify the proposed two-coil architecture in comparison with the traditional one-coil. The results of the investigation show the significant improvement achieved in terms of maximum power variation which is nearly stable with the proposed two-coil architecture (only 2.8% variation) while there are many power holes with the traditional single coil architecture. In addition, the number of the required transmitting coils is significantly reduced due to a larger separation between adjacent coils.