Electric Vehicle Charging Technology Research Articles

Challenges Ahead

How smart electric vehicle charging technology and engineering will make the electric future possible

Evolution of Hybrid Inductive and Capacitive AC Links for Wireless EV Charging—A Comparative Overview

The inductive link in a wireless power transfer (WPT) system, fed by various high-frequency power converters with appropriate control strategies is widely accepted for medium power ( 95%) in static wireless charging scenarios. However, considering the dynamic wireless charging, the inductive link implementation for millions of kilometers is quite expensive due to the need for sophisticated resources. Therefore, relatively low-cost capacitive link, which initially focused on low power ( 90%) and significant misalignment tolerance. This paper aims to find the significant roles played by inductive and capacitive ac link designs in static and dynamic expansion of wireless electric vehicle (EV) charging. Through a relative analysis, this paper emphasizes the need for mutual promotion of these ac links as a hybrid system in order to boost wireless EV charging technology.

Design considerations, modelling, and control of dual‐active full bridge for electric vehicles charging applications

The dual active full bridge (DAFB) is one of the promising isolated DC/DC converter topologies that will play a significant role in the future of electric vehicle (EV) integration in smart grids (SGs). This is due to its inherent soft switching and control simplicity. Therefore, this study presents first the latest developments related to the design of DAFB converter in EV charging technology. It provides a brief discussion of the crucial recommendations regarding the reliability, efficiency, system configuration, EV charger control scheme, battery lifetime, and system materials. Then, it presents a step-by-step modelling approach for a non-ideal DAFB for the purpose of designing its controller. In addition, the model provided by this study includes all non-idealities due to the high-frequency (HF) transformer, semiconductor switches, passive components, and digital system delays. Eventually, the proposed system design and analysis was validated by implementing a 6.1 kW prototype on Simulink and Typhoon-HIL real-time simulator.

High thermal conductivity insulation and sheathing materials for electric vehicle cable application

Polymeric insulated cable with high ampacity and good thermal performance is the core of the new fast charging technology for electric vehicles (EVs). Advanced materials with both good thermal and electrical properties to improve the performance of EVs charging cable are proposed in this paper. Two sample cables were manufactured with ethylene-propylene-diene (EPDM) insulation and a chlorosulfonated polyethylene rubber (CSM) sheath. Both the insulation and sheathing materials were modified by hybrid boron nitride (BN) to improve the thermal conductivity (TC). The test results show that the modified EPDM insulation has good electrical and mechanical properties. For the temperature characteristics of these two cables, the adoption of high TC EPDM insulation and CSM sheath can improve the heat dissipation capability and the temperature distribution in the cable. In addition, the theoretical ampacity of the cable was calculated showing a significant improvement. The employment of high TC insulation and sheath appears to be of great benefit to the reduction of temperature and increase in ampacity of EV charging cables.

Smart Grid R&D Planning Based on Patent Analysis

A smart grid employs information and communications technology to improve the efficiency, reliability, economics, and sustainability of electricity production and distribution. The convergent and complex nature of a smart grid and the multifarious connection between its individual technology components, as well as competition between private companies, which will exert substantial influences on the future smart grid business, make a strategic approach necessary from the beginning of research and development (R&D) planning with collaborations among various research groups and from national, industry, company, and detailed technological levels. However, the strategic, technological, business environmental, and regulatory barriers between various stakeholders with collaborative or sometimes conflictive interests need to be clarified for a breakthrough in the smart grid field. A strategic R&D planning process was developed in this study to accomplish the complicated tasks, which comprises five steps: (i) background research of smart grid industry; (ii) selection of R&D target; (iii) societal, technological, economical, environmental, and political (STEEP) analysis to obtain a macro-level perspective and insight for achieving the selected R&D target; (iv) patent analysis to explore capabilities of the R&D target and to select the entry direction for smart grid industry; and, (v) nine windows and scenario planning analyses to develop a method and process in establishing a future strategic R&D plan. This R&D planning process was further applied to the case of a Korean company holding technological capabilities in the sustainable smart grid domain, as well as in the sustainable electric vehicle charging system, a global consumer market of smart grid. Four plausible scenarios were produced by varying key change agents for the results of this process, such as technology and growth rates, policies and government subsidies, and system standards of the smart grid charging system: Scenario 1, ‘The Stabilized Settlement of the Smart Grid Industry’; Scenario 2, ‘The Short-lived Blue Ocean of the Smart Grid Industry’; Scenario 3, ‘The Questionable Market of the Smart Grid’; and, Scenario 4, ‘The Stalemate of the Smart Grid Industry’. The R&D plan suggestions were arranged for each scenario and detailed ways to cope with dissonant situations were also implied for the company. In sum, in this case study, a future strategic R&D plan was suggested in regard to the electric vehicle charging technology business, which includes smart grid communication system, battery charging duration, service infrastructure, public charge station system, platform and module, wireless charging, data management system, and electric system solution. The strategic R&D planning process of this study can be applicable in various technologies and business fields, because of no inherent dependency on particular subject, like electric vehicle charging technology based on smart grid.

Contactless Charging Technology of Electric Vehicle

The electric vehicle has the advantages of energy-saving, environmental protection, low-carbon economy etc, and the charging system is an indispensable subsystem of electric vehicle. It’s the charging long time and inconvenience of traditional charging mode that makes contactless charging system become the trend of future electric vehicle charging technology development. Firstly, this paper introduces the principle of contactless charging of electric vehicle, analysis the three kinds of charging mode, and then combined with the development of domestic and international situation, puts forward some inevitable problems in reality. Finally, discusses the contactless charging device for electric vehicle application.

How accurate are drivers’ predictions of their own mobility? Accounting for psychological factors in the development of intelligent charging technology for electric vehicles

Intelligent load management systems (ILMS) for electric vehicles (EVs) would make it possible to link EV use to renewable energy sources. ILMS require information about the departure time and length of EV drivers’ upcoming trips to optimize the charging process depending on the availability of renewable energy in the grid. Inaccurate information may lead to insufficient battery levels or inefficient charging processes. In a field test during two weeks 60 participants predicted the departure time and trip length of their upcoming trips after having arrived at home with their own gasoline-powered cars. Actual mobility behavior was assessed by means of logbooks and GPS tracking devices. The results show that participants are on average able to accurately predict their departure times and trip lengths although for some outliers their prediction errors would potentially have led to insufficient battery levels. The type of trip (work, leisure, shopping) significantly influenced the accuracy of mobility predictions.