S&T出版 List of News Articles

Due to the high dv/dt and high frequency of inverter-driven systems, unprecedented electrical stress is being applied to motor insulation. This presentation will discuss the prediction of partial discharge inception voltage, evaluation techniques for insulation material properties, and the various characteristics and material design/exploration techniques of functional and nanocomposite materials, starting from the phenomena of partial discharge and charge transport in insulation materials. Furthermore, with next-generation electric mobility, including aircraft, in mind, the latest trends and future prospects of partial discharge diagnosis using AI will be introduced.

There are many documents that describe analysis and testing methods for polymer materials, but when actually measuring and analyzing data while referring to them, it is common to have doubts or concerns about interpretations, as well as worries about inadvertently making mistakes. This course addresses such situations by summarizing insights gained by the instructor through practical experience in analysis and physical property evaluation, focusing on points of caution and common misunderstandings.

With the spread of EVs, the driving voltage of motors is increasing, and miniaturization is progressing. Consequently, insulation materials for winding coatings must possess not only excellent heat resistance but also advanced insulation performance that can maintain stable operation under high voltage. Additionally, for SiC (silicon carbide) devices used in railways, industrial equipment, and power converters, selecting materials that can withstand harsh high-temperature and high-electric-field environments is urgently needed. Furthermore, similar performance is strongly required for insulation materials used in DC transmission cables that support the long-distance transport of renewable energy. However, there has not been a definitive method established for evaluating insulation properties under such high-temperature and high-electric-field conditions, which has hindered the formulation of guidelines for material development. This course will detail effective measurement methods based on years of research achievements for major polymer insulation materials such as polyimide, epoxy resin, and cross-linked polyethylene, and will introduce typical evaluation cases.

Since the introduction of lithium-ion batteries in 1991, electrodes have been produced in mass production using a method called coating (wet process) up to the present day. I would like to provide an overview of what materials are used and how the coating is done. Additionally, in recent years, solid-state batteries have become a topic of discussion whenever lithium-ion batteries are mentioned. I will explain the types of solid electrolytes and their respective characteristics. I also want to touch on the methods being considered for manufacturing solid-state batteries. In recent years, a new method called the dry process has emerged in electrode manufacturing and has become a topic of interest. The dry process is now gaining attention as one of the manufacturing methods for solid-state batteries. I would like to explain the reasons for this and the current situation.

In conventional systems referred to as ADAS, which correspond to autonomous driving levels 1 to 2, systems were built using standalone sensors such as millimeter-wave radar, monocular cameras, and stereo cameras as external sensors. However, in Honda's autonomous driving level 3, which became the world's first mass-produced model, the system began to be constructed using sensor fusion that incorporates multiple LiDAR units in addition to millimeter-wave radar and monocular cameras. This shift was necessary because, while accidents at level 2 were the driver's responsibility and could tolerate insufficient sensor performance, accidents at level 3 and above are the manufacturer's responsibility, necessitating a significant improvement in performance through the fusion of various sensors. Thus, sensor fusion that incorporates LiDAR as a complement to conventional sensor performance is gaining attention, and LiDAR is included in Lexus's autonomous driving system and Nissan's new technology announcements. In this course, we will introduce the characteristics of conventional ADAS sensors from various companies and the latest autonomous driving sensor situations announced for levels 3 and above, while explaining the technologies of conventional sensors and LiDAR. We will cover the fundamentals to applications of sensor fusion technology that combines these sensors, as well as discuss future technological trends.