Linni Jian’s research while affiliated with City University of Hong Kong and other places

Wireless electric vehicle charging (WEVC) is rapidly advancing as an enabling technology for convenient electrified transportation. The trend toward high-power WEVC systems is accelerating, which not only enhances charging speed and user convenience but also introduces new and complex safety challenges. These challenges are particularly acute at the coupler level, where electrical, thermal, and magnetic risks often interact. This review offers a comprehensive analysis of safety management technologies that are specific to WEVC, with an exclusive focus on coupler-related risks. System-level and coupler-level hazards associated with high-power operation are first examined, followed by an in-depth discussion of recent progress in passive safety materials, such as insulation, thermal dissipation, and electromagnetic shielding. Active safety management strategies are also reviewed in detail, including foreign object detection, live body detection, misalignment detection, and multifunctional detection schemes that integrate these capabilities. Emphasis is placed on the ongoing rapid iteration of safety technologies as power levels increase and on the necessity for solutions that are comprehensive, precise, orderly, and reliable. This review concludes by highlighting future research directions, such as data-driven safety management, intelligent sensor integration, regulatory evolution, and user-centered system design, aiming to support the safe and scalable deployment of WEVC in next-generation mobility.

With the growing use of unmanned surface vehicles (USVs) for underwater exploration, efficient wireless charging solutions like inductive power transfer (IPT) are crucial for addressing power limitations. This paper presents a novel IPT system for USVs and introduces a systematic design approach for optimizing magnetic couplers. The proposed design addresses three critical challenges: misalignment tolerance, lightweight construction, and thermal safety, which are intricately linked through a magnetic field. In terms of misalignment, this paper demonstrates that the coil length is a key factor in determining misalignment tolerance. For a lightweight design, replacing the ferrite plate with ferrite bars can significantly reduce the weight of the coupler without causing core saturation. The design is further validated through a two-way coupled electromagnetic–thermal simulation. The results reveal that, with proper thermal management, the system avoids thermal risks in underwater environments compared to air. Finally, a 3 kW prototype is constructed and tested in fresh water, achieving 55 V and 50 A wireless charging at an 85.7% full-load dc-to-dc efficiency, thus confirming the practicality and performance of the design.

The purpose of this article is to propose a value-oriented electrical load forecasting (ELF) approach that aims to minimize load variance by leveraging vehicle-to-grid (V2G) technology. To achieve this, it is critical and urgent to design a loss function that can accurately measure the suboptimality of decisions induced by forecast errors, especially since the commonly used mean squared error (MSE) falls short in this regard. The Lagrange multiplier method and Karush–Kuhn–Tucker conditions are initially used to elucidate the impact of forecast errors on the actual charging power of electric vehicles. Building on this foundation, a differentiable loss function called mean relative magnitude error (MRME) is put forward for value-oriented ELF, which allows parameter updates in the long short-term memory (LSTM) model via the gradient descent method during the training stage. Furthermore, the MRME and MSE loss functions are combined using a weighted sum method to leverage their respective advantages. Numerous case studies have demonstrated that the LSTM model, whether using MRME alone or in combination with MSE, achieves superior and more robust V2G scheduling performance compared to using MSE alone. The weight coefficients for combining MRME and MSE loss functions are also discussed.

As wireless electric vehicle charging (WEVC) technology moves toward commercialization, understanding its associated risks is crucial, particularly with the trend toward high-power fast charging. In this paper, thermal risks and factors exacerbating the risks in wireless EV chargers are investigated comprehensively, focusing on the magnetic coupler and foreign objects (FOs) intruding on the charging area. The power losses and temperatures of the coupler and FOs are obtained using a two-way electromagnetic-thermal coupled model, and the coupler will be assigned to a risk level according to the proposed four-temperature-level risk evaluation mechanism. In this model, practical considerations include coil types, misalignments, FO materials, ambient temperatures, etc. Moreover, a dynamic perspective is used to characterize the trend of risks so as to provide predictive insights. To validate the newly identified risks, two 6.6-kW WEVC prototypes are built employing circular coils and DD coils, respectively. Experimental studies confirm the necessity of implementing thermal risk management strategies for magnetic coupler under misaligned conditions such as enhanced cooling, including a wider range of materials for foreign object detection (FOD), expanding the FOD area, and so forth.