معرفی
Ye Xu serves as Associate Senior Lecturer in the Department of Computer and Electrical Engineering at Mid Sweden University, Sundsvall, specializing in energy harvesting systems for autonomous sensing applications. Based in room S220, Xu's work bridges electrical engineering and mechanical design to develop self-powered monitoring solutions for industrial systems.
Education:
- PhD in Electrical Engineering, Mid Sweden University (2022), Thesis: Rotational Electromagnetic Energy Harvesting Through Variable Reluctance
Xu's research centers on variable reluctance energy harvesting, with expertise in rotational and vibration systems. Key contributions include Halbach array optimization, multi-phase harvester design, and ortho-planar spring mechanisms for vibration energy conversion. Recent work integrates edge computing for structural health monitoring, enabling on-device crack segmentation in resource-constrained environments.
Analysis of Xu's 15 most recent publications (2018-2025) reveals consistent focus on rotational energy harvesting, evolving from fundamental modeling (2019-2021) to smart bearing applications (2024-2025). The research trajectory shows increasing integration of mechanical design, electromagnetic theory, and embedded systems for industrial IoT solutions, particularly in vehicle electrification through the DeHigh project.
Scientific Awards:
- No major awards documented in available sources
Advising and Grants: While Xu completed doctoral studies in 2022 and holds a faculty position, specific student supervision details are unlisted. Current research is supported through the DeHigh project (electrification of work vehicles), though granular grant information isn't publicly detailed. Xu likely mentors graduate students in energy harvesting system design based on publication patterns.
Xu operates within the STC Research Centre at Mid Sweden University, collaborating on low-voltage electrification projects. The DeHigh initiative represents a key current effort, developing variable reluctance harvesters for work vehicle monitoring systems. Future work appears directed toward industrial implementation of self-powered sensors for predictive maintenance in rotating machinery.