A5079973853- Advanced Battery Technologies Research
- Advancements in Battery Materials
- Advanced machining processes and optimization
- Fault Detection and Control Systems
- Injection Molding Process and Properties
- Distributed and Parallel Computing Systems
- Metal Alloys Wear and Properties
- Tunneling and Rock Mechanics
- Educational Innovations and Challenges
- Advanced Decision-Making Techniques
- E-Learning and Knowledge Management
- Manufacturing Process and Optimization
- Software System Performance and Reliability
- Electric Vehicles and Infrastructure
- Video Surveillance and Tracking Methods
- Metallurgy and Material Forming
- Sensor Technology and Measurement Systems
- Educational Technology and Assessment
- Higher Education Learning Practices
- Robotic Path Planning Algorithms
- Autonomous Vehicle Technology and Safety
- Brake Systems and Friction Analysis
- Power Systems and Technologies
- Advanced Neural Network Applications
- Industrial Technology and Control Systems
Beijing Information Science & Technology University
2024
Central South University
2020-2022
University of Science and Technology Liaoning
2013
Shenyang University
2007
In recent years, with the continuous development of autonomous driving technology, 3D object detection has naturally become a key focus in research perception systems for driving. As most crucial component these systems, gained significant attention. Researchers increasingly favor deep learning framework Transformer due to its powerful long-term modeling ability and excellent feature fusion advantages. A large number Transformer-based methods have emerged. This article divides based on data...
Predicting the discharge time of lithium-ion batteries is an important issue in battery management system. Accurate prediction can avoid accidents, thereby improving safety entire In order to overcome challenge such as need identify model parameters related research, this paper proposes a new method based on Peukert's law. Firstly, Peukert constant fitted by experimentally measured data, and then experiment data are used predict calculate relative error. Secondly, according error between...
Different from previous data-driven methods for lithium-ion battery State-of-Charge (SoC) estimation, this paper aims to develop a hierarchical SoC estimation method address the data dependency issue and measurement noise interferences. In off-line training layer, aging-aware features are extracted improve accuracy throughout entire life cycle. Extreme gradient boosting (XGBoost) is introduced map relationship between its strong nonlinear fitting ability. on-line Ampere-hour integral...
This paper investigates a hybrid instructional design to improve the educational outcomes of "Software Project Management" course. Confronted with challenges globalization and rapid technological progress, traditional lecture-based teaching has proven inadequate fulfill goals contemporary education. The model merges online self-directed learning in-person interactive sessions, facilitating acquisition application knowledge enhancement practical skills through pre-class video instruction,...