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Xin Sui Teaching Portfolio
View Scopus Profile
Xin Sui
Postdoc
,
AAU Energy
Post.Doc.
,
AAU Energy
Postdoc
,
The Faculty of Engineering and Science
Post.Doc.
,
The Faculty of Engineering and Science
Power Electronics System Integration and Materials
Post.Doc.
,
Power Electronics System Integration and Materials
Batteries
https://orcid.org/0000-0002-6180-469X
Email
xin
energy.aau
dk
Pontoppidanstræde 101
,
3-025
9220
Aalborg Ø
Denmark
2019
2024
Research activity per year
Overview
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Network
Projects
(4)
Publications
(46)
Similar Profiles
(12)
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Dive into the research topics where Xin Sui is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Weight
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Engineering
Lithium-Ion Batteries
100%
Estimation
86%
State of Health
59%
Aging
34%
Performance
33%
Electric Vehicle
26%
Temperature
25%
Models
24%
Electric Potential
24%
State of Charge
18%
Battery Management System
18%
Battery Pack
17%
Pitch
17%
Phase Induction Motor
17%
Induction Motor
17%
Experimental Result
16%
Symmetrical Component
16%
Accuracy
16%
Support Vector Machine
16%
Efficiency
16%
Phase Fault
14%
Prediction
14%
Control Strategy
13%
Impedance
13%
Minimization
11%
Applications
9%
Temperature Estimation
9%
Artificial Intelligence
8%
Battery Capacity
8%
Dataset
8%
Optimization
7%
Networks
7%
Feature Extraction
7%
Reliability
7%
Machine Learning Method
7%
Energy Storage System
7%
Simulation Result
7%
Storage
6%
Invariance
6%
Algorithm
6%
Individual Cell
6%
Motor Drive
5%
Fault Tolerant Control
5%
Zeros
5%
Sliding Mode
5%
Power Electronics
5%
Equivalent Circuit Model
5%
Comparative Study
5%
Circuit Faults
5%
Motors
5%
Physics
Battery
56%
Lithium-Ion Batteries
49%
Temperature
31%
Model
25%
Entropy
23%
Electric Battery
19%
Performance
16%
Optimization
13%
Ripples
11%
Motors
11%
Machine Learning
11%
Variations
10%
Information
7%
Electric Potential
6%
Decomposition
5%
Li-Ion Battery
5%
Neural Network
5%
Adaptation
5%
Domains
5%
Physics
5%
Computer Science
Models
31%
Entropy
29%
Accuracy
21%
Machine Learning
17%
Estimation Method
15%
System Management
15%
Support Vector Machine
14%
Ensemble Learning
14%
Algorithms
12%
Induction Phase
11%
Experimental Result
10%
Roles
9%
Extreme Learning Machine
9%
Learning Method
7%
Evaluation
7%
Optimization
5%
Convolutional Neural Network
5%
Postprocessing
5%
Sensor
5%
Domain Adaptation
5%
Detection
5%
Efficient Operation
5%
Digital Twin
5%
Service
5%
