On the impact of mobility on battery-less RF energy harvesting system performance
- Submitting institution
-
University of Bedfordshire
- Unit of assessment
- 12 - Engineering
- Output identifier
- 7770421
- Type
- D - Journal article
- DOI
-
10.3390/s18113597
- Title of journal
- Sensors
- Article number
- 3597
- First page
- -
- Volume
- 18
- Issue
- 11
- ISSN
- 1424-8220
- Open access status
- Compliant
- Month of publication
- October
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
1
- Research group(s)
-
B - SCRI - Smart Cities Research Institute
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper proposes a novel approach to predict the amount of ambient RF energy by tracking the collocation time near RF charging stations using Kalman filter and using predicted information to select an energy storage device of an appropriate capacity. The simulation results demonstrate that the proposed scheme can meet the otherwise contradictory requirements and achieve better performance in terms of sensor coverage and amount of usable harvested energy in both low and high energy areas.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -