Adaptive mpc based real-time energy management strategy of the electric sanitation vehicles
Authors:
- Hao Wang,
- Hongwen He,
- Jianwei Li,
- Yunfei Bai,
- Yuhua Chang,
- Beizhan Yan
Abstract
Electric sanitation vehicles have increasingly been applied to cleaning work due to the requirement of air pollution control. The power distribution and energy management strategy (EMS) influence the vehicle’s performance a lot both in the aspects of cleaning effect and electricity consumption. Aiming to improve energy economy and ensure clean tasks, first, the electricity consumption percentages of the vehicle onboard devices are analyzed and the main contributors are clarified, and the power requirement model of the working motor is built based on experimental data. Second, a universal modeling method of garbage distribution on the road surface is proposed, which implements a nonlinear autoregressive neural network as the predictor. Third, an adaptive model predictive control (AMPC)-based EMS is proposed and verified. The results show the AMPC method can accurately predict the garbage density and the proposed EMS can approximate the energy consumption of the DP-based EMS with little deviation. Compared to conventional rule-based EMS, the AMPC-based EMS achieved a 15.5% decrease in energy consumption as well as a 14.6% decrease in working time.
- Record ID
- WUT2ecd418ba4014987a37060cb9b4abbb1
- Author
- Journal series
- Applied Sciences-Basel, ISSN 2076-3417
- Issue year
- 2021
- Vol
- 11
- Pages
- 1-24
- Publication size in sheets
- 1.15
- Keywords in English
- adaptive model predictive control (AMPC); nonlinear autoregressive neural network; electric sanitation vehicle; energy management strategy; dynamic programming
- ASJC Classification
- ; ; ; ; ;
- DOI
- DOI:10.3390/app11020498 Opening in a new tab
- URL
- https://www.mdpi.com/2076-3417/11/2/498/htm Opening in a new tab
- Language
- (en) English
- File
-
- File: 1
- applsci-11-00498-v2.pdf
-
- Score (nominal)
- 70
- Score source
- journalList
- Score
- = 70.0, 17-06-2021, ArticleFromJournal
- Publication indicators
- = 0; = 0; : 2018 = 0.985; : 2018 = 2.217 (2) - 2018=2.287 (5)
Share
- Uniform Resource Identifier
- https://repo.pw.edu.pl/info/article/WUT2ecd418ba4014987a37060cb9b4abbb1/
- URN
urn:pw-repo:WUT2ecd418ba4014987a37060cb9b4abbb1
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or PerishOpening in a new tab system.