Sliding mode control optimization method using fuzzy-gain scheduling for regenerative braking system
Electric Vehicle (EV) is the alternative method to Internal Combustion Engine (ICE) that may cause environment pollution due to high consumption of fossil fuels. In general, EV is implementing with Regenerative Braking System (RBS) technology to capture wasted heat energy and convert into electrical...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Published: |
Institute of Advanced Scientific Research
2020
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/85832/ http://www.jardcs.org/archivesview.php?volume=3&issue=28&page=6 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Electric Vehicle (EV) is the alternative method to Internal Combustion Engine (ICE) that may cause environment pollution due to high consumption of fossil fuels. In general, EV is implementing with Regenerative Braking System (RBS) technology to capture wasted heat energy and convert into electrical energy for future usage. This research applied parallel braking force distribution with three difference distribution methods such as Advanced Vehicle Simulator (ADVISOR) default strategy, Average and Integrated. In addition, the super-twisting sliding mode control (SMCST) was attached to improve the performance. In order to enhance the robustness of the controller, Fuzzy Gain scheduling method as optimization was introduce. The simulation result was validate using ADVISOR. |
|---|