Chapter 192: Integration of torque blending and slip control using nonlinear model predictive control

Simple item page
dc.contributor.authorBasrah, M. Sofian
dc.contributor.authorSiampis, Efstathios
dc.contributor.authorVelenis, Efstathios
dc.contributor.authorCao, Dongpu
dc.contributor.authorLongo, Stefano
dc.date.accessioned2016-09-29T18:47:09Z
dc.date.available2016-09-29T18:47:09Z
dc.date.issued2016-09-30
dc.description.abstractAntilock Braking System (ABS) is an important active safety feature in preventing accidents during emergency braking. Electrified vehicles which include both hydraulic and regenerative braking systems provide the opportunity to implement brake torque blending during slip control operation. This study evaluates the design and implementation of a new torque allocation algorithm using a Nonlinear Model Predictive Control (NMPC) strategy that can run in real-time, with results showing that wheel-locking can be prevented while also permitting for energy recuperation.en_UK
dc.identifier.citationBasrah MS, Siampis E, Velenis E, et al., (2016) Chapter 192: Integration of torque blending and slip control using nonlinear model predictive control. In: 13th International Symposium on Advanced Vehicle Control, AVEC'16, 13-16 September 2016, Munich, Germany, pp. 585-592en_UK
dc.identifier.urihttps://doi.org/10.1201/9781315265285
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/10633
dc.language.isoenen_UK
dc.publisherUnknownen_UK
dc.rightsAttribution-NonCommercial 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subjectBrakeen_UK
dc.subjectactive safetyen_UK
dc.subjectfull-electric vehiclesen_UK
dc.subjecthybrid electric vehiclesen_UK
dc.titleChapter 192: Integration of torque blending and slip control using nonlinear model predictive controlen_UK
dc.typeConference paperen_UK

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Integration_of_torque_blending_and_slip_control-2016.pdf
Size:
668.4 KB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.79 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Staff publications (SATM)