moln-baserad modellering och optimering av styrsystem till plu-in-hybridfordon med användande av artificiell
Forskningsprojekt , 2018

This proposal formulates a real time implementable energy management strategy (EMS) for plug-in hybrid electric vehicles (PHEV). The artificial intelligence (AI) techniques employ for modelling and optimization the PHEV control parameters to minimize vehicle energy consumption. Three different levels of system upgrading will happen: A primary physical model to generate the initial control rules, upgrade the rules using a hybrid rig and finally optimizing the control setting by communication between PHEVs and a central cloud. The control rules generated in the first step will be uploaded on a programable EMS. A wireless communication system implements between the EMS and a Cloud-based model. The system verification will happen using a PHEV hardware-in-the-loop (HiL) system. Finally, in a real driving cycle the online calibration of a PHEV will be done to validate the system for online optimization based on the cycle, traffic and driver pattern recognition.

Deltagare

Jonas Sjöblom (kontakt)

Docent vid Chalmers, Mekanik och maritima vetenskaper, Förbränning

Ali Ghanaati

vid Chalmers, Mekanik och maritima vetenskaper, Förbränning

Samarbetspartners

Kompetenscentrum i förbränningsmotorteknik

Gothenburg, Sweden

Finansiering

Chalmers

Finansierar Chalmers deltagande under 2018

Relaterade styrkeområden och infrastruktur

Hållbar utveckling

Drivkrafter

Transport

Styrkeområden

Publikationer

Mer information

Senast uppdaterat

2019-09-03