000220308 001__ 220308
000220308 005__ 20181012192627.0
000220308 020__ $$a978-961-6980-15-9
000220308 037__ $$aCONF
000220308 245__ $$aEnvironomic design of hybrid electric vehicles
000220308 260__ $$aSlovenia$$bUniversity of Ljubljana$$c2016
000220308 269__ $$a2016
000220308 336__ $$aConference Papers
000220308 520__ $$aThe improvement of the efficiency of vehicle energy systems promotes an active search to find innovative solutions during the design process. Engineers can use computer-aided processes to find automatically the best design solutions. This kind of approach named “multi-objective optimization” is based on genetic algorithms. The idea is to obtain simultaneously a population of possible design solutions corresponding to the most efficient energy system definition for a vehicle. These solutions will be optimal from technical, economic and environmental point of view. The “genetic intelligence” is tested for the holistic design of the environomic vehicle powertrain solutions. The environomic methodology for design is applied on D-class hybrid electric vehicles, in order to define the powertrain configurations, to estimate the cost of the powertrain equipment and to show the environmental impact of the technical choices. The optimal designs are researched for the new European driving cycle.
000220308 6531_ $$aTransportation
000220308 6531_ $$aMulti-objective optimization
000220308 6531_ $$aHybrid electric vehicles
000220308 6531_ $$aEnvironomics
000220308 700__ $$0246374$$aDimitrova, Zlatina$$g224697
000220308 700__ $$0240374$$aMaréchal, François$$g140973
000220308 7112_ $$aThe 29th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems$$cPortoroz, Slovenia$$dJune 19-23, 2016
000220308 720_1 $$aKitanovski, Andrej$$eed.
000220308 720_1 $$aPoredoš, Alojz$$eed.
000220308 773__ $$tProceedings of ECOS 2016
000220308 8564_ $$s1763085$$uhttps://infoscience.epfl.ch/record/220308/files/P156_Environomic%20design%20of%20hybrid%20electric%20vehicles.pdf$$yPostprint$$zPostprint
000220308 8560_ $$fsimon.marechal@epfl.ch
000220308 909C0 $$0252481$$pIPESE$$xU12691
000220308 909CO $$ooai:infoscience.tind.io:220308$$pconf$$pSTI
000220308 917Z8 $$x265046
000220308 937__ $$aEPFL-CONF-220308
000220308 973__ $$aEPFL$$rREVIEWED
000220308 980__ $$aCONF