Advanced Modelling and Energy Efficiency Prediction for Road Vehicles

This thesis presents a first real world case-study of road transport operations that use the COVER format, in which the driver and the vehicle are regarded as separate entities. This format enables a complex representation of the transport operation that potentially better describe reality compared...

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Main Author: Nordström, Erik
Format: Others
Language:English
Published: Umeå universitet, Institutionen för fysik 2020
Subjects:
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-175358
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spelling ndltd-UPSALLA1-oai-DiVA.org-umu-1753582021-05-05T05:36:57ZAdvanced Modelling and Energy Efficiency Prediction for Road VehiclesengNordström, ErikUmeå universitet, Institutionen för fysik2020Operating cycleCO2 emissionsEnergy consumption simulationPowertrain optimizationRoad formatTransport missionTruck transportationMathematical modelPhysical SciencesFysikVehicle EngineeringFarkostteknikThis thesis presents a first real world case-study of road transport operations that use the COVER format, in which the driver and the vehicle are regarded as separate entities. This format enables a complex representation of the transport operation that potentially better describe reality compared to the conventional representation used in today’s certification tools. The representation of operations treated in this thesis is called Operating Cycles and has been used to fully describe three representative transport missions from a case-study truck. Stochastically generated operating cycles have been used to create a large data set and thus prevent overfitting of specific cycles. The Operating Cycle-representation allowed for fair comparison between vehicle designs and ultimately manifested a vehicle composition that reduced the fuel consumption by nearly 10% for the same kind of transport operations. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-175358application/pdfinfo:eu-repo/semantics/openAccess
collection NDLTD
language English
format Others
sources NDLTD
topic Operating cycle
CO2 emissions
Energy consumption simulation
Powertrain optimization
Road format
Transport mission
Truck transportation
Mathematical model
Physical Sciences
Fysik
Vehicle Engineering
Farkostteknik
spellingShingle Operating cycle
CO2 emissions
Energy consumption simulation
Powertrain optimization
Road format
Transport mission
Truck transportation
Mathematical model
Physical Sciences
Fysik
Vehicle Engineering
Farkostteknik
Nordström, Erik
Advanced Modelling and Energy Efficiency Prediction for Road Vehicles
description This thesis presents a first real world case-study of road transport operations that use the COVER format, in which the driver and the vehicle are regarded as separate entities. This format enables a complex representation of the transport operation that potentially better describe reality compared to the conventional representation used in today’s certification tools. The representation of operations treated in this thesis is called Operating Cycles and has been used to fully describe three representative transport missions from a case-study truck. Stochastically generated operating cycles have been used to create a large data set and thus prevent overfitting of specific cycles. The Operating Cycle-representation allowed for fair comparison between vehicle designs and ultimately manifested a vehicle composition that reduced the fuel consumption by nearly 10% for the same kind of transport operations.
author Nordström, Erik
author_facet Nordström, Erik
author_sort Nordström, Erik
title Advanced Modelling and Energy Efficiency Prediction for Road Vehicles
title_short Advanced Modelling and Energy Efficiency Prediction for Road Vehicles
title_full Advanced Modelling and Energy Efficiency Prediction for Road Vehicles
title_fullStr Advanced Modelling and Energy Efficiency Prediction for Road Vehicles
title_full_unstemmed Advanced Modelling and Energy Efficiency Prediction for Road Vehicles
title_sort advanced modelling and energy efficiency prediction for road vehicles
publisher Umeå universitet, Institutionen för fysik
publishDate 2020
url http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-175358
work_keys_str_mv AT nordstromerik advancedmodellingandenergyefficiencypredictionforroadvehicles
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