Energy consumption prediction for heavy electric vehicles based on the operating cycle format

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dc.contributor.authorBerg, Marcus
dc.contributor.authorTa, Conny
dc.contributor.departmentChalmers tekniska högskola / Institutionen för mekanik och maritima vetenskapersv
dc.contributor.examinerBruzelius, Fredrik
dc.contributor.supervisorRomano, Luigi
dc.contributor.supervisorAndersson, Rickard
dc.date.accessioned2022-07-05T13:49:57Z
dc.date.available2022-07-05T13:49:57Z
dc.date.issued2022sv
dc.date.submitted2020
dc.description.abstractThe objective of this report is to study the energy consumption of a heavy electric vehicle while it is on the road driving along an unknown route. The results from this project deliver a method and a framework that can be used to estimate certain environmental factors’ energy consumption affect on a vehicle. The focus lies on investigating factors that can be hard to predict, or which there is no information about before embarking on a route. The energy consumption from all factors’ is summed up to give a final estimation. A connection between the different factors characteristics and the energy consumption is established by running simulated sce narios generated by stochastic models of the investigated factors. The findings of the project are the relations between characteristics of the factors to its energy consumption. When the variance of the topography increases, an increase in the energy consumption can be observed as well. This observation demonstrates the relation between the characteristics with their corresponding influence on energy consumption. Similar conclusions can also be observed for the two other investigated parameters, curvature and speed bumps. The results are based on the assumption that summing the energy contributions from each factors model gives a total energy consumption for the vehicle along a route. The results of the project show that it is possible to estimate the energy consumption for other parameters with similar phys ical properties as well. This is especially important for parameters which are hard to calculate before starting a route. The findings consists of a series of constructed graphs that represents the simulations. These graphs contain information to map a set of an interval of investigated characteristics such as the variance values, mean curvature and speed bumps intensity to an energy consumption estimate.sv
dc.identifier.coursecodeMMSX30sv
dc.identifier.urihttps://hdl.handle.net/20.500.12380/305073
dc.language.isoengsv
dc.relation.ispartofseries2022:05sv
dc.setspec.uppsokTechnology
dc.subjectenergy consumptionsv
dc.subjectoperating cyclesv
dc.subjectheavy electric vehiclesv
dc.subjectpredictionsv
dc.subjectstochastic modelsv
dc.subjectunknown routesv
dc.titleEnergy consumption prediction for heavy electric vehicles based on the operating cycle formatsv
dc.type.degreeExamensarbete för masterexamensv
dc.type.uppsokH
local.programmeSystems, control and mechatronics (MPSYS), MSc
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