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Modelling and experimental testing of truck tyre rolling resistance

Time: Thu 2023-09-28 14.00

Location: Lecture hall F3, Lindstedtsvägen 26

Language: English

Subject area: Engineering Mechanics

Doctoral student: Jukka Hyttinen , Farkostteknik och Solidmekanik, VinnExcellence Center for ECO2 Vehicle design, Vehicle Dynamics

Opponent: Professor James Busfield, Queen Mary University of London

Supervisor: Lars Drugge, VinnExcellence Center for ECO2 Vehicle design, Väg- och spårfordon samt konceptuell fordonsdesign; Jenny Jerrelind, VinnExcellence Center for ECO2 Vehicle design, Farkostteknik och Solidmekanik

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QC 230905

Abstract

Truck transport offers a versatile way to ship goods in regional, long haulage and urban applications. However, the heavy truck sector accounts for 6 % of total greenhouse gas emissions in the European Union. Therefore, there is a need for a substantial reduction of these emissions to secure the sustainability of Earth for future generations. A key parameter to be considered is rolling resistance, which is the source of approximately half of truck energy consumption.

This thesis aims to provide knowledge and insights about rolling resistance simulations and testing, as well as contribute to a better understanding of parameters affecting rolling resistance. Tests in a climate wind tunnel and on the road were conducted at various speeds and a wide range of ambient temperatures (-30 to +25 °C), providing measurement results that are generally unavailable. The measurements show a considerable increase in the stabilised and non-stationary rolling resistance with lower tyre and ambient temperatures. Furthermore, a way to reduce tyre cooling is suggested in order to increase tyre temperature and thereby reduce rolling resistance. Another key result of this thesis is the design of an on-road driving loss device, which enables quick and convenient validation of energy consumption simulations by retaining the standard interface between the rim and axle while measuring required driving torque during on-road testing. 

Three different simulation models of varying complexity are proposed to simulate rolling resistance: (I) a phenomenological real-time capable rolling resistance estimation model that utilises time-temperature-superposition and a variable thermal inertia temperature model; (II) a semi-physical thermodynamic tyre rolling resistance model with a temperature-dependent nonlinear viscoelastic model that can be used in different parameter studies, such as to analyse the effect of tyre cooling on tyre temperature and rolling resistance; and (III) a finite element simulation model with a hyperviscoplastic PRF rubber model for detailed structural analyses. Furthermore, a convenient method for parametrising a complicated PRF rubber model utilising reduced material parameters was developed and parametrised against measurement data. The reduced material constants simplify the parametrisation, allowing the model to be parametrised with only manual iterations, which is generally not possible. 

Electric vehicles, such as trucks, passenger cars and electrically assisted bicycles, suffer from a reduced driving range at cold temperatures. Increasing the understanding of the influence of rolling resistance on range aspects can help accelerate the adoption of battery-electric trucks and other vehicles that use sustainable energy sources. Therefore, a driving range simulation of a battery-electric truck was conducted where the truck tyre rolling and aerodynamic resistance were varied with ambient temperature, showing a considerable decrease in driving range at cold temperatures. 

The experiments, simulations and the developed measurement device contribute to an increased understanding of rolling resistance and the factors affecting it. These insights are an essential part of developing future resource-efficient vehicles and transport systems where, e.g., transport flow can be optimised by taking into account rolling resistance, aerodynamic resistance and other essential factors.

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