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Estimating tyre pressure based on different tyre temperature measurement points
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Vehicle Engineering and Solid Mechanics. KTH, School of Engineering Sciences (SCI), Centres, VinnExcellence Center for ECO2 Vehicle design. (Vehicle Dynamics)ORCID iD: 0000-0003-0109-6596
Scania.
Scania.ORCID iD: 0000-0002-1036-6837
KTH, School of Engineering Sciences (SCI), Centres, VinnExcellence Center for ECO2 Vehicle design. KTH, School of Engineering Sciences (SCI), Engineering Mechanics.ORCID iD: 0000-0002-1426-1936
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

Knowing the tyre pressure during driving is essential since it affects multiple tyre properties such as rolling resistance, uneven wear, and how prone the tyre is to tyre bursts. Tyre temperature and cavity pressure are closely tied to each other; a change in tyre temperature will cause an alteration in tyre cavity pressure. This article gives insights into which tyre temperature measurement position is representative enough to estimate pressure changes inside the tyre, and whether the pressure changes can be assumed to be nearly isochoric. Climate wind tunnel and road measurements were conducted where tyre pressure and temperature at the tyre inner-liner, the tyre shoulder, and the tread surface were monitored. The measurements show that tyres do not have a uniform temperature distribution. The ideal gas law is used to estimate the tyre pressure from the measured temperatures. The results indicate that of the compared temperature points, the inner-liner temperature is the most accurate for estimating tyre pressure changes (average error 0.63 %), and the pressure changes during driving are nearly isochoric. This conclusion can be drawn because the ratio between inner-liner temperature and tyre pressure is nearly constant, and the pressure can be simulated well using the isochoric gas law.

Keywords [en]
Tyre pressure, Truck tyre, Temperature
National Category
Vehicle and Aerospace Engineering
Research subject
Vehicle and Maritime Engineering
Identifiers
URN: urn:nbn:se:kth:diva-335292OAI: oai:DiVA.org:kth-335292DiVA, id: diva2:1794084
Funder
Vinnova, 2016-05195TrenOp, Transport Research Environment with Novel Perspectives
Note

QC 20230908

Available from: 2023-09-04 Created: 2023-09-04 Last updated: 2025-02-14Bibliographically approved
In thesis
1. Modelling and experimental testing of truck tyre rolling resistance
Open this publication in new window or tab >>Modelling and experimental testing of truck tyre rolling resistance
2023 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

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.

Abstract [sv]

Lastbilstransporter erbjuder ett flexibelt sätt att frakta varor, samtidigt som sektorn för tunga vägtransporter står för 6 % av de totala växthusgaserna i EU. Därför finns det ett behov av en avsevärd minskning av dessa utsläpp för att säkerställa ett hållbart samhälle. En av nyckelparametrarna är rullmotståndet, som orsakar ungefär hälften av en lastbils energiförbrukning.

Denna avhandling syftar till att ge ökad kunskap om rullmotståndssimuleringar och mätningar samt bidra till en fördjupad förståelse hur olika parametrar påverkar rullmotståndet, vilket kan leda till lägre energiförbrukning för tunga transporter. Tester i en klimatvindtunnel och på väg har utförts i olika hastigheter och ett brett område av omgivningstemperaturer (-30 till +25 °C). Mätningarna visar på en avsevärd ökning av det stabiliserade och icke-stationära rullmotståndet med lägre däck- och omgivningstemperaturer. Dessutom har ett sätt att minska däckkylningen föreslagits för att öka däcktemperaturen och därmed minska rullmotståndet. Därutöver har en mätutrustning för att mäta vridmomentet och drivförluster under körning konstruerats, som möjliggör snabb, kostnadseffektiv och lätthanterlig validering av energiförbrukningssimuleringar genom att behålla standardgränssnittet mellan fälgen och axeln.

Tre olika simuleringsmodeller med varierande komplexitet har föreslagits för att simulera rullmotstånd; (I) en fenomenologisk realtidskapabel rullmotståndsmodell som kan användas för att uppskatta rullmotstånd vid körning, (II) en semi-fysikalisk termodynamisk däcksrullmotståndsmodell med ickelinjär viskoelasticitet som kan användas i olika parameterstudier, såsom att analysera effekten av däckkylning på däckets temperatur och rullmotstånd, och (III) en finita element däckmodell med en hyperviskoplastisk PRF-gummimodell för detaljerade strukturella analyser. Dessutom har en metod utvecklats som underlättar parametriseringen av en komplicerad PRF-gummimodell genom reducerade materialparametrar. De reducerade materialparametrarna förenklar parametriseringen mot mätdata, vilket gör att modellen kan parametriseras genom manuella iterationer, som vanligtvis inte är möjligt.

Elektriska fordon, som lastbilar, personbilar och elektriskt assisterade cyklar, lider av en minskad räckvidd vid kalla temperaturer. Ökad förståelse av räckviddsaspekter underlättar introduktionen av batterielektriska lastbilar och andra fordon som använder hållbara energikällor. Därför genomfördes en räckviddssimulering av en batterielektrisk lastbil där rullmotstånd och aerodynamisk motstånd varierades med omgivningstemperaturen, där simuleringarna visade en betydande minskning av körräckvidden vid kalla temperaturer. 

Experimenten, simuleringarna och den utvecklade mätutrustningen bidrar till en ökad förståelse för rullmotståndet och de faktorer som påverkar det. Dessa insikter är en viktig del i att utveckla framtidens resurseffektiva fordon och transportsystem, där till exempel transportflödet kan optimeras med hänsyn till rullmotstånd, aerodynamiskt motstånd och andra viktiga aspekter.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2023. p. 94
Series
TRITA-SCI-FOU ; 2023:45
Keywords
Truck tyre, PRF, filler-reinforced rubber, ambient temperature, rubber testing, constitutive modelling, parametrisation, rolling resistance, load cell, Fletcher-Gent effect, Payne effect, Lastbilsdäck, PRF, förstärkande fyllmedel, gummi, omgivningstemperatur, gummiprovning, konstitutiv modellering, parametrisering, rullmotstånd, lastcell, Fletcher-Gent effekt, Payne effekt
National Category
Vehicle and Aerospace Engineering
Research subject
Engineering Mechanics
Identifiers
urn:nbn:se:kth:diva-335323 (URN)978-91-8040-681-9 (ISBN)
Public defence
2023-09-28, Lecture hall F3, Lindstedtsvägen 26, Stockholm, 14:00 (English)
Opponent
Supervisors
Funder
Vinnova, 2016-05195TrenOp, Transport Research Environment with Novel Perspectives
Note

QC 230905

Available from: 2023-09-05 Created: 2023-09-04 Last updated: 2025-02-14Bibliographically approved

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Hyttinen, JukkaÖsterlöf, RickardJerrelind, JennyDrugge, Lars

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