Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Correlations of subjective assessments and objective metrics for vehicle handling and steering: A walk through history
KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering, Vehicle Dynamics. Volvo Cars.ORCID iD: 0000-0002-6699-1965
KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering, Vehicle Dynamics.ORCID iD: 0000-0002-2265-9004
Volvo Cars.
KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering, Vehicle Dynamics.ORCID iD: 0000-0001-8928-0368
2016 (English)In: International Journal of Vehicle Design, ISSN 0143-3369, E-ISSN 1741-5314, Vol. 72, no 1, 17-67 p.Article in journal (Refereed) Published
Abstract [en]

Achieving customer satisfaction concerning steering feel and vehicle handling requires subjective assessments and tuning of vehicle components by expert test drivers and engineers. Extensive subjective testing is expensive, time consuming and requires physical vehicles, which is in conflict with reduction of development time and cost. Objective testing and model-based development are constantly increasing but translating subjective requirements into objective ones is non-trivial. This paper summarises, discusses and classifies the methods, strategies and findings in previously published research regarding correlations of subjective assessments and objective metrics for vehicle handling and steering. The aim is twofold: (i) to identify key parameters of steering, handling and their preferred values and (ii) to compile and discuss the fundamental issues to deal with in the continued search for correlations between objective metrics and subjective assessments. The paper gives a comprehensive overview and insight of different aspects to take into account when conducting research in this field.

Place, publisher, year, edition, pages
Inderscience Enterprises , 2016. Vol. 72, no 1, 17-67 p.
Keyword [en]
steering feel, vehicle handling, driver preferences, objective metrics, subjective assessments, regression analysis, neural networks, fuzzy logic, vehicle steering, customer satisfaction, literature review
National Category
Vehicle Engineering
Research subject
Vehicle and Maritime Engineering; SRA - Transport
Identifiers
URN: urn:nbn:se:kth:diva-169081DOI: 10.1504/IJVD.2016.079191ISI: 000391087600002Scopus ID: 2-s2.0-84989221515OAI: oai:DiVA.org:kth-169081DiVA: diva2:819650
Projects
iCOMSA
Funder
VINNOVA, 2012-04609
Note

QC 20170127

Available from: 2015-06-11 Created: 2015-06-11 Last updated: 2017-12-04Bibliographically approved
In thesis
1. Towards Efficient Vehicle Dynamics Evaluation using Correlations of Objective Metrics and Subjective Assessments
Open this publication in new window or tab >>Towards Efficient Vehicle Dynamics Evaluation using Correlations of Objective Metrics and Subjective Assessments
2015 (English)Licentiate thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2015. xiv, 64 p.
Series
TRITA-AVE, ISSN 1651-7660 ; 2015:28
National Category
Vehicle Engineering
Identifiers
urn:nbn:se:kth:diva-169085 (URN)
Presentation
2015-06-12, Vehicle Engineering Lab, Teknikringen 8, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 20150611

Available from: 2015-06-11 Created: 2015-06-11 Last updated: 2015-06-11Bibliographically approved
2. Towards efficient vehicle dynamics development: From subjective assessments to objective metrics, from physical to virtual testing
Open this publication in new window or tab >>Towards efficient vehicle dynamics development: From subjective assessments to objective metrics, from physical to virtual testing
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Vehicle dynamics development is strongly based on subjective assessments (SA) of vehicle prototypes, which is expensive and time consuming. Consequently, in the age of computer- aided engineering (CAE), there is a drive towards reducing this dependency on physical test- ing. However, computers are known for their remarkable processing capacity, not for their feelings. Therefore, before SA can be computed, it is required to properly understand the cor- relation between SA and objective metrics (OM), which can be calculated by simulations, and to understand how this knowledge can enable a more efficient and effective development process.

The approach to this research was firstly to identify key OM and SA in vehicle dynamics, based on the multicollinearity of OM and of SA, and on interviews with expert drivers. Sec- ondly, linear regressions and artificial neural network (ANN) were used to identify the ranges of preferred OM that lead to good SA-ratings. This result is the base for objective require- ments, a must in effective vehicle dynamics development and verification.

The main result of this doctoral thesis is the development of a method capable of predicting SA from combinations of key OM. Firstly, this method generates a classification map of ve- hicles solely based on their OM, which allows for a qualitative prediction of the steering feel of a new vehicle based on its position, and that of its neighbours, in the map. This prediction is enhanced with descriptive word-clouds, which summarizes in a few words the comments of expert test drivers to each vehicle in the map. Then, a second superimposed ANN displays the evolution of SA-ratings in the map, and therefore, allows one to forecast the SA-rating for the new vehicle. Moreover, this method has been used to analyse the effect of the tolerances of OM requirements, as well as to verify the previously identified preferred range of OM.

This thesis focused on OM-SA correlations in summer conditions, but it also aimed to in- crease the effectiveness of vehicle dynamics development in general. For winter conditions, where objective testing is not yet mature, this research initiates the definition and identifica- tion of robust objective manoeuvres and OM. Experimental data were used together with CAE optimisations and ANOVA-analysis to optimise the manoeuvres, which were verified in a second experiment. To improve the quality and efficiency of SA, Volvo’s Moving Base Driving Simulator (MBDS) was validated for vehicle dynamics SA-ratings. Furthermore, a tablet-app to aid vehicle dynamics SA was developed and validated.

Combined this research encompasses a comprehensive method for a more effective and ob- jective development process for vehicle dynamics. This has been done by increasing the un- derstanding of OM, SA and their relations, which enables more effective SA (key SA, MBDS, SA-app), facilitates objective requirements and therefore CAE development, identi- fies key OM and their preferred ranges, and which allow to predict SA solely based on OM. 

Place, publisher, year, edition, pages
Stockholm: Kungliga tekniska högskolan, 2017. 72 p.
Series
TRITA-AVE, ISSN 1651-7660 ; 2017:12
Keyword
Steering feel, vehicle handling, driver preference, objective metrics, subjective assessments, regression analysis, artificial neural network
National Category
Vehicle Engineering
Research subject
Vehicle and Maritime Engineering
Identifiers
urn:nbn:se:kth:diva-202348 (URN)978-91-7729-302-6 (ISBN)
Public defence
2017-03-17, D3, Lindstedsvägen 5, Stockholm, 10:00 (English)
Opponent
Supervisors
Projects
iCOMSA
Funder
VINNOVA, 2012-04609
Note

QC 20170223

Available from: 2017-02-23 Created: 2017-02-21 Last updated: 2017-02-23Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopusInderscience

Authority records BETA

Gil Gómez, GasparNybacka, MikaelDrugge, Lars

Search in DiVA

By author/editor
Gil Gómez, GasparNybacka, MikaelDrugge, Lars
By organisation
Vehicle Dynamics
In the same journal
International Journal of Vehicle Design
Vehicle Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 1096 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf