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Nybacka, Mikael, Associate ProfessorORCID iD iconorcid.org/0000-0002-2265-9004
Publications (10 of 26) Show all publications
Gil Gómez, G., Nybacka, M., Bakker, E. & Drugge, L. (2016). Analysing vehicle dynamics objective and subjective testing in winter conditions. In: The Dynamics of Vehicles on Roads and Tracks: Proceedings of the 24th Symposium of the International Association for Vehicle System Dynamics, IAVSD 2015. Paper presented at 24th Symposium of the International Association for Vehicle System Dynamics, IAVSD 2015, Graz, Austria, 17 August 2015 - 21 August 2015 (pp. 759-768). Taylor & Francis Group
Open this publication in new window or tab >>Analysing vehicle dynamics objective and subjective testing in winter conditions
2016 (English)In: The Dynamics of Vehicles on Roads and Tracks: Proceedings of the 24th Symposium of the International Association for Vehicle System Dynamics, IAVSD 2015, Taylor & Francis Group, 2016, p. 759-768Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a test procedure developed to gather good quality data from objective and subjective testing on winter conditions. As the final goal of this test is to analyse the correlation between objective metrics and subjective assessments on winter for steering and handling, this procedure has to ensure a minimum change of the surface properties, which has a major influence on vehicle performance, during the whole test campaign. Therefore, the method presented keeps the total test time very low and allows similar vehicle configurations to be test- ed, objectively and subjectively, very close in time. Moreover, continuous maintenance work on the ice is performed. Reference vehicles are also used to monitor the changes on vehicle per- formance caused by weather conditions, which are inevitable. The method showed to be very effective. Initial results on objective metrics and subjective assessments are also presented. 

Place, publisher, year, edition, pages
Taylor & Francis Group, 2016
Keywords
Subjective testing, System theory, Vehicles, Continuous maintenance, Objective metrics, Subjective assessments, Test campaign, Test procedures, Vehicle configuration, Vehicle dynamics, Winter conditions, Vehicle performance
National Category
Vehicle Engineering
Research subject
Vehicle and Maritime Engineering
Identifiers
urn:nbn:se:kth:diva-181060 (URN)10.1201/b21185-81 (DOI)000385792300079 ()9781138028852 (ISBN)978-1-4987-7702-5 (ISBN)
Conference
24th Symposium of the International Association for Vehicle System Dynamics, IAVSD 2015, Graz, Austria, 17 August 2015 - 21 August 2015
Projects
iCOMSA
Funder
VINNOVA, 2012-04609TrenOp, Transport Research Environment with Novel Perspectives
Note

QC 20160404

Available from: 2016-01-27 Created: 2016-01-27 Last updated: 2017-05-03Bibliographically approved
Gil Gómez, G., Nybacka, M., Bakker, E. & Drugge, L. (2016). Correlations of subjective assessments and objective metrics for vehicle handling and steering: A walk through history. International Journal of Vehicle Design, 72(1), 17-67
Open this publication in new window or tab >>Correlations of subjective assessments and objective metrics for vehicle handling and steering: A walk through history
2016 (English)In: International Journal of Vehicle Design, ISSN 0143-3369, E-ISSN 1741-5314, Vol. 72, no 1, p. 17-67Article 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
Keywords
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:nbn:se:kth:diva-169081 (URN)10.1504/IJVD.2016.079191 (DOI)000391087600002 ()2-s2.0-84989221515 (Scopus ID)
Projects
iCOMSA
Funder
VINNOVA, 2012-04609
Note

QC 20170127

Available from: 2015-06-11 Created: 2015-06-11 Last updated: 2017-12-04Bibliographically approved
Daniel, W., Nybacka, M., Wallmark, O., Drugge, L. & Stensson Trigell, A. (2016). Experimental implementation of a fault handling strategy for electric vehicles with individual-wheel drives. In: The Dynamics of Vehicles on Roads and Tracks - Proceedings of the 24th Symposium of the International Association for Vehicle System Dynamics, IAVSD 2015: . Paper presented at 24th Symposium of the International Association for Vehicle System Dynamics, IAVSD 2015, Graz, Austria, 17 August 2015 through 21 August 2015 (pp. 147-152). CRC Press
Open this publication in new window or tab >>Experimental implementation of a fault handling strategy for electric vehicles with individual-wheel drives
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2016 (English)In: The Dynamics of Vehicles on Roads and Tracks - Proceedings of the 24th Symposium of the International Association for Vehicle System Dynamics, IAVSD 2015, CRC Press, 2016, p. 147-152Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a fault handling strategy for electric vehicles with four individual-wheel drives, which are based on wheel hub motors. The control strategy to handle the faults is based on the principle of control allocation and is implemented in an experimental vehicle. Experimental tests has been performed with the experimental vehicle and with simulation. The results show that the directional stability of such a vehicle can be improved for the analysed manoeuvre and failure mode, and the tendencies of the experimental results correspond with the simulation results. It has been found that the lateral and yaw motion could be strongly improved. 

Place, publisher, year, edition, pages
CRC Press, 2016
Keywords
Vehicle dynamics, fault handling, control allocation, experimental vehicle
National Category
Vehicle Engineering
Research subject
Vehicle and Maritime Engineering
Identifiers
urn:nbn:se:kth:diva-180359 (URN)000385792300015 ()2-s2.0-84973662750 (Scopus ID)978-113802885-2 (ISBN)
Conference
24th Symposium of the International Association for Vehicle System Dynamics, IAVSD 2015, Graz, Austria, 17 August 2015 through 21 August 2015
Funder
Integrated Transport Research Lab (ITRL)
Note

QC 20161118

Available from: 2016-01-12 Created: 2016-01-12 Last updated: 2016-11-18Bibliographically approved
Gil Gómez, G., Nybacka, M., Bakker, E. & Drugge, L. (2016). Objective metrics for vehicle handling and steering and their correlations with subjective assessments. International Journal of Automotive Technology, 17(5), 777-794
Open this publication in new window or tab >>Objective metrics for vehicle handling and steering and their correlations with subjective assessments
2016 (English)In: International Journal of Automotive Technology, ISSN 1229-9138, E-ISSN 1976-3832, Vol. 17, no 5, p. 777-794Article in journal (Refereed) Published
Abstract [en]

This paper focuses on increasing the available knowledge about correlations between objective metrics and subjective assessments in steering feel and vehicle handling. Linear and non-linear correlations have been searched for by means of linear regression and neural network training, complemented by different statistical tools. For example, descriptive statistics, the t-distribution and the normal distribution have been used to define the 95% confidence interval for expected subjective assessments and their mean, which makes it possible to predict the subjective rating related to a given objective metric and its area of confidence. Single- and multi-driver correlations have been investigated, as well as how the use of different databases and different vehicle classes affects the results. A method for automatizing the search for correlations when using the driver-by-driver strategy is also explained and evaluated. Ranges of preferred objective metrics for vehicle dynamics have been defined. Vehicles with characteristics within these ranges of values are expected to receive a higher subjective rating when evaluated. Finally, linear correlations between objective metrics have been studied, linear dependency between objective metrics has been identified and its consequences have been presented.

Place, publisher, year, edition, pages
Korean Society of Automotive Engineers, 2016
Keywords
Driver preference; Neural network; Objective metrics; Regression analysis; Steering feel; Subjective assessments; Vehicle handling
National Category
Vehicle Engineering
Identifiers
urn:nbn:se:kth:diva-169083 (URN)10.1007/s12239-016-0077-y (DOI)000379040800005 ()2-s2.0-84977119468 (Scopus ID)
Note

QC 20160819

Available from: 2015-06-11 Created: 2015-06-11 Last updated: 2017-12-04Bibliographically approved
Ljungberg, M., Nybacka, M., Gil Gómez, G. & Katzourakis, D. (2015). Electric Power Assist Steering System Parameterization and Optimisation Employing Computer-Aided Engineering. In: Steering and Suspension Technology Symposium: . Paper presented at SAE 2015 World Congress & Exhibition.
Open this publication in new window or tab >>Electric Power Assist Steering System Parameterization and Optimisation Employing Computer-Aided Engineering
2015 (English)In: Steering and Suspension Technology Symposium, 2015Conference paper, Published paper (Refereed)
Abstract [en]

The automotive industry strives to develop high quality vehicles in a short period of time that satisfy the consumer needs and stand out in the competition. Full exploitation of simulation and Computer-Aided Engineering (CAE) tools can enable quick evaluation of different vehicle concepts and setups without the need of building physical prototypes. Addressing the aforementioned statements this paper presents a method for optimising the Electric Power-Assisted Steering (EPAS) ECU parameters employing solely CAE. The objective of the optimisation is to achieve a desired steering response. The developed process is tested on three specific steering metrics (friction feel, torque build-up and torque deadband) for two function parameters (basic steering torque and active return) of the EPAS. The optimisation method enabled all metrics to fall successfully within the target range. 

Series
SAE International ; 2015-01-1500
Keywords
EPAS, Steering system optimisation, CAE design process, steering feel
National Category
Vehicle Engineering
Research subject
Vehicle and Maritime Engineering
Identifiers
urn:nbn:se:kth:diva-163550 (URN)10.4271/2015-01-1500 (DOI)
Conference
SAE 2015 World Congress & Exhibition
Projects
iCOMSA
Funder
VINNOVA, 2012-04609
Note

QC 20150506

Available from: 2015-04-08 Created: 2015-04-08 Last updated: 2015-05-06Bibliographically approved
Gil Gómez, G., Nybacka, M., Bakker, E. & Drugge, L. (2015). Findings from subjective evaluations and driver ratings of vehicle dynamics: steering and handling. Vehicle System Dynamics, 53(10), 1416-1438
Open this publication in new window or tab >>Findings from subjective evaluations and driver ratings of vehicle dynamics: steering and handling
2015 (English)In: Vehicle System Dynamics, ISSN 0042-3114, E-ISSN 1744-5159, Vol. 53, no 10, p. 1416-1438Article in journal (Refereed) Published
Abstract [en]

This paper investigates subjective assessments (SA) of vehicle handling and steering feel tests, both numerical and verbal, to understand drivers’ use of judgement scales, rating tendencies and spread. Two different test methods are compared: a short multi-vehicle first-impression test with predefined-driving vs the standard extensive single-vehicle free-driving tests, both offering very similar results but with the former saving substantial testing time. Rating repeatability is evaluated by means of a blind test. Key SA questions are identified by numerical subjective assessment autocorrelations and by generating word clouds from the most used terms in verbal assessments, with both methods leading to similar key parameters. The results exposed in this paper enable better understanding of SA, allowing improving the overall subjective testing and evaluation process, and improving the data collection and analysis process needed before identifying correlations between SA and objective metrics.

Place, publisher, year, edition, pages
Taylor & Francis, 2015
Keywords
steering feel, vehicle handling, driver preference, subjective assessments, regression analysis
National Category
Vehicle Engineering
Research subject
Vehicle and Maritime Engineering
Identifiers
urn:nbn:se:kth:diva-169082 (URN)10.1080/00423114.2015.1050402 (DOI)000375451500003 ()2-s2.0-84940607901 (Scopus ID)
Projects
iCOMSA
Funder
VINNOVA, 2012-04609
Note

QC 20170314

Available from: 2015-06-11 Created: 2015-06-11 Last updated: 2017-12-04Bibliographically approved
Wallmark, O., Nybacka, M., Malmquist, D., Burman, M., Wennhage, P. & Géoren, P. (2014). Design and implementation of an experimental research and concept demonstration vehicle. In: 2014 IEEE Vehicle Power and Propulsion Conference, VPPC 2014: . Paper presented at 2014 IEEE Vehicle Power and Propulsion Conference, VPPC 2014, 27 October 2014 through 30 October 2014. IEEE conference proceedings
Open this publication in new window or tab >>Design and implementation of an experimental research and concept demonstration vehicle
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2014 (English)In: 2014 IEEE Vehicle Power and Propulsion Conference, VPPC 2014, IEEE conference proceedings, 2014Conference paper, Published paper (Refereed)
Abstract [en]

This paper introduces the Research Concept Vehicle (RCV), an experimental research and demonstration vehicle developed at KTH Royal Institute of Technology. The vehicle is intended as a platform to implement, validate, and demonstrate research results from different research projects carried out at KTH. In its first generation, the RCV is a pure electric vehicle where each wheel is equipped with an in-wheel motor and individual steering and camber actuators. This high level of over actuation allows for a wide range of experimental evaluation in several fields of research, which is listed in this paper. Results from initial experimental test drives are also included.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2014
National Category
Vehicle Engineering
Identifiers
urn:nbn:se:kth:diva-174805 (URN)10.1109/VPPC.2014.7007042 (DOI)2-s2.0-84934325440 (Scopus ID)9781479967834 (ISBN)
Conference
2014 IEEE Vehicle Power and Propulsion Conference, VPPC 2014, 27 October 2014 through 30 October 2014
Funder
Integrated Transport Research Lab (ITRL)StandUpTrenOp, Transport Research Environment with Novel Perspectives
Note

QC 20151209. QC 20160304

Available from: 2015-12-09 Created: 2015-10-07 Last updated: 2016-11-11Bibliographically approved
Nybacka, M., He, X., Gil Gómez, G., Bakker, E. & Drugge, L. (2014). Links between subjective assessments and objective metrics for steering. International Journal of Automotive Technology, 15(6), 893-907
Open this publication in new window or tab >>Links between subjective assessments and objective metrics for steering
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2014 (English)In: International Journal of Automotive Technology, ISSN 1229-9138, E-ISSN 1976-3832, Vol. 15, no 6, p. 893-907Article in journal (Refereed) Published
Abstract [en]

The characteristics of steering perception are decisive factors for overall driver preference and for vehicle safety. Car manufacturers are continuously required to tune the characteristics of the vehicle and have a strong need to be more effective in the design and evaluation of cars. Using only objective metrics (OM) can result in unwanted steering feel and using only subjective assessments (SA) is time-consuming, costly and non-repetitive. Before a tool can be built to predict the steering feel in front-end development and to improve design knowledge from the full vehicle level to the component level, links between subjective assessments and objective metrics must be found and analysed. The data collected for the study presented in this paper include subjective ratings from expert drivers and objective measurements made with steering robots, involving twelve expert drivers and over twenty vehicles across four different vehicle classes. Linear regression and neural network analysis (NN) have been used to explore reliable subjective-objective links. The tools and methods used in this research showed promising results. Most of the links found concern response and torque feedback. The preferred ranges of some crucial objective metrics leading to more desirable steering feel have been defined and presented. The results indicate that it would be possible for car manufacturers to develop new vehicles more effectively with a steering feel in line with the design criteria by using the tools and methods investigated in this paper. 

Keywords
Steering feel, Driver preference, Objective metrics, Subjective assessments, Regression analysis, Neural network
National Category
Vehicle Engineering
Research subject
Vehicle and Maritime Engineering
Identifiers
urn:nbn:se:kth:diva-155319 (URN)10.1007/s12239-014-0094-7 (DOI)000342972700005 ()
Projects
iCOMSA
Funder
TrenOp, Transport Research Environment with Novel PerspectivesVinnova, 2012-04609
Note

QC 20141112

Available from: 2014-11-04 Created: 2014-11-04 Last updated: 2017-12-05Bibliographically approved
Nybacka, M., He, X., Su, Z., Drugge, L. & Bakker, E. (2014). Links between subjective assessments and objective metrics for steering, and evaluation of driver ratings. Vehicle System Dynamics, 52, 31-50
Open this publication in new window or tab >>Links between subjective assessments and objective metrics for steering, and evaluation of driver ratings
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2014 (English)In: Vehicle System Dynamics, ISSN 0042-3114, E-ISSN 1744-5159, Vol. 52, p. 31-50Article in journal (Refereed) Published
Abstract [en]

During the development of new vehicles, finding correlation links between subjective assessments (SA) and objective metrics (OM) is an important part of the vehicle evaluation process. Studying different correlation links is important in that the knowledge gained can be used at the front end of development, during testing and when creating new systems. Both SA from expert drivers using a rating scale of 1-10 and OM from different tests measured by a steering robot were collected using standard testing protocols at an automotive manufacturer. The driver ratings were evaluated and the correlations were analysed using regression analysis and neural networks through a case study approach. Links were identified and were compared with related research.

Place, publisher, year, edition, pages
Taylor & Francis, 2014
Keywords
steering feel, driver preference, objective metrics, subjective assessments, regression analysis, neural network
National Category
Vehicle Engineering
Research subject
SRA - Transport
Identifiers
urn:nbn:se:kth:diva-140604 (URN)10.1080/00423114.2013.876503 (DOI)000337582400004 ()2-s2.0-84901620886 (Scopus ID)
Projects
iCOMSA
Funder
TrenOp, Transport Research Environment with Novel PerspectivesVinnova, 2012-04609
Note

QC 20140224

Available from: 2014-01-28 Created: 2014-01-28 Last updated: 2017-12-06Bibliographically approved
Angelis, S., Tidlund, M., Leledakis, A., Lidberg, M., Nybacka, M. & Katzourakis, D. (2014). Optimal Steering for Double-Lane Change Entry Speed Maximization. In: Proceedings of ACEV'14 International symposium on advanced vehicle control, 22-26 September 2014,Tokyo, Japan: . Paper presented at ACEV'14 International symposium on advanced vehicle control, 22-26 September 2014,Tokyo, Japan. Tokyo, Japan: Society of Automotive Engineers
Open this publication in new window or tab >>Optimal Steering for Double-Lane Change Entry Speed Maximization
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2014 (English)In: Proceedings of ACEV'14 International symposium on advanced vehicle control, 22-26 September 2014,Tokyo, Japan, Tokyo, Japan: Society of Automotive Engineers, 2014Conference paper, Published paper (Refereed)
Abstract [en]

This study introduces a method for estimating the vehicle’s maximum entry speed for an ISO3888 part-2 double-lane change (DLC) test in simulation. Pseudospectral collocation in TOMLAB/ PROPT calculates the optimal steering angle that maximizes the entry speed. The rationale is to estimate the vehicle’s performance in the design phase and adapt the tuning to improve DLC ratings. A two-track vehicle dynamics model (VDM) employing non-linear tires, suspension properties and a simplified Dynamic Stability and Traction Control (DSTC) system was parameterized as a 2011 T5 FWD Volvo S60 using in-field tests and its corresponding kinematics and compliance (K&C) measurements. A sensitivity analysis on the parameters revealed certain trends that influence the entry speed, which can be varied from 69.4 up to 73.3 km/h when adapting certain vehicle features. To evaluate the method, the generated optimal steering control inputs for the simulated S60 were applied on the actual car motivating the further development of the method. 

Place, publisher, year, edition, pages
Tokyo, Japan: Society of Automotive Engineers, 2014
Keywords
Vehicle dynamics, steering, brake, tire, suspension, optimization, simulation
National Category
Vehicle Engineering
Research subject
Vehicle and Maritime Engineering
Identifiers
urn:nbn:se:kth:diva-163551 (URN)
Conference
ACEV'14 International symposium on advanced vehicle control, 22-26 September 2014,Tokyo, Japan
Note

QC 20150408

Available from: 2015-04-08 Created: 2015-04-08 Last updated: 2015-04-08Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-2265-9004

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