dc.contributor.author |
Ferreira, A
|
|
dc.contributor.author |
De Saxe, C
|
|
dc.contributor.author |
Steenkamp, Anton J
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|
dc.contributor.author |
Nordengen, P
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|
dc.date.accessioned |
2022-10-17T07:34:03Z |
|
dc.date.available |
2022-10-17T07:34:03Z |
|
dc.date.issued |
2022-07 |
|
dc.identifier.citation |
Ferreira, A., De Saxe, C., Steenkamp, A.J. & Nordengen, P. 2022. Developing a truck rollover risk calculator for South Africa. http://hdl.handle.net/10204/12505 . |
en_ZA |
dc.identifier.uri |
http://hdl.handle.net/10204/12505
|
|
dc.description.abstract |
The Static Rollover Threshold (SRT) is an important metric for characterising a heavy vehicle’s inherent stability and risk of rollover. Current methods of assessing SRT include a tilt-table test and multi-body dynamics simulation which can be costly, time-consuming and often require significant technical expertise or technical vehicle data not normally accessible to the public. Simplified calculation methods exist, but a remaining challenge exists to reduce the required level of user expertise and input data to make the assessment useable by, for example, fleet insurers who would have an interest in SRT information. In this paper we investigate the use of simplified calculations prescribed by the New Zealand Land Transport Rule (NZLTR) and UNECE 111 as the basis for the development of a user-friendly SRT calculator. The calculation results were validated against a multi-body dynamics model using TruckSIM for the case of a rigid truck for a range of vehicle suspension and mass properties. The NZLTR and ‘interpolated’ UNECE 111 methods resulted in the smallest errors compared with TruckSIM, averaging 6-7% in absolute error over the 16 scenarios assessed. Maximum errors occurred when the ratio between drive axle and steer axle roll stiffness was at its highest (at a ratio of 4.7:1). The UNECE 111 method was then used as the basis for a Python-based SRT calculator tool. The tool demonstrates how pre-loaded technical vehicle data and logic can be used to minimise the required user expertise and hence make SRT calculation feasible by non-technical users in the fleet insurance industry in South Africa. |
en_US |
dc.format |
Fulltext |
en_US |
dc.language.iso |
en |
en_US |
dc.relation.uri |
https://irfnet.ch/wp-content/uploads/2022/06/FINAL-ANNOUNCEMENT-BROCHURE-AND-PROGRAMME_FINAL.pdf |
en_US |
dc.source |
South African Transport Conference 2022 (SATC), Pretoria, South Africa, 4-7 July 2022 |
en_US |
dc.subject |
Static Rollover Threshold |
en_US |
dc.subject |
SRT |
en_US |
dc.subject |
Heavy goods vehicles |
en_US |
dc.subject |
Truck rollover |
en_US |
dc.subject |
UNECE 111 |
en_US |
dc.subject |
New Zealand Land Transport Rule |
en_US |
dc.subject |
NZLTR |
en_US |
dc.title |
Developing a truck rollover risk calculator for South Africa |
en_US |
dc.type |
Conference Presentation |
en_US |
dc.description.pages |
13 |
en_US |
dc.description.note |
Paper delivered at the South African Transport Conference 2022 (SATC), Pretoria, South Africa, 4-7 July 2022 |
en_US |
dc.description.cluster |
Smart Mobility |
en_US |
dc.description.impactarea |
Trans Network Asset Man Sys |
en_US |
dc.identifier.apacitation |
Ferreira, A., De Saxe, C., Steenkamp, A. J., & Nordengen, P. (2022). Developing a truck rollover risk calculator for South Africa. http://hdl.handle.net/10204/12505 |
en_ZA |
dc.identifier.chicagocitation |
Ferreira, A, C De Saxe, Anton J Steenkamp, and P Nordengen. "Developing a truck rollover risk calculator for South Africa." <i>South African Transport Conference 2022 (SATC), Pretoria, South Africa, 4-7 July 2022</i> (2022): http://hdl.handle.net/10204/12505 |
en_ZA |
dc.identifier.vancouvercitation |
Ferreira A, De Saxe C, Steenkamp AJ, Nordengen P, Developing a truck rollover risk calculator for South Africa; 2022. http://hdl.handle.net/10204/12505 . |
en_ZA |
dc.identifier.ris |
TY - Conference Presentation
AU - Ferreira, A
AU - De Saxe, C
AU - Steenkamp, Anton J
AU - Nordengen, P
AB - The Static Rollover Threshold (SRT) is an important metric for characterising a heavy vehicle’s inherent stability and risk of rollover. Current methods of assessing SRT include a tilt-table test and multi-body dynamics simulation which can be costly, time-consuming and often require significant technical expertise or technical vehicle data not normally accessible to the public. Simplified calculation methods exist, but a remaining challenge exists to reduce the required level of user expertise and input data to make the assessment useable by, for example, fleet insurers who would have an interest in SRT information. In this paper we investigate the use of simplified calculations prescribed by the New Zealand Land Transport Rule (NZLTR) and UNECE 111 as the basis for the development of a user-friendly SRT calculator. The calculation results were validated against a multi-body dynamics model using TruckSIM for the case of a rigid truck for a range of vehicle suspension and mass properties. The NZLTR and ‘interpolated’ UNECE 111 methods resulted in the smallest errors compared with TruckSIM, averaging 6-7% in absolute error over the 16 scenarios assessed. Maximum errors occurred when the ratio between drive axle and steer axle roll stiffness was at its highest (at a ratio of 4.7:1). The UNECE 111 method was then used as the basis for a Python-based SRT calculator tool. The tool demonstrates how pre-loaded technical vehicle data and logic can be used to minimise the required user expertise and hence make SRT calculation feasible by non-technical users in the fleet insurance industry in South Africa.
DA - 2022-07
DB - ResearchSpace
DP - CSIR
J1 - South African Transport Conference 2022 (SATC), Pretoria, South Africa, 4-7 July 2022
KW - Static Rollover Threshold
KW - SRT
KW - Heavy goods vehicles
KW - Truck rollover
KW - UNECE 111
KW - New Zealand Land Transport Rule
KW - NZLTR
LK - https://researchspace.csir.co.za
PY - 2022
T1 - Developing a truck rollover risk calculator for South Africa
TI - Developing a truck rollover risk calculator for South Africa
UR - http://hdl.handle.net/10204/12505
ER -
|
en_ZA |
dc.identifier.worklist |
36821 |
en_US |