This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Objectified Drivability Evaluation and Classification of Passenger Vehicles in Automated Longitudinal Vehicle Drive Maneuvers with Engine Load Changes
Technical Paper
2019-01-1286
ISSN: 0148-7191, e-ISSN: 2688-3627
This content contains downloadable datasets
Annotation ability available
Sector:
Language:
English
Abstract
To achieve global market and brand specific drivability characteristics as unique selling proposition for the increasing number of passenger car derivatives, an objectified evaluation approach for the drivability capabilities of the various cars is required. Thereto, it is necessary to evaluate the influence of different engine concepts in various complex and interlinked powertrain topologies during engine load change maneuvers based on physical criteria. Such an objectification approach enables frontloading of drivability related engineering tasks by the execution of drivability development and calibration work within vehicle subcomponent-specific closed-loop real-time co-simulation environments in early phases of a vehicle development program. So far, drivability functionalities could be developed and calibrated only towards the end of a vehicle development program, when test vehicles with a sufficient level of product maturity became available. The resulting compaction and parallelization of the calibration work to meet the emissions, on-board diagnostics as well as the drivability requirements drastically reduces development costs and time.
This article presents an objectified drivability evaluation and classification approach for passenger cars, which is based on physical criteria, developed at the RWTH Aachen University in cooperation with FEV Europe GmbH. At the beginning of this work, the derived physical criteria for the objectification of longitudinal drivability load change maneuver results are presented and their subjective significance is explained. The calculation and variation of these criteria are discussed against the background of reproducibility and vehicle-spanning sensitivity. In addition, the automated method for determining and recording of the drivability measurements is explained. Furthermore, the results of sensitivity tests, which are based on calibration changes with regard to the longitudinal vehicle drivability behavior, are examined in detail. Individual disturbances and their influence on the results and physical criteria are also discussed. Finally, by presenting and discussing the results of a multitude of driving tests with a variety of vehicles using different characteristic diagrams (e.g. scatter bands), the reliability, maturity and validity of the holistic method is demonstrated.
Recommended Content
Technical Paper | Status of the Ford Universal Development Computer System |
Journal Article | Model-Based and Signal-Based Gearbox Sensor Fault Detection, Identification and Accommodation |
Authors
Topic
Citation
Guse, D., Heusch, C., Pischinger, S., Tegelkamp, S. et al., "Objectified Drivability Evaluation and Classification of Passenger Vehicles in Automated Longitudinal Vehicle Drive Maneuvers with Engine Load Changes," SAE Technical Paper 2019-01-1286, 2019, https://doi.org/10.4271/2019-01-1286.Data Sets - Support Documents
Title | Description | Download |
---|---|---|
Unnamed Dataset 1 | ||
Unnamed Dataset 2 | ||
Unnamed Dataset 3 | ||
Unnamed Dataset 4 | ||
Unnamed Dataset 5 | ||
Unnamed Dataset 6 | ||
Unnamed Dataset 7 |
Also In
References
- Venkitachalam , H. , von Wissel , D. , Richenhagen , J. Metricbased Evaluation of Software Architecture for an Engine Management System SAE Int. J. Engines 9 3 1377 1385 2016 10.4271/2016-01-0037
- Ulmer , H. , Heilig , A. , Rühl , M. , and Löw , B. Improving the Calibration Process of Internal Combustion Engines by Using an Innovative Multidimensional Optimization Algorithm SAE Technical Paper 2016-01-2153 2016 10.4271/2016-01-2153
- Maschmeyer , H. , Kluin , M. , and Beidl , C. 2015
- Guse , D. , Ueda , N. , Trampert , S. , Scharf , J. , et al.
- Schoeggl , P. and Ramschak , E. Vehicle Driveability Assessment using Neural Networks for Development, Calibration and Quality Tests SAE Technical Paper 2000-01-0702 2000 10.4271/2000-01-0702
- Liu , P. , Zhang , T. , and Zhao , X. Vehicle Drivability Evaluation and Pedal-Acceleration Response Analysis Advances in Information Sciences and Service Sciences (AISS) 5 10 2013 10.4156/AISS
- Klein , S. , Griefnow , P. , Guse , D. et al. Virtual 48 V Mild Hybridization - Efficient Validation by Engine-in-the-Loop SAE Technical Paper 2018-01-0410 2018 10.4271/2018-01-0410
- Trampert , S. , Nijs , M. , Huth , T. , Guse , D. 2017
- Slaney , T. , Nijs , M. , Guse , D. , et al. High Efficient Propulsion System Calibration Employing Engine-in-the-Loop Test Facilities Symposium for Combustion Control 2018 RWTH Aachen University Aachen 2018
- Bencker , R. , Brunner , H. , and Freymann , R. 2000
- Mitschke , M. and Wallentowitz , H. Dynamik der Kraftfahrzeuge Wiesbaden Springer Vieweg 2014
- Loos , H. and Laermann , F. Simulations and Measurements of Car Drivability Phenomena Vehicle System Dynamics 10.1080/00423119208969412
- SAE International Vehicle Dynamics Standards Committee 2016
- Lakshmanan , S. , Palaniappan , A. , and Chekuri , V. Methodology for Evaluation of Drivability Attributes in Commercial Vehicle SAE Technical Paper 2015-01-2767 2015 10.4271/2015-01-2767
- N.N Assessing Vibration: A Technical Guideline 2006 http://www.dec.nsw.gov.au/resources/vibrationguide0643.pdfRMS
- N.N 1997
- Rößler , I. and Ungerer , A. 2014