This content is not included in your SAE MOBILUS subscription, or you are not logged in.
Research on Objective Drivability Evaluation with Multi-Source Information Fusion for Passenger Car
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 14, 2020 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
The drivability plays an important role for marketability and competitiveness of passenger car in meeting some customer requirements, which directly affects the driving experience and the desire of purchasing. In this paper, a framework of objective drivability evaluation with multi-source information fusion for passenger car is proposed. At first, according to vehicle powertrain system and optimization theory, certain vehicle performances, which are closely related to objective drivability are analyzed, including vehicle longitudinal acceleration, vehicle speed, engine torque, engine speed, gear position, accelerator pedal, brake signal and voltage signal. Then, combined with the evaluation criterion of signal-to-noise ratio (SNR), mean error (ME), root mean squared error (RMSE) and signal smoothness (SS), a de-noising method is developed for the drivability evaluation information. The optimal wavelet base-function and decomposition layer are analyzed, which is suitable for filtering processing of vehicle longitudinal acceleration signal. Last but not least, based on data layer, the multi-source information is implemented. Combined the driving characteristics with expert knowledge of passenger car, the classes of standard drivability test cycles are formulated, and the sliding window method is used to identify the working conditions. Finally, the effectiveness of the selected filtering algorithm and the reliability of the hardware and software platform are verified by the actual vehicle test of starting condition.
This research provide a reliable reference for obtaining valuable special diagnosis of objective drivability for passenger cars, and also can be used to optimize the intelligent level of automatic transmission ramp. As for the development of autonomous vehicle, path planning and tracking control algorithm can be offered with a theoretical basis.
CitationZhou, W., Guo, X., Pei, X., Chen, Z. et al., "Research on Objective Drivability Evaluation with Multi-Source Information Fusion for Passenger Car," SAE Technical Paper 2020-01-1044, 2020, https://doi.org/10.4271/2020-01-1044.
Data Sets - Support Documents
|Unnamed Dataset 1|
|Unnamed Dataset 2|
- Huang , W. , Liu , H.J. , Tong , R.H. , and Li , M. Application of Assessment Method of Vehicle Drivability in Creep Conditions Journal of Harbin Institute of Technology 50 7 126 130 2018
- Walters , T. , Shaw , P. , Madurai Kumar , M. , and Hoop , J. Analysis Lead Drivability Assessment SAE Technical Paper 2015-01-2804 2015 https://doi.org/10.4271/2015-01-2804
- Dorey , R.E. and Martin , E.J. Vehicle Driveability - The Development of an Objective Methodology SAE Technical Paper 2000-01-1326 2000 https://doi.org/10.4271/2000-01-1326
- List , H.O. Objective Evaluation of Vehicle Drivability SAE Technical Paper 980804 1998 https://doi.org/10.4271/980804
- Zhang , X.D. 2017
- Jin , H. , Li , L. , Chen , H.Y. Filter Algorithm for Longitudinal Acceleration of Vehicles Transactions of Beijing Institute of Technology 29 1 14 22 2009
- Wu , J.N. , Yun , L. , and Wang , J.J. A Novel De-noising Algorithm for Acceleration Signal Based on Compressed Sensing ICNC-FSKD 2017
- Xu , C. , Shen , X.R. , Li , J.J. , and Fan , Y.Z. Research on Wavelet De-noising Method of Vehicle Based MEMS Accelerator Signal Chinese Journal Sensors and Actuators 20 11 2442 2444 2007
- Liu , H.J. , Li , M. , Huang , W. , and Tong , R.H. Signal De-noising Method for Whole Vehicle Drivability Evaluation Based on Wavelet Transform Noise and Vibration Control 38 1 103 108 2018
- Shin , C.W. and Kim , H. Development of an Evaluation Method for Quantitative Drivability in Heavy-Duty Vehicles Journal of Mechanical Science and Technology 28 5 1615 1621 2014
- Walters , T.L. , Shaw , P. , Kumar , M.M. et al. Analysis Lead Drivability Assessment SAE Technical Paper 2015-01-2804 2015 https://doi.org/10.4271/2015-01-2804
- Lakshmanan , S. , Palaniappan , A. , and Chekuri , V. Methodology for Evaluation of Drivability Attributes in Commercial Vehicle SAE Technical Paper 2015-01-2767 2015 https://doi.org/10.4271/2015-01-2767
- Chandrasekaran , K. , Rao , N. , Palraj , S. , Kurella , C. et al. Objective Drivability Evaluation on Compact SUV and Comparison with Subjective Drivability SAE Technical Paper 2017-26-0153 2017 https://doi.org/10.4271/2017-26-0153
- Liu , P.H. , Tong , Z. , and Zhao , X.B. Vehicle Drivability Evaluation and Pedal-acceleration Response Analysis Advances in Information Sciences and Service Sciences (AISS) 5 10 506 513 2013
- Chang , W.S. Cha , Suk Won , and Lim , W. An Objective Method of Drivability Evaluation using a Simulation Model for Hybrid Electric Vehicles International Journal of Precision Engineering and Manufacturing 2014 15 2 219 226