Research on Soft Measurement of Electronic Stability Control for Electric-wheel Vehicle
- DOI
- 10.2991/lemcs-15.2015.328How to use a DOI?
- Keywords
- Soft measurement; Vehicle model; Electric-wheel vehicle; Improved UKF; ESC
- Abstract
In order to enhance the timeliness and accuracy of the soft measurement method of the ESC for electric-wheel vehicle, an improved soft measurement algorithm was designed. The improved algorithm was built based on an improved UKF. The improved UKF sampling strategy used scaled minimal skew sampling method to speed up the system sampling rate. The sigma points of the improved UKF were sampling two times to enhance the accuracy. The three degree of freedom vehicle model was built to establish vehicle dynamic relationship. According to the three degree of freedom vehicle model, the vehicle measurement model was built. The verification experiments of improved soft measurement algorithm were made based on the electric-wheel vehicle ESC test platform. The experiments included a step input experiment in 70 kilometers per hour and a step input experiment in 110 kilometers per hour. From the experimental results, it could be seen that the estimated value of yaw velocity and sideslip angle tracked the actual very well. The overshoot of the tracking process was small and the lag time was short. The improved soft measurement algorithm was fit for the ESC of electric-wheel vehicle.
- Copyright
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Cheng Wang AU - Chuanxue Song PY - 2015/07 DA - 2015/07 TI - Research on Soft Measurement of Electronic Stability Control for Electric-wheel Vehicle BT - Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science PB - Atlantis Press SP - 1635 EP - 1638 SN - 1951-6851 UR - https://doi.org/10.2991/lemcs-15.2015.328 DO - 10.2991/lemcs-15.2015.328 ID - Wang2015/07 ER -