Next Article in Journal
Ionic Liquid-Based Optical and Electrochemical Carbon Dioxide Sensors
Next Article in Special Issue
Robust Road Condition Detection System Using In-Vehicle Standard Sensors
Previous Article in Journal
Modulation of Intracellular Quantum Dot to Fluorescent Protein Förster Resonance Energy Transfer via Customized Ligands and Spatial Control of Donor–Acceptor Assembly
Previous Article in Special Issue
Passive Sensor Integration for Vehicle Self-Localization in Urban Traffic Environment
Article Menu

Export Article

Open AccessArticle
Sensors 2015, 15(12), 30469-30486; doi:10.3390/s151229812

An Accurate and Generic Testing Approach to Vehicle Stability Parameters Based on GPS and INS

1,2,* , 1,2,†
and
2,†
1
College of Power and Energy Engineering, Harbin Engineering University, Harbin 150001, China
2
Heilongjiang Institute of Technology, Harbin 150050, China
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Felipe Jimenez
Received: 25 September 2015 / Revised: 1 December 2015 / Accepted: 1 December 2015 / Published: 4 December 2015
(This article belongs to the Special Issue Sensors in New Road Vehicles)
View Full-Text   |   Download PDF [2741 KB, uploaded 4 December 2015]   |  

Abstract

With the development of the vehicle industry, controlling stability has become more and more important. Techniques of evaluating vehicle stability are in high demand. As a common method, usually GPS sensors and INS sensors are applied to measure vehicle stability parameters by fusing data from the two system sensors. Although prior model parameters should be recognized in a Kalman filter, it is usually used to fuse data from multi-sensors. In this paper, a robust, intelligent and precise method to the measurement of vehicle stability is proposed. First, a fuzzy interpolation method is proposed, along with a four-wheel vehicle dynamic model. Second, a two-stage Kalman filter, which fuses the data from GPS and INS, is established. Next, this approach is applied to a case study vehicle to measure yaw rate and sideslip angle. The results show the advantages of the approach. Finally, a simulation and real experiment is made to verify the advantages of this approach. The experimental results showed the merits of this method for measuring vehicle stability, and the approach can meet the design requirements of a vehicle stability controller. View Full-Text
Keywords: data fusion; Kalman filter; GPS/INS; fuzzy logical system; vehicle stability parameters data fusion; Kalman filter; GPS/INS; fuzzy logical system; vehicle stability parameters
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Miao, Z.; Zhang, H.; Zhang, J. An Accurate and Generic Testing Approach to Vehicle Stability Parameters Based on GPS and INS. Sensors 2015, 15, 30469-30486.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top