A Statistical Approach for Real-Time Prognosis of Safety-Critical Vehicle Systems 2007-01-1497
The paper describes the development of a vehicle stability indicator based on the correlation between various current vehicle chassis sensors such as hand wheel angle, yaw rate and lateral acceleration. In general, there is a correlation between various pairs of sensor signals when the vehicle operation is linear and stable and a lack of correlation when the vehicle is becoming unstable or operating in a nonlinear region. The paper outlines one potential embodiment of the technology that makes use of the Mahalanobis distance metric to assess the degree of correlation among the sensor signals. With this approach a single scalar metric provides an accurate indication of vehicle stability.
Citation: D'Silva, S., Jalics, L., and Krage, M., "A Statistical Approach for Real-Time Prognosis of Safety-Critical Vehicle Systems," SAE Technical Paper 2007-01-1497, 2007, https://doi.org/10.4271/2007-01-1497. Download Citation
Author(s):
Siddharth H. D'Silva, Laci Jalics, Mark Krage
Affiliated:
Delphi Corporation
Pages: 9
Event:
SAE World Congress & Exhibition
ISSN:
0148-7191
e-ISSN:
2688-3627
Also in:
Safety-Critical Systems, 2007-SP-2121, SAE 2007 Transactions Journal of Passenger Cars: Electronic and Electrical Systems-V116-7
Related Topics:
Safety critical systems
Prognostics
Stability control
Sensors and actuators
Vehicle dynamics /flight dynamics
SAE MOBILUS
Subscribers can view annotate, and download all of SAE's content.
Learn More »