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Sensor Fusion Based on an Integrated Neural Network and Probability Density Function (PDF) Dual Kalman Filter for On-Line Estimation of Vehicle Parameters and States
- Source :
- Sensors; Volume 17; Issue 5; Pages: 987, e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid, instname, Sensors (Basel, Switzerland)
- Publication Year :
- 2017
- Publisher :
- Multidisciplinary Digital Publishing Institute, 2017.
-
Abstract
- Vehicles with a high center of gravity (COG), such as light trucks and heavy vehicles, are prone to rollover. This kind of accident causes nearly 33% of all deaths from passenger vehicle crashes. Nowadays, these vehicles are incorporating roll stability control (RSC) systems to improve their safety. Most of the RSC systems require the vehicle roll angle as a known input variable to predict the lateral load transfer. The vehicle roll angle can be directly measured by a dual antenna global positioning system (GPS), but it is expensive. For this reason, it is important to estimate the vehicle roll angle from sensors installed onboard in current vehicles. On the other hand, the knowledge of the vehicle's parameters values is essential to obtain an accurate vehicle response. Some of vehicle parameters cannot be easily obtained and they can vary over time. In this paper, an algorithm for the simultaneous on-line estimation of vehicle's roll angle and parameters is proposed. This algorithm uses a probability density function (PDF)-based truncation method in combination with a dual Kalman filter (DKF), to guarantee that both vehicle's states and parameters are within bounds that have a physical meaning, using the information obtained from sensors mounted on vehicles. Experimental results show the effectiveness of the proposed algorithm. This work is supported by the Spanish Government through the Project TRA2013-48030-C2-1-R, which is gratefully acknowledged.
- Subjects :
- Truck
0209 industrial biotechnology
Engineering
dual Kalman filter
vehicle dynamics
probability density function (PDF) truncation
state estimation
parameter estimation
vehicle roll angle
sensor fusion
Probability density function
Vehicle dynamics
02 engineering and technology
Biochemistry
Article
Analytical Chemistry
020901 industrial engineering & automation
Control theory
0502 economics and business
Parameter estimation
Electrical and Electronic Engineering
Instrumentation
Ingeniería Mecánica
Sensor fusion
050210 logistics & transportation
business.industry
Dual Kalman filter
05 social sciences
Kalman filter
Rollover
Vehicle roll angle
Atomic and Molecular Physics, and Optics
Center of gravity
Electronic stability control
Global Positioning System
Probability density function (PDF) truncation
business
State estimation
Subjects
Details
- Language :
- English
- ISSN :
- 14248220
- Database :
- OpenAIRE
- Journal :
- Sensors; Volume 17; Issue 5; Pages: 987
- Accession number :
- edsair.doi.dedup.....b055014cc7e02fa8ccf678176d7b417b
- Full Text :
- https://doi.org/10.3390/s17050987