Stochastic models of road geometry and wind condition for vehicle energy management and control

Khayyam, Hamid 2013, Stochastic models of road geometry and wind condition for vehicle energy management and control, IEEE transactions on vehicular technology, vol. 62, no. 1, pp. 61-68, doi: 10.1109/TVT.2012.2218137.

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Title Stochastic models of road geometry and wind condition for vehicle energy management and control
Author(s) Khayyam, Hamid
Journal name IEEE transactions on vehicular technology
Volume number 62
Issue number 1
Start page 61
End page 68
Total pages 8
Publisher IEEE
Place of publication Piscataway, N.J.
Publication date 2013
ISSN 0018-9545
Keyword(s) probability distribution functions
road and wind modeling
stochastic modeling
vehicle energy management and control
vehicle modeling and simulation
Summary Modeling and simulation is commonly used to improve vehicle performance, to optimize vehicle system design, and to reduce vehicle development time. Vehicle performances can be affected by environmental conditions and driver behavior factors, which are often uncertain and immeasurable. To incorporate the role of environmental conditions in the modeling and simulation of vehicle systems, both real and artificial data are used. Often, real data are unavailable or inadequate for extensive investigations. Hence, it is important to be able to construct artificial environmental data whose characteristics resemble those of the real data for modeling and simulation purposes. However, to produce credible vehicle simulation results, the simulated environment must be realistic and validated using accepted practices. This paper proposes a stochastic model that is capable of creating artificial environmental factors such as road geometry and wind conditions. In addition, road geometric design principles are employed to modify the created road data, making it consistent with the real-road geometry. Two sets of real-road geometry and wind condition data are employed to propose probability models. To justify the distribution goodness of fit, Pearson's chi-square and correlation statistics have been used. Finally, the stochastic models of road geometry and wind conditions (SMRWs) are developed to produce realistic road and wind data. SMRW can be used to predict vehicle performance, energy management, and control strategies over multiple driving cycles and to assist in developing fuel-efficient vehicles.
Language eng
DOI 10.1109/TVT.2012.2218137
Field of Research 090203 Automotive Mechatronics
090602 Control Systems, Robotics and Automation
091307 Numerical Modelling and Mechanical Characterisation
Socio Economic Objective 850702 Energy Conservation and Efficiency in Transport
HERDC Research category C1 Refereed article in a scholarly journal
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Collection: School of Information Technology
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