The Experts below are selected from a list of 59673 Experts worldwide ranked by ideXlab platform
Francois Dion - One of the best experts on this subject based on the ideXlab platform.
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Vehicle Dynamics Model for Estimating Maximum Light Duty Vehicle Acceleration Levels
2009Co-Authors: Hesham A. Rakha, Matthew Snare, Francois DionAbstract:This paper presents and validates a Vehicle Dynamics model for predicting maximum light-duty Vehicle accelerations for use within a microscopic traffic simulation environment. A database of unconstrained Vehicle acceleration data for 13 light-duty Vehicles and trucks is also constructed. Using field data, the proposed Vehicle Dynamics model is validated and compared with a number of state-of-the-art Vehicle acceleration models, including the Searle model and the dual-regime, linear decay, and polynomial models. The proposed model is shown to be able to predict Vehicle behavior accurately with readily available input parameters and is flexible in estimating acceleration rates of both large and small Vehicles on varied types of terrain. Directions for further research are discussed.
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Vehicle Dynamics MODEL FOR ESTIMATING MAXIMUM LIGHT-DUTY Vehicle ACCELERATION LEVELS
Transportation Research Record, 2004Co-Authors: Hesham A. Rakha, Matthew Snare, Francois DionAbstract:A Vehicle Dynamics model for predicting maximum light-duty Vehicle accelerations for use within a microscopic traffic simulation environment is presented and validated. The research also constructs a database of unconstrained Vehicle acceleration data for 13 light-duty Vehicles and trucks. With the use of the field data, the proposed Vehicle Dynamics model is validated and compared with a number of state-of-the-art Vehicle acceleration models, including the Searle model and the dual-regime, linear decay, and polynomial models. The advantages of the proposed model include its ability to predict Vehicle behavior accurately with readily available input parameters and its flexibility in estimating acceleration rates of both large and small Vehicles on varied types of terrain.
Hesham A. Rakha - One of the best experts on this subject based on the ideXlab platform.
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Vehicle Dynamics Model for Estimating Maximum Light Duty Vehicle Acceleration Levels
2009Co-Authors: Hesham A. Rakha, Matthew Snare, Francois DionAbstract:This paper presents and validates a Vehicle Dynamics model for predicting maximum light-duty Vehicle accelerations for use within a microscopic traffic simulation environment. A database of unconstrained Vehicle acceleration data for 13 light-duty Vehicles and trucks is also constructed. Using field data, the proposed Vehicle Dynamics model is validated and compared with a number of state-of-the-art Vehicle acceleration models, including the Searle model and the dual-regime, linear decay, and polynomial models. The proposed model is shown to be able to predict Vehicle behavior accurately with readily available input parameters and is flexible in estimating acceleration rates of both large and small Vehicles on varied types of terrain. Directions for further research are discussed.
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Vehicle Dynamics MODEL FOR ESTIMATING MAXIMUM LIGHT-DUTY Vehicle ACCELERATION LEVELS
Transportation Research Record, 2004Co-Authors: Hesham A. Rakha, Matthew Snare, Francois DionAbstract:A Vehicle Dynamics model for predicting maximum light-duty Vehicle accelerations for use within a microscopic traffic simulation environment is presented and validated. The research also constructs a database of unconstrained Vehicle acceleration data for 13 light-duty Vehicles and trucks. With the use of the field data, the proposed Vehicle Dynamics model is validated and compared with a number of state-of-the-art Vehicle acceleration models, including the Searle model and the dual-regime, linear decay, and polynomial models. The advantages of the proposed model include its ability to predict Vehicle behavior accurately with readily available input parameters and its flexibility in estimating acceleration rates of both large and small Vehicles on varied types of terrain.
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Vehicle Dynamics model for predicting maximum truck acceleration levels
Journal of Transportation Engineering-asce, 2001Co-Authors: Hesham A. Rakha, Ivana Lucic, Sergio Henrique Demarchi, Jose Reynaldo Setti, Michel Van AerdeAbstract:The paper presents a simple Vehicle Dynamics model for estimating maximum Vehicle acceleration levels based on a Vehicle's tractive effort and aerodynamic, rolling, and grade resistance forces. In addition, typical model input parameters for different Vehicle, pavement, and tire characteristics are presented. The model parameters are calibrated/validated against field data that were collected along the Smart Road test facility at Virginia Tech utilizing a truck and trailer for 10 weight-to-power configurations, ranging from 85 kg/kW to 169 kg/kW (140 lb/hp to 280 lb/hp). The model was found to predict Vehicle speeds at the conclusion of the travel along the section to within 5 km/h (3.1 mi/hr) of field measurements, thus demonstrating the validity and applicability of the model.
Matthew Snare - One of the best experts on this subject based on the ideXlab platform.
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Vehicle Dynamics Model for Estimating Maximum Light Duty Vehicle Acceleration Levels
2009Co-Authors: Hesham A. Rakha, Matthew Snare, Francois DionAbstract:This paper presents and validates a Vehicle Dynamics model for predicting maximum light-duty Vehicle accelerations for use within a microscopic traffic simulation environment. A database of unconstrained Vehicle acceleration data for 13 light-duty Vehicles and trucks is also constructed. Using field data, the proposed Vehicle Dynamics model is validated and compared with a number of state-of-the-art Vehicle acceleration models, including the Searle model and the dual-regime, linear decay, and polynomial models. The proposed model is shown to be able to predict Vehicle behavior accurately with readily available input parameters and is flexible in estimating acceleration rates of both large and small Vehicles on varied types of terrain. Directions for further research are discussed.
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Vehicle Dynamics MODEL FOR ESTIMATING MAXIMUM LIGHT-DUTY Vehicle ACCELERATION LEVELS
Transportation Research Record, 2004Co-Authors: Hesham A. Rakha, Matthew Snare, Francois DionAbstract:A Vehicle Dynamics model for predicting maximum light-duty Vehicle accelerations for use within a microscopic traffic simulation environment is presented and validated. The research also constructs a database of unconstrained Vehicle acceleration data for 13 light-duty Vehicles and trucks. With the use of the field data, the proposed Vehicle Dynamics model is validated and compared with a number of state-of-the-art Vehicle acceleration models, including the Searle model and the dual-regime, linear decay, and polynomial models. The advantages of the proposed model include its ability to predict Vehicle behavior accurately with readily available input parameters and its flexibility in estimating acceleration rates of both large and small Vehicles on varied types of terrain.
Raul G. Longoria - One of the best experts on this subject based on the ideXlab platform.
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Coordinated and reconfigurable Vehicle Dynamics control
IEEE Transactions on Control Systems Technology, 2009Co-Authors: Junmin Wang, Raul G. LongoriaAbstract:A coordinated reconfigurable Vehicle Dynamics control (CRVDC) system is achieved by high-level control of generalized forces/moment, distributed to the slip and slip angle of each tire by an innovative control allocation (CA) scheme. Utilizing control of individual tire slip and slip angles helps resolve the inherent tire force nonlinear constraints that otherwise may make the system more complex and computationally expensive. This in turn enables a real-time adaptable, computationally efficient accelerated fixed-point (AFP) method to improve the CA convergence rate when actuation saturates. Evaluation of the overall system is accomplished by simulation testing with a full-Vehicle CarSim model under various adverse driving conditions, including scenarios where Vehicle actuator failures occur. Comparison with several other Vehicle control system approaches shows how the system operational envelope for CRVDC is significantly expanded in terms of Vehicle global trajectory and planar motion responses.
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combined tire slip and slip angle tracking control for advanced Vehicle Dynamics control systems
Conference on Decision and Control, 2006Co-Authors: Junmin Wang, Raul G. LongoriaAbstract:This paper describes a combined tire longitudinal slip and lateral slip angle tracking control approach as part of an overall advanced Vehicle Dynamics control system. Nonlinear sliding mode control is used to manipulate the driving/braking/steering of each wheel to track slip and slip angles specified by a higher-level controller and a control allocation algorithm. Controlling slip and slip angles, which depend on individual wheel and Vehicle dynamic states, relies on a tire model to estimate the induced tire longitudinal and lateral forces as well as self-aligning moment. Further, Vehicle body states are treated here as exogenous signals independent of the slip/slip angle controller in order to isolate and simplify the control design. The performance of this control approach is evaluated and compared against results for conventional Vehicle control systems in a full-Vehicle CarSimreg model simulation. Improved performance is observed under an adverse split-mu hard braking scenario
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coordinated Vehicle Dynamics control with control distribution
American Control Conference, 2006Co-Authors: Junmin Wang, Raul G. LongoriaAbstract:This paper investigates a hierarchically coordinated Vehicle Dynamics control approach with individual wheel torque and steering actuation. A high-level robust nonlinear sliding mode controller is designed to determine the generalized forces/moments required to achieve Vehicle motion objectives. A weighted pseudo-inverse based control allocation method is employed for computationally efficient distribution of control effort to the slip and slip angle of each wheel. To avoid saturation, tire-road friction estimation is an essential part of the control distribution scheme. Two adverse driving scenario simulations are used to evaluate the effectiveness of this control system.
A Dais - One of the best experts on this subject based on the ideXlab platform.
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observation of lateral Vehicle Dynamics
Control Engineering Practice, 1996Co-Authors: Uwe Kiencke, A DaisAbstract:Abstract By observation of lateral Vehicle Dynamics the detection of critical driving situations is made possible, as well as the estimation of adhesion characteristics during cornering. This paper presents a comparison of a linear and a nonlinear observer for the Vehicle and tyre side-slip angles. The modelling, especially the model reduction and simplification, is shown.
