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  • Survey of the Dynamic Modeling Methods of Light Vehicles

    Vehicle dynamics models can be classified into two groups based on the model simplification. There are simplified models based on neglections, these models do not contain all body directions: longitudinal, lateral and vertical directions. There are several reasons for the simplification: control, estimation and analysis methods can be used only with simplified models, or another reason is the computational cost. Apart from simplified models, there are detailed/truth vehicle dynamics models which aim is to provide a virtual plant of the real vehicle for virtual prototype-based development. In this paper, some simplified vehicle models are presented, after a short introduction.

  • Parameter Estimation of Drag Coefficient and Rolling Resistance of Vehicles Based on GPS Speed Data

    In this paper, a parameter estimation method of the model-based design approach is applied to estimate the drag coefficient and the rolling resistance coefficient of a vehicle. In fact, a constant-force parameter (c_const) and a velocity-square-force parameter (c_square) are in the vehicle model, and these result in the sum force applied along the translational DOF that models the vehicle. It is only an assumption that the constant force is the rolling resistance and the force proportional to the square of the velocity is the drag force of the air. Only GPS speed data is used for the estimation process. The conclusion is that parameter estimation is a good alternative when expensive measurement devices are not available to measure the force losses separately and directly.

  • Vehicle Dynamics Simulation in Matlab/Simulink Environment

    In the following we are researching different methods of vehicle dynamics simulations. Starting from a simple two-wheeled vehicle model, we are showing ways to simulate the movement of vehicles with real suspensions on any surfaces. MATLAB, Simulink and Simscape provide very suitable resources for the above mentioned purposes. The benefits of such vehicle model become obvious because of the fact during the physics simulation we can access all the data we need to simulate any control algorithms for vehicles: in this article we are presenting a simple ABS control simulation.

  • Automated static structural FEA environment in MATLAB using Solid Edge and Femap

    Nowadays, CAD and FE software are getting integrated to each other. However, these new integrated pieces of software cannot be customized enough to analyze different optimization methods or model behavior. In this paper, a MATLAB environment is developed that connects to C# and VB programs, which use Solid Edge and Femap API functions, in order to automate the geometry modification and the FE model building and solving functions. A simple static structural size optimization problem is solved with the fmincon solver of MATLAB.

  • Vehicle Modelling and Simulation in Simulink

    In this paper a vehicle dynamics model is presented, which is an example that contains all the necessary aspects of making a decent vehicle model. Several examples show the use of such a model: basic vehicle dynamics phenomena can be recognized with the simulation of a detailed vehicle model. We are dealing with the connection between downforce and under/oversteer in this paper. In addition, the use of numerical simulations in the field of control systems is pointed out by an example of simulating an ABS control for the vehicle.

  • Survey of the Application Fields and Modeling Methods of Automotive Vehicle Dynamics Models

    In this paper, a review is presented on automotive vehicle dynamics modeling. Applied vehicle dynamics models from various application fields are analyzed and classified in the first section. Vehicle dynamics models may be simplified because of different reasons: several control/estimation/analysis methods are suitable only for simplified models (e.g. using control-oriented models), or because of the computational cost. Detailed/truth models of vehicle dynamics represent another field of vehicle dynamics modeling, these models play an important role in the virtual prototyping of vehicles. In the second section, the main modeling considerations of vehicle dynamics are presented in longitudinal, lateral and vertical directions. Various physical effects must be considered in the case of vehicle dynamics modeling, a lot of these effects are significant only in a specific direction of the vehicle body, which is the main potential of model simplification. The section presents vehicle modeling considerations in all of the three translational directions of the vehicle body.

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