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A vehicle’s performance and fuel economy plays an important role in obtaining a larger market share in the segment. This can be best achieved by optimizing the aerodynamics of the vehicle. Aerodynamics can be improved by altering the bodylines on a vehicle. Its drag coefficient can be maintained at a minimum value by properly designing various component profiles. The stability of a vehicle and Passenger comfort are affected by wind noise that is related to the aerodynamics of a vehicle. To study the effects of the above-mentioned parameters, the vehicle is tested inside a wind tunnel. In this paper, the authors study the body profile for different vehicles and analyze them using Computational Fluid Dynamics software - FLUENT. To study the influence of different body profiles on drag coefficient, 3 different vehicle segments are considered.

Vehicle Dynamics play an important role in responsiveness of a vehicle. The performance of a vehicle depends on its ride and handling characteristics [1]. Handling is a measure of the directional response of a vehicle and one of the important characteristics from the vehicle dynamics point of view. The directional response of a vehicle depends on the dynamics of the steering system. A good steering control provides an accurate feedback about how the vehicle reacts to the road. In this paper, the powerful techniques of Bond graphs and state equations [2] are used to design and analyze the dynamics of a manual rack and pinion steering system. The author obtains the transfer function between the Angle of rotation of front tire and the Angle of rotation of steering wheel. The overall steering ratio of the bond graph modeled steering system is compared with the overall ratio of a similar vehicle to validate the model.

Bond graph modeling is a powerful technique to study the complex interactions occurring between various components in a system. A few investigations were carried out to study vehicle dynamics using Bondgraphs, but are limited to 2 degree of freedom systems [1,2&3]. In this work, a 4-DOF-vehicle model was developed using bond graphs. A frequency response analysis was also carried out to study the natural frequencies. This model was later validated using Lagrangian principles. The results correlated well for a typical passenger car using the manufacturer supplied information available in the public domain.