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In the conceptualization phase of vehicle development, for achieving reasonable dynamics performance, proper selection of steering system meeting all the requirements is necessary. This requires accurate prediction of major steering performance attributes like steering effort, steering torque, Turning Circle Diameter (TCD), %Ackerman and steering returnability. However, currently available models majorly depend on Computer Aided Engineering (CAE)-analysis or physical trials which requires system detailing and the same cannot be used for early prediction of the steering performances in the concept phase. This paper aims to address this deficiency with the help of a new steering performance calculator. In the calculator, performance attributes namely steering effort, steering torque, TCD and %-Ackerman has been modelled with engineering calculations and other attributes namely steering returnability&precision has been modelled through machine learning techniques.

Body-over-Frame is the primary type of construction used in SUVs, pick-ups, and other commercial vehicles in India. In this type of construction, the body, engine, suspensions etc. are mounted on the ladder frame. Since the frame acts as the skeleton of the vehicle, optimal design of frame at the concept stage of the vehicle program is critical for meeting all structural performance targets. Frontloading of these targets aids in architecture development and reduces future design modifications. The natural frequency response from the frame directly affects the NVH performance of the vehicle. This paper focuses on frontloading the natural frequency targets by performing concept-level simulations on the ladder frame even before creation of 3D concept data. A parametric beam model is created based on the reference vehicles. The beam model has been validated with correlation of more than 85% compared with CAE and physical testing outputs of existing vehicles.