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Automotive steel wheel is a critical component for human safety. For validating steel wheel various tests will be performed at component and vehicle level. Cornering test performed at vehicle level is one of the tests, where wheel will be validated for high cornering loads. Cornering test performed at vehicle level consists of three different events i.e., rotations of vehicle in track1, rotations of vehicle track 2 and rotations of vehicle in track3. As wheel will experience different loading in each of the events of cornering test, correlating the virtual Finite Element Analysis (FEA) with physical test is quite challenging. If in FEA we can predict the damage and life very near to the physical validation, we can create a safe wheel for high cornering loads without any test concerns. Vent hole shape and Hat depth are two important aspects in wheel disc design. Vent hole shape and size will influence the heat dissipation of braking.

In automotive Body-In-White (BIW) structures, stiffness and the fatigue behavior is greatly influenced by the properties of its joints. Spot welding is one of the most widely used process for joining of sheet metals in BIW. Spot weld fatigue life under Accelerated Durability Test (ADT) is crucial for durability performance of BIW structures. Experience of BIW validations highlighted more number of spot weld failures in CAE when compared to actual tests. Hence, lot of iterations in the form of design modifications are required to be carried out to make these spot welds meet the targets which increases design & development time as well as cost. Current practice uses force-based approach for predicting spot weld fatigue life in CAE. To improve the spot weld fatigue life correlation, extensive study has been carried out on the approaches used for calculating spot weld fatigue life, namely force & stress-based approaches.

Automotive Suspension is one of the critical system in load transfer from road to Chassis or BIW. Using flex bodies in Multi body simulations helps to extract dynamic strain variation. This paper highlights how the MBD and FE integration helped for accurate strain prediction on suspension components. Overall method was validated through testing. Good strain correlation was observed in dynamic strains of constant amplitude in different loading conditions. Combination of different direction loading was also tested and correlated. Method developed can be used in the initial phase of the vehicle development program for suspension strength evaluation. Suspension is one of the important system in vehicle which is subjected to very high loading in all the directions. To predict the dynamic stresses coming on the suspension system due to transient loads, faster and accurate method is required. To accelerate the suspension design process it become necessary to get good accuracy in the results.