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Virtual validation of automobile components poses a huge challenge and needs continuous process improvements. One of such challenge in FE modelling of welds and understanding its behavior with respect to physical behavior. With the ongoing development of BSVI line of products in commercial vehicle industry, the virtual validation needs to be accurate and close to the physical behavior of the components. The learning and challenges faced during the previous development is implemented in the current study for weld simulation and correlation activity. The brackets welded to the power train components is taken as a challenge in the present work. Initially weld model was depicted in the CAD and was analyzed in CAE by providing proper FE connection. This practice had lot of flaws, approximations due to perpendicularity and flatness concerns in the models leading to consuming a lot of time in model preparation.

Lot of CAE (Computer Aided Engineering) based evaluation methods and DVPs (Design Verification Process) are available which are derived from acceleration data, strain data acquired on vehicle over proving ground. Using peak load summary from acceleration inputs generic gravity loads get derived. Use of these loads for CAE analysis are having certain advantages like faster concept level evaluation, broader perspective and confidence on concept design. But there are few limitations of using these methods like it gives only broader perspective of concept design and not able to capture many failure modes and locations as per RWUP (Real World Usage Pattern). This paper explains the advantages of using WFT (Wheel Force Transducer) data for getting more reliable, realistic and co-relating more failure modes on the vehicle. WFT data acquired on all four wheel-ends at wheel center. Each wheel end transducer records 3 translational and 3 rotational forces.

Diesel exhaust after treatment solutions using injection, such as urea-based SCR and lean NOx trap systems, effectively reduce the emission NOx level in various light vehicles, commercial vehicles, and industrial applications. The performance of the injector is crucial for successfully utilizing this type of technology, and a simulation tool plays an important role in the virtual design, that the performance of the injector is evaluated to reach the optimized design. The virtual test methodology using CFD to capture the fluid dynamics of the injector internal flow has been previously developed and validated for quantifying the dosing rate of the test injector. In this study, the capability of the virtual test methodology was extended to determine the spray angle of the test injector, and the effect of the manufacturing process on the injector internal nozzle flow characteristics was investigated using the enhanced virtual test methodology.

Diesel exhaust aftertreatment solutions using injection, such as urea-based SCR and lean NOx trap systems, effectively reduce the emission NOx level in various light vehicles, commercial vehicles, and industrial applications. The performance of the injector plays an important role in successfully utilizing this type of technology, and the CFD tool provides not only a time and cost-saving, but also a reliable solution for extensively design iterations for optimizing the injector internal nozzle flow design. Inspired by this fact, a virtual test methodology on injector dosing rate utilizing CFD was proposed for the design process of injector internal nozzle flows.

When a specialty tractor is operated by mounting the front loader or backhoes, the loads are distributed proportionately to the front and rear axles. The maximum load and fatigue life were identified as the main parameters in predicting fatigue failure. This paper mainly focuses on predicting front axle loads and fatigue life in front loader applications. To design a new front axle for the loader application, an existing front axle assembly that was designed for orchard, sprayer, and small farm application is selected for study and to extend it for front loader application with minimal design modifications. The major challenge is to estimate the dynamic loads coming to the front axle due to the front loader application and validate it for a different set of load cases as per the design verification plan. Hence a methodology was framed to estimate the actual loads using MBD, validate with field measurements, and verify the new front axle design using those loads in FEA.

The objective of this work is to find cumulative fatigue damage of the truck cabin caused by proving ground data. Stresses in the cabin are derived by finite element analysis using inertia relief method. Multi body simulation software ADAMS was used to obtain the load history at cabin attachment points using measured proving ground data as input. The fatigue damage of the truck cabin was estimated by linear super position method with static results and load history. The calculated numerical fatigue damage results were compared with physical test results and correlated.