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The objective of this study is to develop, demonstrate and validate the methodology of external aerodynamic analysis of a State Road Transport bus for prediction of drag coefficient and its impact on fuel consumption with experimental validation. It has been verified that vehicle consumes around 40% of the available engine power to overcome the air drag. This gives us a huge scope to study the effect of aerodynamic drag. Baseline model of State Road Transport Bus was evaluated for estimating fuel consumption using Computational Fluid dynamics (CFD) methodology. The CFD results were validated with the experimental data with less than 10% deviation. Bus design was optimized with an objective of reducing the fuel consumption with parameters like angle of windshield, rounding and tapering corners and rear draft angle. Optimized bus design is also ensured to meet functional specifications as per AIS052.

A Generator set is comprised of mainly an Engine, Alternator and Chassis. High Horse-Power Generator development is challenging, with lots of complexities in physical and virtual validations. Creating high fidelity analytical model is always beneficial and economical at the design stages as it avoids repetitive tests on various design concepts. This paper reports analytical methods of developing an FEA model of a Generator for locomotive application and its correlation with Test. Highlighted as well are some of the challenges faced in FE modeling of a large Generator model (60 liters engine capacity) with node count of around 4 million. In this technique, Modal Analysis is first performed to capture the dynamic behavior. More than 95 % correlation is achieved between the FEA and test natural frequencies (Bending modes). Harmonic Analysis with Modal Superposition is then applied to understand the dynamic response of a Chassis under the action of engine vibratory loads.

The design and development of complete vehicle, understanding of chassis system development process is an important task. Chassis frame of a vehicle is supporting member, both structurally and functionally, to all other chassis aggregate systems viz. suspension, steering, braking system etc. In this paper, a methodology for chassis frame model construction and validation is explained. In present work, chassis frame model is validated in terms of modal parameters and also against static loading conditions. Existing chassis 3D Computer Aided Design (CAD) data was generated using scanning and cloud point data conversion technique. FE model was generated and validated through experimental measurements viz. modal testing, vertical bending, lateral bending, and torsional bending test. Loading and boundary conditions were replicated on the complete FE model in CAE domain and test validation was carried out using appropriate mesh biasing and weld modeling techniques.

The work presented in this paper deals with the use of non-linear FEA simulation in powertrain development. Prediction of cylinder bore distortion early in the design stage significantly affects overall performance of engine as bore distortion directly affects oil consumption, blowby and emission. The paper presents a methodology for predicting bore distortion with an objective of achieving improved performance of powertrain. For this purpose detailed Finite Element Model of Engine Assembly was prepared, nonlinear interaction between powertrain mating parts was captured by defining contacts, physical behaviour of gasket was captured through experimental testing by extracting loading and unloading pressure closure curve and the same data was used as an input for defining gasket nonlinear properties. Physical assembly sequence was captured by carrying out sequential analysis.

The work presented in this paper deals with the use of combined Computer Aided Engineering (CAE) and experimental testing approach for reducing engine noise. The paper describes a systematic approach for giving solutions to the structure borne engine noise related problems. Noise Source Identification (NSI) was carried out on diesel engine to identify noise radiating sources, ranking of noise sources was carried out and contribution of individual engine component in radiated Sound Power Level (SWL) was computed. Detailed Finite Element Model (FEM) of engine assembly was developed and model was correlated in terms of natural frequencies and transfer functions by performing modal testing. Correlated FEM was used for predicting surface vibration velocities under various engine speeds and loading conditions in frequency domain. Velocities so predicted in frequency domain were used as an input for SWL prediction using Boundary Element Method (BEM) approach.