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The major area in which the automotive manufacturers are working is to produce high-performance vehicles with lighter weight, higher fuel economy and lower emissions. In this regard, hollow camshafts are widely used in modern diesel and gasoline engines due to their inherent advantages of less rotational inertia, less friction, less weight and better design flexibility. However, the dynamic loads of chain system, valve train and fuel injection pump (if applicable) makes it challenging to design over-head hollow camshafts with the required factor of safety (FOS). In the present work, high-fidelity FE model of a hollow camshaft assembly is simulated to evaluate the structural performance for assembly loads, valve train operating loads, fuel injection pump loads and chain system loads. The investigation is carried out in a high power-density (70 kW/lit) 4-cylinder in-line diesel engine.

Highly competitive automotive market demands shorter product development cycle while maintaining higher standards of performance in terms of durability and Noise Vibration & Harness (NVH). Engine cranktrain system is one of the major vibration sources in engine and first torsional mode frequency is a key parameter which influences vibration characteristics. Current CAE (Computer Aided Engineering) workflow for evaluating cranktrain system performance is time-consuming and takes around 55 Hrs. It involves crankshaft geometry cleanup, stiffness calculation, 1D model building and post processing. Over the time, significant historical data has been created while performing this virtual simulation during the product development cycle. Having a trained Machine Learning (ML) model based on this historical data, which can predict first torsional mode frequency accelerates the virtual validation. In this paper, prediction of first torsional frequency of cranktrain system using ML is presented.

Light weighting in modern automotive powertrains call for use of plastics (PP, PA66GF35) for cam covers, intake manifolds and style covers, and noise encapsulation covers. Conventionally, in early stage of design these components are evaluated for static assembly loads & gasket compression loads at component level. However, engine dynamic excitations which are random in nature make it challenging to evaluate these components for required fatigue life. In this paper, robust methodology to evaluate the fatigue life of engine style cover assembly for random vibration excitations is presented. The investigation is carried out in a high power-density 4-cylinder in-line diesel engine. The engine style cover (with Polyurethane foam) is mounted on cam cover and the intake manifold using steel studs and rubber isolators to suppress the radiated noise.