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Valve train system is one major contributor to engine overall friction loss and is approximately 30% of total engine friction at lower speed and approximately 20 % at higher engine speed. Valve spring loads (preload and working) are proportional to friction loss of valve train. To optimizing the valve spring design main requirement is valve train perform it function safely at maximum engine cutoff RPM with minimum preload and working load. Robustness and frictional power loss are contradicting requirement, robustness demand high stiffness spring for better valve jump and bounce performance with dynamic safe valve spring design, on the other hand low frictional power loss demand for use of low stiffness spring. To optimize the valve spring stiffness for meeting both the requirement we need accurate prediction of valve spring in design stage and good correlation with testing data to reduce the number of iterations.

The system response of many engineering systems depends on time. A random process approach is therefore, needed to quantify variation or uncertainty. The system input may consist of a combination of random variables and random processes. In this case, a time-dependent reliability analysis must be performed to calculate the probability of failure within a specified time interval. This is known as cumulative probability of failure which is in general, different from the instantaneous probability of failure. Failure occurs if the limit state function becomes negative at least at one instance within a specified time interval. Time-dependent reliability problems appear if for example, the material properties deteriorate in time or if random loading is involved which is modeled by a random process. Existing methods to calculate the cumulative probability of failure provide an upper bound which may grossly overestimate the true value.

When a vehicle moves over uneven ground, motion of the sprung and unsprung masses causes dynamic shifting in the load transmitted to the ground, making the normal reaction in the tire-soil patch a continuously changing wheel parameter that may affect vehicle performance. At high loads, sinkage of the wheel can become high as the wheel digs into the soil. At low loads, the wheel can have difficulty acquiring sufficient traction. Additionally, steerability of the wheel can be diminished at very low loads. Controlling the damping forces in the suspension that is usually used to improve ride quality and stabilize motion of the sprung mass can result in an increase in the dynamic variation of the wheel normal reaction and cause vehicle performance deterioration. In this paper, a method is developed to establish boundary constraints on the dynamic normal reaction to maintain reasonable tire-terrain mobility characteristics.

To achieve acceptable valve train lubrication with low viscosity oil is challenging. Understanding the effect of valve train design parameter on valve train lubrication is important. In this study rocker arm valve train mechanism is analyzed to check the influence of valve train design parameters on lubrication at cam and rocker face interface. In valve train lubrication, lubrication oil film thickness play important role in valve train wear and friction. Main objective is to maintain acceptable oil film thickness at peak valve lift and minimizing the duration of critical minimum oil film thickness at cam flank to avoid wear at cam/ roller rocker follower interface when using low viscosity oil. Cam nose wear effect the engine performance and wear at cam flank change the dynamic characteristics of valve train.