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A methodology is presented to do accelerated vibration durability test, on Electro Dynamic Shaker (EDS) by using Power Spectral Density (PSD) profile based on typical customer usage pattern. A generalized iterative procedure is developed to optimize input excitation PSD profile on EDS for simulating the exact customer usage conditions. The procedure minimizes the error between the target channels measured on road and the response channels measured on EDS. Also, response of accelerometers and strain gauges at multiple locations on the test component are arrived at based on a single input excitation using this procedure. The same is verified experimentally as well. Different parameters like strain, acceleration, etc. are simulated simultaneously. This methodology has enabled successful simulation of road conditions in lab, thereby arriving at a correlation between rig and road. The correlation obtained is based on the simulation of the same failure mode as that of the road on the rig.

Vision based systems using cameras are widely used in various industry verticals. The basic functionality of a vision system is to detect an object and then recognize it. In current automotive industry these systems are being used in applications like collision avoidance, intelligent cruise control, blind spot detection, parking assistance, identify pedestrians, etc. During driving conditions, 2 wheeler and 4 wheeler drivers are required to concentrate more on the road because of which they may tend to miss the traffic signs; more often during night times. The traffic signs can be one way, U-turn, right/left turn prohibited, bump ahead and etc. So there is a need for a system which detects, recognizes and intimates these signs to the driver. Extensive research is being carried out in the area of recognizing a traffic sign, but more focused research is done for a complex problem of detecting the sign in the real world environment.

Two wheelers are very popular as means of transportation in ASIA. It is also used as load carrier in some places. Chassis frame is a very critical part of a two wheeler taking most of the loads coming from the roads. During the design and development stage, structural integrity of the frame needs to be established. Bump test is one of the critical life tests performed on the vehicle for evaluating the fatigue life of the frame. Normally, three to four iterations take place before frame passes this bump test. This is a time taking test process (1week per iteration) and does not guarantee the end result. In the new approach, the bump test simulation is made using ADAMS software. The ADAMS model is validated by using the axle accelerations measured in the physical bump test. Subsequently, the loads obtained from ADAMS model are used in FEM software and the stresses are predicted. The stress pattern helped in identifying the critical areas.

Tyres are the primary contact between the vehicle and the road. It serves as the medium of communication between the road and the rider, which it does in terms of road loads and displacements. Therefore, measurement of dynamic wheel forces experienced by a two-wheeler is crucial for tuning the ride and handling characteristics of the vehicle. Currently, there are standard wheel force transducers available in the market, which are extensively used in cars. However, mass of such a system is relatively high to be used on two-wheelers. Special wheels and adaptors increase the unsprung mass considerably, which changes the dynamics of the vehicle. Moreover, cost of such systems is exorbitantly high to be used for two-wheelers. This paper describes the development of an innovative and a highly versatile and low-cost alternative method for real-time measurement of dynamic wheel loads and moments of a two-wheeler when compared with the currently available systems in the market.

This paper aims at the estimation of dynamic wheel loads of a two-wheeler through mathematical modeling that will aid during the initial stages of product development. A half car model that represents a two-wheeler was used for this purpose. Road displacements were given as input to the model and the wheel loads estimated. Actual road data obtained from two-poster rig was used as input to the model thereby making it possible to calculate the wheel loads for different customer usage conditions on different roads. In this paper, a severe rough road was chosen for verification of the model with that of the rig as the rider dynamics on such roads are the most difficult to simulate even on the rigs. The estimated values from model were verified with those measured using a two-poster rig for the same road displacement. Attempt has been further made to establish a correlation between the ride comfort predictions from the model and the two-poster rig.