Browse Publications Technical Papers 2015-26-0159

Latch Failure Prediction for Side Door Intrusion Test in CAE and Its Correlation with Physical Testing 2015-26-0159

During vehicle development, numerous test are done to ensure safety & durability of the vehicle. One such test prescribed by regulation (IS 12009:1995) is side door intrusion test (SDIT). This test evaluates strength requirement of a side door of passenger cars to minimize the safety hazards caused by intrusion into passenger compartment in a side impact accident viz., initial, intermediate and peak crush resistance. In current scenario the passenger car manufacturers are striving hard on cost reduction by reducing the development cost. Thus, to predict the exact vehicle performance before its prototype stage is vital. This can be achieved by evaluating performance by the help of Computer aided engineering (CAE)
During the SDIT, the load is applied to the outer surface of the door in an inward direction. This inward force applied by loading device is resisted by the door assembly, while door is pivoted at door latch and hinge. At Maruti Suzuki India Limited, CAE has achieved a good correlation with Physical testing in terms of predicting the deformation pattern, resistance force offered by door. In model development history, many times latch failure has been observed and due to this resistance offered by the door decreases significantly. Hence, Latch plays a very important role for estimating side door strength. Currently, the countermeasures for this latch failure are taken on the basis of repetitive physical testing because CAE methodology to predict latch failure is not available at present. Prediction of this failure if available in CAE will reduce the iterative physical testing and hence the cost and time involved in the vehicle development.
This paper presents a methodology adopted to address the issue of latch failure evaluation and the critical observations made during the course of study. The verification of the developed methodology is done by correlation of CAE results with physical test results.


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