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Objective metrics for performance evaluation of ride, handling and steering are required to compare, validate and optimize dynamic behavior of vehicles. Some of these objective metrics are recommended and defined by International Organization for Standardization (ISO) and Society of Automotive Engineers (SAE), which involve data processing, statistical analysis and complex mathematical operations on acquired data through simulation or experimental testing. Due to the complexity of operations and volume of data, evaluation is often time consuming and tedious. Process automation using existing tools such as MS Excel, nCode, Siemens LMS, etc. includes several limitations and challenges, which make it cumbersome to implement. This work is about development of a centralized platform for quantification, visualization and comparison of ride, handling and steering performance metrics obtained from testing and simulation data as per relevant ISO standards.

Ride is essentially the outcome of coupled dynamics of various involved sub-systems which make it too complex to deal analytically. Tires, amongst these, are known to be highly nonlinear compliant systems. Selection of tires specifications such as rated tyre pressure, etc. are generally decided through subjective assessment. While experts agree that tyre pressure affects the attributes such as ride to a noticeable degree, the quantification of the change often remains missing. In the current work, vibration levels of various sub-systems relevant to ride in an SUV are measured for three different tyre pressures at different speeds over the three randomly generated roads. For the purpose, artificial road profiles of classes A, B and C are synthesized from the spectrum of road classes defined in ISO 8608:2016 and reproduced on a four-poster test rig.