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In today’s rapidly evolving automotive world, reduction of time to market has prime importance for a new product development. It is critical to have significant front-loading of the development activities to reduce development time while achieving best in class performance targets. Driver-in-the-loop (DIL) simulators have shown significant potential for achieving it, through real time subjective feedback at preliminary stages of the vehicle development. Recent advances in technology of driving simulators have enabled quite accurate representation steering and handling performance, also good prediction on primary ride and low frequency vibrations. In conventional damper development, the definition of the initial dampers tuning specifications typically requires a mule vehicle, or atleast, a comparable vehicle. However, this approach is associated with protracted iterations that consume substantial time and cost.

In recent years, the push for reduced product development timelines has been more than ever with significant changes in the automotive market. High electrification, intelligent vehicle systems and increased number for car manufacturers are a few key drivers to the same. The front loading of development activities is now a key focus area for achieving faster product development. From vehicle dynamics point of view availability of subjective evaluation feedback plays a key role in optimization various system specifications. This paper discusses an approach for front loading through parallel development of the tire and vehicle chassis system, using advanced simulation and driving simulator technology. The proposed methodology uses virtual tire models which in combination with real-time vehicle model enables subjective evaluation of vehicle performance in driver-in-loop simulators.

A vehicle simulation model is developed, validated and integrated into a closed-loop virtual driving environment using a state-of-the-art hexapod driving simulator. Thirty variant states are implemented and evaluated subjectively on steering and handling performance quality and quantity. Standard open-loop objective testing manoeuvres are simulated and performance metrics are calculated, allowing for a systematic cross-correlation process. Graphical analysis of the correlation metrics proves that chassis changes may accurately be felt through the simulator interface. It is proposed how obtained correlation models may serve for driver-feel optimizing target setting in early vehicle development stages, frontloading a great deal of costly prototype testing. System requirements are established and benefits and limitations are portrayed.