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A typical powertrain mount design process starts with performing the system calculations to determine optimum mount parameters, viz. position, orientation and stiffness values to meet the desired NVH targets. Therefore, a 6 degrees of freedom lumped parameter system of powertrain and mounts is modelled in Matlab®. The approach is to decouple the torque roll axis mode from the remaining five rigid body modes so that the response to the torque pulses is predominantly ‘oscillations about Torque Roll Axis’. This is achieved by optimizing the above mount parameters within specified constraints so that ‘Rotation about the torque roll axis’ is one of the natural modes of vibration. The tool developed here uses ‘Particle Swarm Optimization(PSO) algorithm’ because of its ease of implementation and better convergence to the solution. The algorithm is programmed in TK solver®.

The concept definition phase of typical vehicle development focuses on the architecture definition and optimization based on different constraints/requirements. With the focus on Sustainability, the architecture optimization process must include “Light-weighting” as an optimization criterion. With only concept vehicle architecture available, the vehicle weight estimation becomes judgmental & inaccurate. This paper aims to address this deficiency with a new analytical approach for vehicle weight estimation. The new approach for vehicle weight estimation is a “bottom-up” approach using parametric models for each system weight with the inputs being the relevant vehicle specifications driving the system engineering. For size/shape-driven (rather than functional) systems, the models are content-based & segment-based. The parametric models are then iterated for multiple architecture concepts & specifications and the optimum concept (meeting all functional & business constraints) is chosen.