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During the design conception of an automobile, typically low-fidelity physics-based simulations are coupled with engineering judgement to define key architectural components and subsystems which limits the capability to identify NVH issues arising from systems interaction. This translates to non-optimal designs because of unexplored design opportunities and therefore, lost business efficiencies. The sparse design information available during the design conception phase limits the development of representative higher fidelity physics-based simulations. To address that restriction on design optimization opportunities, this paper introduces an alternate approach to develop reduced order predictive models using regression techniques by harnessing historical measurement and simulation data. The concept is illustrated using two driveline NVH phenomenon: axle whine and take-off shudder.

NVH requirements are critical in new driveline developments. Failure modes due to resonances must be carefully analyzed and potential root causes must have adequate countermeasures. One of the most common root causes is the modal alignment. This work shows the steps to design and optimize a new plastic bracket for an automotive half shaft bearing. This bracket replaces a very stiff bracket, made of cast iron. The initial design of plastic bracket was not stiff enough to bring natural frequency of the system above engine second order excitation at maximum speed. The complete power pack was modeled and NVH CAE analysis was performed. The CAE outputs included Driving Point Response, Frequency Response Function and Modal analysis. The boundary conditions were discussed deep in detail to make sure the models represented actual system.

This paper presents a web-based tool to calculate gear and bearing forces for a front or rear axle. Force equilibrium is ensured in both gear and bearing load calculations for front and rear axles in both drive and coast modes.

A building-block method, often used for simulating automotive systems, is described in this paper for simulating a driveline system. In the method, a driveline supplier's design responsible components are modeled with explicit FE models. Model accuracy is verified by testing and correlating the components in a free-free condition. Non-design responsible components are modeled using lumped parameters and/or modal models. These components and the validated design responsible components are integrated into a system model and connected using simple lumped parameter connections. Correlation at the system level is performed by making adjustments to the connection parameters and to the parameters of the non-design responsible components. The resulting system model has been used to accurately predict operating responses in a driveline system.