Madamedon, Misan, Gu, Fengshou, Aburass, Ali and Ball, Andrew (2016) Online Estimation of Engine Driveline Dynamic Properties. In: International Conference for Student on Applied engineering, 20-21st October 2016, Newcastle. (Unpublished)

This paper investigates the dynamics of the engine driveline system for achieving accurate and online diagnostics of engine conditions using instantaneous angular speed (IAS). Based on a state space modelling approach and key structures of the system, a torsional vibration model is developed and its modal properties: modal frequency, damping ratio and shapes are evaluated. Then taking the output data from the model as the input a latest stochastic subspace identification (SSI) method was implemented and result shows that the SSI approach is sufficiently accurate to extract these modal properties. Moreover, experimental studies show that the SSI approach can correctly extract modal properties under the low frequency range of interest based on just the transient IAS data acquired during engine shutdown, which confirms the theoretical analysis and provides the basis for the subsequent IAS based diagnosis development in which modal characteristics will be taken into account.

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