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This paper presents the results of an experimental test campaign carried out on a city bus powered by serial hybrid power train. The driveline system combines an Internal Combustion Engine with a battery pack and two electric motors. Tests were aimed at identifying the salient signal characteristics of the noise spectra recorded during operating conditions and to assess the acoustic comfort in the passenger compartment. Transfer Path Analysis technique was applied to identify airborne and structure borne vibro-acoustic loads, to measure transfer functions linking source locations to target locations and to estimate the internal vibro-acoustic comfort in operating conditions.

One of the scientific fields where, for already more than 20 years, system identification plays a crucial role is this of structural dynamics and vibro-acoustic system optimization. The experimental approach is based on the “Modal Analysis” concept. The present paper reviews the test procedure and system identification principles of this approach. The main focus though is on the real problems with which engineers, performing modal analysis on complex structures on a daily basis, are currently confronted. The added value of several new testing approaches (laser methods, smart transducers…) and identification algorithms (spatial domain, subspace, maximum likelihood,..) for solving these problems is shown. The discussed elements are illustrated with a number of industrial case studies.

Active suspension systems aim at increasing safety by improving vehicle ride and handling performance while ensuring superior passenger comfort. Good control of this active system can only be achieved by providing the control algorithm with reliable and accurate signals for the required quantities. This paper presents the design and development of a state estimator that accurately provides the information required by a sky-hook controller, using a minimum of sensors. The vehicle inertial parameters are estimated by an algorithm based on Monte Carlo simulations and anthropometric data. All state updating is performed using Kalman filters. The resulting performance enhancement has been proven during test drives.