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It is not uncommon for complex engineering products to undergo several design iterations due to changing market expectations or inadequate performance. In such circumstances, a prototype is generally available that could be used for performance analysis before a revision to the design is made. The availability of a prototype can be an invaluable tool for the analysis of the impact of potential design changes on the system performance. In this paper, a process is proposed for the derivation of a physical model that could be used for design analysis. The process uses model identification for determination of model complexity and numerical optimization for estimation of model parameters. This process is applied to a new pneumatic fan clutch system that has been developed to improve the efficiency of engine temperature regulation in heavy-duty commercial vehicles. This system is currently in a prototype phase and its detailed physical model is required for design trade-off analysis

Advanced engine test methods incorporate several different sensing and signal processing techniques for identifying and locating manufacturing or assembly defects of an engine. A successful engine test method therefore, requires advanced signal processing techniques. This paper introduces a novel signal processing technique to successfully detect a faulty internal combustion engine in a quantitative manner. Accelerometers are mounted on the cylinder head and lug surfaces while vibration signals are recorded during engine operation. Using the engine's cam angular position, the vibration signals are transformed from the time domain to the crank-angle domain. At the heart of the transformation lies interpolation. In this paper, linear, cubic spline and sinc interpolation methods are demonstrated for reconstructing vibration signals in the crank-angle domain.