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In the last few years, the effect of diabatic test conditions on compressor performance maps has been widely investigated, leading some Authors to propose different correction models. The accuracy of turbocharger performance map constitute the basis for the tuning and validation of a numerical method, usually adopted for the prediction of engine-turbocharger matching. Actually, it is common practice in automotive applications to use simulation codes, which can either require measured compression ratio and efficiency maps as input values or calculate them “on the fly” throughout specific sub-models integrated in the numerical procedures. Therefore, the ability to correct the measured performance maps taking into account internal heat transfer would allow the implementation of commercial simulation codes used for engine-turbocharger matching calculations.

Today turbocharging represents a key technology to reduce fuel consumption and exhaust emissions for both Spark Ignition and diesel engines, moreover improving performance. 1D models, generally employed to compute the engine-turbocharger matching conditions, can be optimized basing on certain information about turbine and compressor behavior. Because of difficulty in the correct evaluation of turbine isentropic efficiency with direct techniques, turbocharger turbine efficiency is generally referred to thermomechanical efficiency. To this aim, the possibility to accurately estimate power losses in turbocharger bearings can allow the assessment of the turbine isentropic efficiency starting from the thermomechanical one. In the paper, an experimental and theoretical study on turbocharger mechanical losses is presented. The proposed model, developed in the MATLAB environment, refers to radial and axial bearings.

Downsizing and boosting is currently the principal solution to reduce fuel consumption in automotive engines without penalizing the power output. A key challenge for controlling the boost pressure during highly transient operations lies in avoiding to operate the turbocharger compressor in its instability region, also known as surge. While this phenomenon is well known by control engineers, it is still difficult to accurately predict during transient operations. For this reason, the scientific community has directed considerable efforts to understand the phenomena leading to the onset of unstable behavior, principally through experimental investigations or high-fidelity CFD simulations. On the other hand, less emphasis has been placed on creating control-oriented models that adopt a physics-based (rather than data-driven) approach to predict the onset of instability phenomena.