Stringent emission regulations are driving engine manufacturers to increase investment into enabling technologies to achieve better specific fuel consumption, thermal efficiency and most importantly carbon reduction. Engine downsizing is seen as a key enabler to successfully achieve all of these requirements. Boosting through turbocharging is widely regarded as one of the most promising technologies for engine downsizing. However, the wide range of engine speeds and loads requires enhanced quality of engine-turbocharger matching, compared to the conventional approach which considers only the full load condition. Thus, development of computational models capable of predicting the unsteady behaviour of a turbocharger turbine is crucial to the overall matching process. A purely one-dimensional (1D) turbine model is capable of good unsteady swallowing capacity predictions, however it has not been fully exploited to predict instantaneous turbine power. On the contrary, meanline models (zero-dimensional) are regarded as a good tool to determine turbine efficiency in steady state but they do not include any information about the pressure wave action occurring within the turbine. This paper explores an alternative methodology to predict instantaneous turbine power and swallowing capacity by integrating one-dimensional and meanline models. A single entry mixed-flow turbine is modelled using a 1D gas dynamic code to solve the unsteady flow state in the volute, consequently used as the input for a meanline model to evaluate the instantaneous turbine power. The key in the effectiveness of this methodology relies on the synchronisation of the flow information of different time scales. The model is validated against experimental data generated at Imperial College London under steady and pulsating flow conditions. Three rotational speeds (27.0, 43.0, and 53.7 rps/root K) and four pulse flow frequencies (20 to 80 Hz) are considered for performance validation. In addition to the turbine performance, the common level of unsteadiness is also compared based on Strouhal number evaluations. Furthermore, comparisons are made with the quasi-steady assumption in order to understand the strengths and weaknesses of the current method for effective unsteady turbine performance prediction. (C) 2014 Elsevier Ltd. All rights reserved.