Abstract
<div class="section abstract"><div class="htmlview paragraph">Specific test systems are essential for the development and optimization of powertrains for two-wheeler applications. The World Motorcycle Test Cycle (WMTC) is prevalently used for type approval certification in terms of emissions and fuel consumption. In this respect, decreasing fuel consumption and increasing efficiency within the WMTC is an important development goal. The aim of the development project presented in this paper was to investigate how the robustness and repeatability of the measurement data can be increased by using a specific measurement procedure and test setup. As fuel consumption and emission levels reach ever lower levels, any influencing factors related to performance and emissions are of particular interest within the powertrain development phase.</div><div class="htmlview paragraph">When it comes to the differentiation of specific influencing factors such as lube oil behavior and its contribution to fuel consumption, very high measurement-repeatability and accuracy must be maintained. High measurement repeatability enables the effects resulting from deliberate changes in engineering variabilities to be distinguished from unintended measurement uncertainties.</div><div class="htmlview paragraph">This paper describes a measurement procedure to increase repeatability by using a dedicated test system for full 2-wheeler vehicle applications. This test setup utilizes a virtual driver unit to exclude uncertainties due to variable human driver behavior. An advanced mechanical test setup was employed to eliminate unwanted variations of powertrain properties such as wheel-slip or drive chain losses. The test system control mode was adopted to guarantee enhanced actuation stability and consistency. Additional measures to control boundary conditions were applied, for example test logic and measurement procedures were aligned to avoid drifts caused by external factors. In total, the derived test setup provided statistical cycle work measurement stability during transient test cycle operation with a coefficient of variation (CoV) in the magnitude of less than 0.07%. This improved measurement data quality is key for future technology improvements to meet market demands and legislative requirements.</div></div>
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