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The recent advance in the development of various hybrid vehicle technologies comes along with the need of establishing optimal energy management strategies, in order to minimize both fuel economy and pollutant emissions, while taking into account an increasing number of state and control variables, depending on the adopted hybrid architecture. One of the objectives of this research was to establish benchmarking performance, in terms of fuel economy, for real time on-board management strategies, such as ECMS (Equivalent Consumption Minimization Strategy), whose structure has been implemented in a SIMULINK model for different hybrid vehicle concepts.

The purpose of this paper is to present some innovative techniques developed for an unconventional utilization of currently standard exhaust sensors, such as HEGO, UEGO, and NOx probes. In order to comply with always more stringent legislation about pollutant emissions, intake-exhaust systems are becoming even more complex and sophisticated, especially for CI engines, often including one or two UEGO sensors and a NOx sensor, and potentially equipped with both short-route and long-route EGR. Within this context, the effort to carry out novel methods for measuring the main exhaust gas dynamic properties exploiting sensors installed for different purposes, could be useful both for control applications, such as EGR rates estimation, or cost reduction, minimizing the on-board devices number. In this work, a gray-box model for measuring the gas mass flow rate, based on standard NOx sensor operating parameters of its heating circuit, is analyzed.