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Reducing energy consumption is a key focus for hybrid electric vehicle (HEV) development. The popular vehicle dynamic model used in many energy management optimization studies does not capture the vehicle dynamics that the in-vehicle measurement system does. However, feedback from the measurement system is what the vehicle controller actually uses to manage energy consumption. Therefore, the optimization solely using the model does not represent what the vehicle controller sees in the vehicle. This paper reports the utility factor-weighted energy consumption using a rule-based strategy under a real-world representative drive cycle. In addition, the vehicle test data was used to perform the optimization approach. By comparing results from both rule-based and optimization-based strategies, the areas for further improving rule-based strategy are discussed. Furthermore, recent development of OBD raises a concern about the increase of energy consumption. This paper investigates the energy consumption increase with extensive OBD usage.

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With proper control, exhaust gas recirculation (EGR) can be used for knock mitigation in SI engines, enabling fuel economy improvements through more optimal combustion phasing and lower fuel-enrichment at high loads. Due to significant pressure pulsations across the EGR valve, estimating the mass flow rates at transient and reversing flows across the valve can be challenging. Many systems utilize the pressure drop across a restriction in a flow path as an indication of mass flow. In automotive applications, the measurement of the pressure drop is accomplished by the use of a delta pressure sensor and the pressure drop mechanism could be a sharp edge orifice or other restrictions such as a valve opening. This technique works well for steady-state flow; however, if pressure fluctuations exist, especially at higher frequencies, this method of measuring mass flow can have large errors. The accuracy of EGR mass flow estimation based on a pressure differential (Δ P) measurement and the steady compressible flow orifice equation is investigated for various Δ P sensor frequencies and sampling rates on Ford 3.5L V6 GTDI and 2.3L I4 GTDI engines. This paper identifies the two major contributors of the error are the long length of the gauge lines and the close location of the downstream tap. The long length of the gauge line results in resonances at low frequency which affects the sensor performance. When the downstream tap is placed too close to the orifice, the accuracy of sensor reading is reduced. The proposed solution suggests keeping the gauge line as short as possible and the downstream tap at least two diameters away from the orifice and using a high-speed sensor. The result from engine testing shows a great improvement in the measurement accuracy by 43%. It is demonstrated that using a slow responding sensor with a low sample rate leads to erroneous mass flow calculation when significant pressure pulsations exist. A minimum of 1 kHz sample rate is needed to increase the accuracy of the EGR estimate within ±1%.

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