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The hybrid electric vehicle (HEV) is one of the solutions for reducing fuel consumption and hence cutting global warming pollution, since hybrid systems have been successfully applied in passenger cars and SUVs. For government agencies in Taiwan to open the market for HEV purchases and to make policies, the HEV's real ability to reduce fuel consumption in Taiwan's urban area needs to be evaluated. This paper discusses an HEV test project which was performed in an Asian urban area, Taipei city and county. Two HEVs - one Toyota Prius and one Ford Escape Hybrid were tested in the urban area by four different groups of drivers for two months. A data logging system was also installed on the HEV to record vehicle information during the driving. Results of the fleet test were also compared to the results performed by AVTA for HEV fuel economy in the urban area. Analysis showed that full HEVs did have high fuel economy in this Asian urban area.

A nonlinear model-based method for engine misfire detection has been proposed in the earlier work [2]. Many possible reasons for persistent cylinder misfire (e.g., a burned inlet valve or other faults), however, still need to be identified. Identification of engine misfire enables engineers, vehicle operators or technicians to trace the cause of misfire and to identify the faulty components in the engine. Also, a cylinder-by-cylinder manifold model will provide a considerably more accurate estimate of individual cylinder air flows. This paper develops a model-based nonlinear intake manifold pressure observer and an algorithm to identify a burned inlet valve. The proposed manifold model is a runner-by-runner model. A nonlinear observer using this runner-by-runner model can estimate the plenum pressure and all individual runner pressures and their subsequent flows. The estimate is then used as an indication of a faulty inlet valve, one of the possible causes of engine misfire.

Many researchers have studied and developed methods for on-board engine combustion misfire detection in production vehicles. Misfiring can damage the catalytic converter within a short time and can lead to increased emission levels. For that reason, the on-board detection of engine misfire is one requirement of the On Board Diagnosis II (OBDII) Regulation and a recent interest for many researchers. One object in this paper is to propose a misfire detection method for multi-cylinder SI engines. The detection is achieved by examining the estimated cylinder pressures and combustion heat release rates in engine cylinders. The Sliding Observer methodology is applied in these estimations. This detection method provides a reliable and low-cost way to diagnose engine misfires. The other object of the paper is to eliminate large estimation errors due to system unobservability and reconstruct cylinder pressures.