Abstract-Hybrid Vehicle fuel economy performance is highly sensitive to the energy management strategy used to select among multiple energy sources. Optimal solutions are easy to specify if the drive cycle is known a priori. It is very challenging to compute controllers that yield good fuel economy for a class of drive cycles representative of typical driver behavior. Additional challenges come in the form of constraints on powertrain activity, like shifting and starting the engine, which are commonly called "drivability" metrics. These constraints can adversely affect fuel economy. The benefits of including drivability restrictions in a Shortest Path Dynamic Programming (SPDP) formulation of the energy management problem are investigated for the first time. It is shown that this method yields up to 10% fuel economy improvement on a representative parallel electric hybrid when compared to a simpler instantaneous optimization formulation. This result is obtained by comparing a SPDP controller designed for drivability to a second SPDP controller, designed for fuel economy only, that uses an additional instantaneous optimization step for the incorporation of drivability. The results also quantify the tradeoff between drivability and fuel economy.

The 2004 Federal Tier II and California LEV I emission standards for diesel light trucks mandate tailpipe NOx levels of 0.6g∕mi. Active lean NOx catalysts (ALNC or LNC) have been proposed as a means to achieve this standard. These catalysts require the delivery of supplemental hydrocarbons in order to reduce NOx in the lean environment typical of diesel exhaust. In the system studied here, these additional hydrocarbons are injected into the exhaust system downstream of the turbocharger. A control-oriented, gray-box mathematical model is developed for diesel active lean NOx catalysts. The model represents the phenomena relevant to NOx reduction and HC consumption, namely, the catalyst chemical reactions, HC storage in the ALNC, and heat transfer behavior on the basis of an individual exhaust element. As an illustration of how the model may be used, dynamic programing is applied to determine the optimal trade-off of NOx conversion efficiency versus quantity of injected hydrocarbons.

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