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An automotive powertrain system consists of several interactive and linked nonlinear systems. This research focuses on the coordination of Gasoline Direct Injection (GDI) engine, transmission and emission aftertreatment systems. The goal is to design an optimal control strategy for driving performance, emissions (HC, CO, NOX), fuel economy and smoothness when switching engine mode and when shifting gears, under both discrete and continuous limitations. A multivariable control strategy is used to compromise among all powertrain subsystems to achieve optimal overall performance. A nonlinear discrete dynamic programming approach is proposed for hybrid system optimization. The complex multivariable automotive control problem is then simplified into an optimization problem. The feasibility of automotive hybrid control via the discrete dynamic programming approach is demonstrated by results from many numerical simulations under different operating conditions.

Gasoline Direct Injection (GDI) engine has a significant fuel economy improvement over the traditional port fuel injection engine. The tradeoff for this benefit is excessive exhaust emissions, especially NOx. Three-way-catalyst (TWC) is inefficient to treat NOx emission during lean operation. So Lean NOx Trap (LNT) is invented for NOx aftertreatment and it has both storage mode and purge mode. Research on modeling and control of LNT has been conducted, but it is still lack of the essential information on the temperature effect. This research focuses on the impact of trap temperature on LNT storage time, purge time and fuel economy. The mechanism of temperature effect on LNT is investigated at first. Then the temperature control strategy based on fuel economy improvement is proposed.