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Linear engine alternator (LEA) design optimization traditionally has been difficult because each independent variable alters the motion with respect to time, and therefore alters the engine and alternator response to other governing variables. An analogy is drawn to a conventional engine with a very light flywheel, where the rotational speed effectively is not constant. However, when springs are used in conjunction with an LEA, the motion becomes more consistent and more sinusoidal with increasing spring stiffness. This avoids some attractive features, such as variable compression ratio HCCI operation, but aids in reducing cycle-to-cycle variation for conventional combustion modes. To understand the cycle-to-cycle variations, we have developed a comprehensive model of an LEA with a 1kW target power in MATLAB®/Simulink, and an LEA corresponding to that model has been operated in the laboratory.

The control and design optimization of a Free Piston Engine Generator (FPEG) has been found to be difficult as each independent variable changes the piston dynamics with respect to time. These dynamics, in turn, alter the generator and engine response to other governing variables. As a result, the FPEG system requires an energy balance control algorithm such that the cumulative energy delivered by the engine is equal to the cumulative energy taken by the generator for stable operation. The main objective of this control algorithm is to match the power generated by the engine to the power demanded by the generator. In a conventional crankshaft engine, this energy balance control is similar to the use of a governor and a flywheel to control the rotational speed. In general, if the generator consumes more energy in a cycle than the engine provides, the system moves towards a stall.

Transit agencies across the United States operate bus fleets primarily powered by diesel, natural gas, and hybrid drive systems. Passenger loading affects the power demanded from the engine, which in turn affects distance-specific emissions and fuel consumption. Analysis shows that the nature of bus activity, taking into account the idle time, tire rolling resistance, wind drag, and acceleration energy, influences the way in which passenger load impacts emissions. Emissions performance and fuel consumption from diesel and natural gas powered buses were characterized by the West Virginia University (WVU) Transportable Emissions Testing Laboratory. A comparison matrix for all three bus technologies included three common driving cycles (the Braunschweig Cycle, the OCTA Cycle, and the ADEME-RATP Paris Cycle). Each bus was tested at three different passenger loading conditions (empty weight, half weight, and full weight).

Most transient heavy duty diesel emissions data in the USA have been acquired using the Federal Test Procedure (FTP), a heavy-duty diesel engine transient test schedule described in the US Code of Federal Regulations. The FTP includes both urban and freeway operation and does not provide data separated by driving mode (such as rural, urban, freeway). Recently, a four-mode engine test schedule was created for use in the Advanced Collaborative Emission Study (ACES), and was demonstrated on a 2004 engine equipped with cooled Exhaust Gas Recirculation (EGR). In the present work, the authors examined emissions using these ACES modes (Creep, Cruise, Transient and High-speed Cruise) and the FTP from a Detroit Diesel Corporation (DDC) Series 60 1992 12.7 liter pre-EGR engine. The engine emissions were measured using full exhaust dilution, continuous measurement of gaseous species, and filter-based Particulate Matter (PM) measurement.