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This paper covers the development of a closed loop transaxle synchronization algorithm which was a key deliverable in the control system design for the L3 Enigma, a Battery Dominant Hybrid Electric Vehicle. Background information is provided to help the reader understand the history that lead to this unique solution of the input and output shaft synchronizing that typically takes place in a manual vehicle transmission or transaxle when shifting into a gear from another or into a gear from neutral when at speed. The algorithm stability is discussed as it applies to system stability and how stability impacts the speed at which a shift can take place. Results are simulated in The MathWorks Simulink programming environment and show how traction motor technology can be used to efficiently solve what is often a machine design issue. The vehicle test bed to which this research is applied is a parallel biodiesel hybrid electric vehicle called the Enigma.

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2009 - 2011 EcoCAR: The NeXt Challenge Advanced Vehicle Technology Competition series organized by Argonne National Lab (ANL), and sponsored by General Motors Corporation (GM), and the U.S. Department of Energy (DOE). Following GM's Vehicle Development Process (VDP), HEVT established team goals that meet or exceed the competition requirements for EcoCAR in the design of a plug-in extended-range hybrid electric vehicle. The competition requires participating teams to improve and redesign a stock Vue XE donated by GM. The result of this design process is an Extended-Range Electric Vehicle (E-REV) that uses grid electric energy and E85 fuel for propulsion. The vehicle design is predicted to achieve an SAE J1711 utility factor corrected fuel consumption of 2.9 L(ge)/100 km (82 mpgge) with an estimated all electric range of 69 km (43 miles) [1].

For a hybrid electric vehicle (HEV) with an internal combustion engine, simply operating the engine in its regions of high efficiency does not guarantee the most fuel efficient operational strategy. This paper defines an operational strategy for a HEV through calculating individual powertrain component losses and comparing those losses across possible operational modes. The results of these calculations define how the vehicle can decrease fuel consumption while maintaining low vehicle emissions. The results presented are meant only to define a literal strategy; that is, an understanding as to why the vehicle should operate in a certain way given driver demands, vehicle speed, and powertrain limitations.

The Virginia Tech Hybrid Electric Vehicle Team (HEVT) has integrated a proton exchange membrane (PEM) fuel cell as the auxiliary power unit (APU) of a series hybrid design to produce a highly efficient zero-emission vehicle (ZEV). This design is implemented in a 1997 Chevrolet Lumina sedan, renamed ANIMUL H2, using an efficient AC induction drivetrain, regenerative braking, compressed hydrogen fuel storage, and an advance lead-acid battery pack for peak power load leveling. The fuel cell is sized to supply the average power demand and to sustain the battery pack state-of-charge (SOC) within a 40-80% window. To optimize system efficiency, the fuel cell is driven with a load-following control strategy. The vehicle is predicted to achieve a combined city/highway fuel economy of 4.3 L/100 km or 51 mpgge (miles per gallon gasoline equivalent).

EcoCAR 2: Plugging In to the Future (EcoCAR) is North America's premier collegiate automotive engineering competition, challenging students with systems-level advanced powertrain design and integration. The three-year Advanced Vehicle Technology Competition (AVTC) series is organized by Argonne National Laboratory, headline sponsored by the U. S. Department of Energy (DOE) and General Motors (GM), and sponsored by more than 28 industry and government leaders. Fifteen university teams from across North America are challenged to reduce the environmental impact of a 2013 Chevrolet Malibu by redesigning the vehicle powertrain without compromising performance, safety, or consumer acceptability. During the three-year program, EcoCAR teams follow a real-world Vehicle Development Process (VDP) modeled after GM's own VDP. The VDP serves as a roadmap for the engineering process of designing, building and refining advanced technology vehicles.

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) has integrated a proton exchange membrane fuel cell as the auxiliary power unit of a series hybrid design to produce a highly efficient zero-emission vehicle. A 1997 Chevrolet Lumina sedan, renamed ANIMUL H2, carries this advanced powertrain, using an efficient AC induction drivetrain, regenerative braking, compressed hydrogen fuel storage, and an advance lead-acid battery pack for peak power load leveling. The fuel cell supplies the average power demand and to sustain the battery pack state-of-charge within a 40-80% window. To optimize system efficiency, a load-following strategy controls the fuel cell power level. The vehicle weighed 2000kg (4400lb) and achieved a combined city/highway fuel economy of 9L/100 km or 26 mpgge (miles per gallon gasoline equivalent).

One of the most widely used computer simulation tools for hybrid electric vehicles (HEVs) is the ADvanced VehIcle SimulatOR (ADVISOR) developed by the National Renewable Energy Laboratory. The capability to quickly perform parametric and sensitivity studies for specific vehicles is a unique and invaluable feature of ADVISOR. However, no simulation tool is complete without being validated against measured vehicle data to insure the reliability of its predictions. This paper details the validation of ADVISOR using data from the Virginia Tech FutureCar Challenge Lumina, a series HEV. The modeling process is discussed in detail for each of the major components of the hybrid system: transmission; electric motor and inverter; auxiliary power unit (fuel and emissions); batteries; and miscellaneous vehicle parameters. The integration of these components into the overall ADVISOR model is also described. The results of the ADVISOR simulations are then explained.