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The engine tuning study presented here serves as an introduction to the basic concepts of implementing a motorcycle engine on an eddy current dynamometer test stand. This work represents the first engine tuning effort of a young FSAE® team and depicts the common challenges encountered by novice teams. The torque and power characteristics of a restricted 600 cc Suzuki GSXR engine were tuned in order to deliver the performance demands of an FSAE® vehicle. Coarse baseline fuel and ignition maps were initially developed manually and then optimized via a closed-loop algorithm. User-defined air-fuel ratios were automatically maintained throughout the engine's operating regime during this optimization process. Performance data were logged throughout each tuning cycle where spark timing and air-fuel ratio were varied accordingly to maximize power output. Spark settings were located approximately 10% before the knock threshold identified using a knock sensor.

The increasing push to accelerate the product design process and to minimize physical testing expense has promoted the development of hardware-in-the-loop testing procedures which couple well-defined virtual models with physical systems. Clear advantages include: 1) the advanced screening of candidate designs and control algorithms earlier in the product development phase, 2) lower overall testing cost to the manufacturer, 3) faster test times for design iterations, and 4) greater flexibility in the types of tests possible. This paper describes the design of an economical system that uses a parameterized, model-based vehicle simulation to control the operation of powertrain test cell hardware as part of a real-time test procedure. A commercially available vehicle simulation package allows for the modeling of a variety of chassis and powertrain combinations, along with a wide range of test procedures.

The number of control actuators available on spark-ignition engines is rapidly increasing to meet demand for improved fuel economy and reduced exhaust emissions. The added complexity greatly complicates control strategy development because there can be a wide range of potential actuator settings at each engine operating condition, and map-based actuator calibration becomes challenging as the number of control degrees of freedom expand significantly. Many engine actuators, such as variable valve actuation and flow control valves, directly influence in-cylinder combustion through changes in gas exchange, mixture preparation, and charge motion. The addition of these types of actuators makes it difficult to predict the influences of individual actuator positioning on in-cylinder combustion without substantial experimental complexity.

A hybrid electric vehicle simulation tool (HE-VESIM) has been developed at the Automotive Research Center of the University of Michigan to study the fuel economy potential of hybrid military/civilian trucks. In this paper, the fundamental architecture of the feed-forward parallel hybrid-electric vehicle system is described, together with dynamic equations and basic features of sub-system modules. Two vehicle-level power management control algorithms are assessed, a rule-based algorithm, which mainly explores engine efficiency in an intuitive manner, and a dynamic-programming optimization algorithm. Simulation results over the urban driving cycle demonstrate the potential of the selected hybrid system to significantly improve vehicle fuel economy, the improvement being greater when the dynamic-programming power management algorithm is applied.

A PC-based, computationally-efficient, quasi-dimensional simulation of HCCI engine performance and emissions has been developed with the intent to bridge the gap between zero-dimensional and sequential fluid-mechanic - thermo-kinetic models. The model couples a detailed chemistry description, a core gas model, a predictive boundary layer model, and a ring-dynamics crevice flow model. The thermal boundary layer, which is axially discretized to account for the relative piston motion, is modeled using compressible energy arguments. The ring-pack crevice zone is modeled using a coupled ring dynamic and flow model. The physically-based mathematical model is solved within the context of a single simulation framework, which lends to flexibility and expediency in performing a range of parametric studies. The simulation was validated under turbo-charged conditions using data obtained from a Caterpillar 3500 test engine.

A critical limitation preventing newer FSAE teams from improving in the international rankings is that of the person-machine interface, where driver inexperience and lack of training lead to loss of traction. The Traction Control System (TCS) described here uses closed-loop control of available engine power via spark retardation. Two distinct, driver-selectable algorithms were developed which govern TCS operation for either 1) launch control for the straight line acceleration event, or 2) full traction control for all other dynamic events. Launch control uses a spark retard rev limit to allow the driver to hold the engine at the ideal RPM for easy rev matching via flat foot shifting. Wheel speeds are simultaneously monitored to achieve ideal tire slip ratios. The full traction control algorithm uses the launch control method as a basis, but also addresses potential need for corner exit oversteer or engine braking.

The development and use of a simulation of an Integrated Starter Alternator (ISA) for a High Mobility Multi-purpose Wheeled Vehicle (HMMWV) is presented here. While the primary purpose of an ISA is to provide electric power for additional accessories, it can also be utilized for mild hybridization of the powertrain. In order to explore ISA's potential for improving HMMWV's fuel economy, an ISA model capable of both producing and absorbing mechanical power has been developed in Simulink. Based on the driver's power request and the State of Charge of the battery (SOC), the power management algorithm determines whether the ISA should contribute power to, or absorb power from the crankshaft. The system is also capable of capturing some of the braking energy and using it to charge the battery. The ISA model and the power management algorithm have been integrated in the Vehicle-Engine SIMulation (VESIM), a SIMULINK-based vehicle model previously developed at the University of Michigan.