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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.

Medium trucks constitute a large market segment of the commercial transportation sector, and are also used widely for military tactical operations. Recent technological advances in hybrid powertrains and fuel cell auxiliary power units have enabled design alternatives that can improve fuel economy and reduce emissions dramatically. However, deterministic design optimization of these configurations may yield designs that are optimal with respect to performance but raise concerns regarding the reliability of achieving that performance over lifetime. In this article we identify and quantify uncertainties due to modeling approximations or incomplete information. We then model their propagation using Monte Carlo simulation and perform sensitivity analysis to isolate statistically significant uncertainties. Finally, we formulate and solve a series of reliability-based optimization problems and quantify tradeoffs between optimality and reliability.

A regenerative braking model for a parallel Hybrid Electric Vehicle (HEV) is developed in this work. This model computes the line and pad pressures for the front and rear brakes, the amount of generator use depending on the state of deceleration (i.e. the brake pedal position), and includes a wheel lock-up avoidance algorithm. The regenerative braking model has been developed in the symbolic programming environment of MATLAB/SIMULINK/STATEFLOW for downloadability to an actual HEV's control system. The regenerative braking model has been incorporated in NREL's HEV system simulation called ADVISOR. Code modules that have been changed to implement the new regenerative model are described. Resulting outputs are compared to the baseline regenerative braking model in the parent code. The behavior of the HEV system (battery state of charge, overall fuel economy, and emissions characteristics) with the baseline and the proposed regenerative braking strategy are first compared.