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In order to reduce painful and injurious shear stresses for lower limb amputees, prosthetic ankle joints need to provide torsional control in the transverse plane. This paper attempts to characterize biological ankle function in the transverse plane with simple mechanical elements to assist in the design of a biomimetic prosthetic ankle joint. Motion capture data was collected from ten subjects walking in a straight trajectory to model four states of stance phase. Passive elements were chosen to model the ankle in each state. The ankle was observed to act as a quadratic torsional spring in State 1 and as linear torsional springs in States 2, 3 and 4. The results of this study should assist with the mechanical design and control of a biomimetic torsional prosthesis by suggesting a finite state control system and by providing the stiffness coefficients to be controlled for straight walking.

The flowfield around a 60% scale stationary Formula 1 tire in contact with the ground in a closed wind tunnel was examined experimentally in order to assess the accuracy of different turbulence modeling techniques. The results of steady RANS and Large Eddy Simulation (LES) were compared with PIV data, which was obtained within the same project. The far wake structure behind the wheel was dominated by two strong counter-rotating vortices. The locations of the vortex cores, extracted from the LES and PIV data as well as computed using different RANS models, showed that the LES predictions are closest to the PIV vortex cores. All turbulence models were able to accurately predict the region of strong downward velocity between the vortex cores in the center-plane of the tire, but discrepancies arose when velocity profiles were compared close to the inboard and outboard edges of the tire.

This study investigates using driver prediction to anticipate energy usage over a 160-meter look-ahead distance for a series, plug-in, hybrid-electric vehicle to improve conventional thermostatic powertrain control. Driver prediction algorithms utilize a hidden Markov model to predict route and a regression tree to predict speed over the route. Anticipated energy consumption is calculated by integrating force vectors over the look-ahead distance using the predicted incline slope and vehicle speed. Thermostatic powertrain control is improved by supplementing energy produced by the series generator with regenerative braking during events where anticipated energy consumption is negative, typically associated with declines or decelerations.

Regenerative braking is an important factor in improving hybrid electric vehicle efficiency. This paper proposes a new regenerative braking strategy that activates preemptively during a distracted driving scenario, before service brakes are utilized. The strategy uses onboard advanced driver assistance systems, such as forward facing radar, to detect when an object is approaching fast enough to enable regenerative braking in response. The proposed strategy is simulated on a full-vehicle model of a series plug-in hybrid electric vehicle. A driver model is developed to mimic the behavior of a distracted driver through delayed response time to the changing speed of a lead vehicle. Multiple trials are simulated using different combinations of existing regenerative braking strategies along with the proposed strategy. Results show that a preventative regenerative braking control strategy can recuperate significant amounts of energy while also improving vehicle safety.

Measurements from a Global Navigation System in conjunction with an Inertial Measurement Unit were recently introduced in different aerial and ground vehicles as an input to control vehicle dynamics. In automobiles this approach could help to further improve braking and / or stability control systems as information like velocity over ground and side slip angle becomes available. This paper presents the technical background, validation through test results and the evaluation of potential benefits of such an “INS/GPS” setup. As a result of the extended measuring capabilities a reduction in braking distance and a more effective stability control becomes possible. The results show an excellent performance that should be exploited in future automotive applications.

Pedal misapplications may be rare, but the outcomes can be tragic. A naturalistic driving study with 30 drivers was conducted to gain a better understanding of foot pedal behaviors. Foot movements were observed from the moment subjects entered and positioned themselves in their vehicle, and continued through starting the ignition, shifting into gear, accelerating to driving speed, and finally, resting their foot after parking the vehicle. A coding methodology was developed to categorize the various foot movements and behaviors. Over 3,300 startup and parking sequences were coded. This paper describes the unique challenges involved in classifying foot movements and behaviors when drivers’ intentions are not known. For example, hesitant or interrupted foot movements often occurred when a driver was transitioning from a gas pedal press to a brake pedal press.