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General Motors has introduced a Two-Mode Transmission (2-MT) that provides significant improvements over the Toyota THS-II transmission. These improvements are achieved by employing additional planetaries with clutches and brakes to switch from a Mode-1 to Mode-2 as vehicle speed increases. In addition the 2-MT has four fixed-gear ratios that provide for a purely mechanical energy path from the IC engine to the driven wheels with the electric machines also able to provide additional driving torque. The purpose of this present paper is to extend the methodology in a previous paper [1] to include the 2-MT, thereby presenting an analytic foundation for its operation. The main contribution in this analysis is in the definition of dimensionless separation factors, defined in each mode that govern the power split between the parallel mechanical and electrical energy paths from the IC engine to the driven wheels.

It is common practice to validate diesel spray models against experimental diesel-spray images based on elastic light scattering, but the metric used to define the liquid boundary in a modeled spray can be physically inconsistent with the liquid boundary detected by light scattering measurements. In particular, spray models typically define liquid penetration based on a liquid mass threshold, while light scattering signal intensities are based on droplet size and volume fraction. These metrics have different response characteristics to changes in ambient conditions and fuel properties. Thus, when spray models are “tuned” or calibrated to match these types of measurements, the predictive capabilities of these models can be compromised. In this work, we compare two different liquid length metrics of an evaporating, non-reacting n-dodecane spray under diesel-like conditions using KIVA-3V.

With the advent of autonomous vehicles, the human driver’s attention will slowly be relinquished from the driving task. It will allow drivers to participate in more non-driving related activities, such as engaging with information and entertainment systems. However, the automated driving system would need to notify the driver of upcoming points-of-interest on the road when the driver’s attention is focused on their screen rather than on the road or driving display. In this paper, we investigated whether providing directional alerts for an upcoming point-of-interest (POI) in or around the user’s active screen can augment their ability in relocating their visual attention to the POI on the road when traveling in a vehicle with Conditional Driving Automation. A user study (N = 15) was conducted to compare solutions for alerts that presented themselves in the participants’ central and peripheral field of view.

An intelligent connected vehicle (ICV) swarm system that includes N vehicles is considered. Based on the special properties of potential functions, a kinematic model describing the swarm performances is proposed, which allows all vehicles to enclose the tracking target and show both tracking and formation characteristics. Treating the performances as the desired constraints, the analytical form of constraint forces can be obtained inspired by the Udwadia-Kalaba approaches. A special approach of uncertainty decomposition to deal with uncertain interferences is proposed, and a switching-type robust control method is addressed for each vehicle agent in the swarm system. The features and validity of the addressed control are demonstrated in the numerical simulations.

Trail-Braking (TB) is a common cornering technique used in rally racing to negotiate tight corners at (moderately) high speeds. In a previous paper by the authors it has been shown that TB can be generated as the solution to the minimum-time cornering problem, subject to fixed final positioning of the vehicle after the corner. A TB maneuver can then be computed by solving a non-linear programming (NLP). In this work we formulate an optimization problem by relaxing the final positioning of the vehicle with respect to the width of the road in order to study the optimality of late-apex trajectories typically followed by rally drivers. We test the results on a variety of corners. The optimal control inputs are approximated by simple piecewise linear input profiles defined by a small number of parameters. It is shown that the proposed input parameterization can generate close to optimal TB along the various corner geometries.