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Traditional Electronic Stability Control (ESC) for automobiles is usually accomplished through the use of estimated vehicle dynamics from simplified models that rely on parameters such as cornering stiffness that can change with the vehicle state and time. This paper proposes a different method for electronic stability control of oversteer by predicting the degree of instability in a vehicle. The algorithm is solely based on measurable response characteristics including lateral acceleration, yaw rate, speed, and driver steering input. These signals are appropriately conditioned and evaluated with fuzzy logic to determine the degree of instability present. When the “degree of instability” passes a certain threshold, the appropriate control action is applied to the vehicle in the form of differential yaw braking. Using only the measured response of the vehicle alleviates the problem of degraded performance when vehicle parameters change.

The primary objective of this paper is to develop a model that accurately represents the dynamics of drum brake through the components of its configuration. Detailed description will be that dynamic models for brake chamber, brake camshaft and brake shoe are built up respectively with consideration of various resistances from friction, inertia and return spring. These dynamic models are indirectly validated because the calculation values of the models are consistent with the results from the mechanism efficiency experiments of drum brake. According to these dynamic models, two different drum brakes with Involutes and Archimedes cam actuating mechanism have been researched.

We consider the modeling and control design of the regenerative braking system for heavy duty hybrid electric vehicles (HEVs) which have an isolated air-over-hydraulic (AOH) brake system and a generator. A nonlinear model is set up to characterize the behavior of the brake system. Then, the brake control is formulated as a torque tracking problem according to the driver's operations. The AOH brake system is appointed to track a constant brake torque; meanwhile, the generator is designed to track the torque error between the desired braking torque and the torque output of the AOH brake system. Finally, numerical experiments are carried out to verify the proposed model and control algorithms.

This paper proposes and compares torque distribution management strategies for vehicle stability control (VSC) of vehicles with independently driven wheels. For each strategy, the following feedback control variables are considered turn by turn: 1) yaw rate 2) lateral acceleration 3) both yaw rate and lateral acceleration. Computer simulation studies are conducted on the effects of road friction conditions, feedback controller gains, and a driver emulating speed controller. The simulation results indicated that all VSC torque management strategies are generally very effective in tracking the reference yaw rate and lateral acceleration of the vehicle on both dry and slippery surface conditions. Under the VSC strategies employed and the test conditions considered, the sideslip angle of the vehicle remained very small and always below the desired or target values.

From the viewpoint of energy conservation and transformation, this paper researches on the braking heat generation and brake temperature change characteristics during heavy-duty tractors brake, and a temperature-predicting model of brake drum is established. According to this model, firstly the entire vehicle kinetic energy is distributed thrice between front and rear axle, tire and road surface friction and sliding friction between hoof and drum, between linings and brake drum, and then the input heat of each drum brakes is figured out through the transformed kinetic energy. Secondly, each brake drum absorbs the heat and results in temperature rise, and dynamics temperature of brake drum is calculated considered cooling due to radiation, conduction, and convection.

In the next 20 years fully autonomous vehicles are expected to be in the market. The advance on their development is creating paradigm shifts on different automotive related research areas. Vehicle interiors design and human vehicle interaction are evolving to enable interaction flexibility inside the cars. However, most of today’s vehicle manufacturers’ autonomous car concepts maintain the steering wheel as a control element. While this approach allows the driver to take over the vehicle route if needed, it causes a constraint in the previously mentioned interaction flexibility. Other approaches, such as the one proposed by Google, enable interaction flexibility by removing the steering wheel and accelerator and brake pedals. However, this prevents the users to take control over the vehicle route if needed, not allowing them to make on-route spontaneous decisions, such as stopping at a specific point of interest.

Improper fit in a vehicle will affect a driver’s ability to reach the steering wheel and pedals, view the roadway and instrument gauges, and allow vehicle safety features to protect the driver during a crash. CarFit® is a community outreach program to educate older drivers on proper “fit” within their personal vehicle. A subset of measurements from CarFit® were used to quantify the “fit” of 97 older drivers over 60 and 20 younger drivers, ages 30-39, in their personal vehicles. Binary, logistic regression was used to assess the likelihood of drivers meeting the CarFit® measurement criteria prior to and after CarFit® education. The results showed older drivers were five times more likely than younger drivers to meet the CarFit® criteria for line of sight above the steering wheel, suggesting that younger drivers would also benefit from CarFit® education.