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Browse AllThe once rarified field of Artificial Intelligence, and its subset field of Machine Learning have very much permeated most major areas of engineering as well as everyday life. It is already likely that few if any days go by for the average person without some form of interaction with Artificial Intelligence. Inexpensive, fast computers, vast collections of data, and powerful, versatile software tools have transitioned AI and ML models from the exotic to the mainstream for solving a wide variety of engineering problems. In the field of braking, one particularly challenging problem is how to represent tribological behavior of the brake, such as friction and wear, and a closely related behavior, fluid consumption (or piston travel in the case of mechatronic brakes), in a model. This problem has been put in the forefront by the sharply crescendo-ing push for fast vehicle development times, doing high quality system integration work early on, and the starring role of analysis-based tools in
The influence of moisture adsorption, prior braking, and deceleration rate on the low-speed braking noise has been investigated, using copper-free disc pads on a passenger car. With increasing moisture adsorption time, decreasing severity of prior braking or increasing deceleration rate, the noise sound level increases for the air-borne exterior noise as well as for the structure-borne interior noise. The near-end stop noise and the zero-speed start-to-move noise show a good correlation. Also, a good correlation is found between the noise measured on a noise dynamometer and on a vehicle for the air-borne noise. All the variables need to be precisely controlled to achieve repeatable and reliable results for dynamometer and vehicle braking groan noise tests. It appears that the zero-speed start-to-move vehicle interior noise is caused by the pre-slip vibration of the brake: further research is needed
Moisture adsorption and compression deformation behaviors of Semimet and Non-Asbestos Organic brake pads were studied and compared for the pads cured at 120, 180 and 240 0C. The 2 types of pads were very similar in moisture adsorption behavior despite significant differences in composition. After being subjected to humidity and repeated compression to 160 bars, they all deform via the poroviscoelastoplastic mechanism, become harder to compress, and do not fully recover the original thickness after the pressure is released for 24 hours. In the case of the Semimet pads, the highest deformation occurs with the 240 °C-cure pads. In the case of the NAO pads, the highest deformation occurs with the 120 0C-cure pads. In addition, the effect of pad cure temperatures and moisture adsorption on low-speed friction was investigated. As pad properties change all the time in storage and in service because of continuously changing humidity, brake temperature and pressure, one must question any
Many performance sport passenger vehicles use drilled or grooved cast iron brake rotors for a better braking performance or a cosmetic reason. Such brake rotors would unfortunately cause more brake dust emission, appearing with dirty wheel rims. To better understand the effects of such brake rotors on particle emission, a pin-on-disc tribometer with two particle emission measurement devices was used to monitor and collect the emitted airborne particles. The first device was an aerodynamic particle sizer, which is capable of measuring particles ranging from 0.5 to 20 μm. The second device was a condensation particle counter, which measures and collects particles from 4 nm to 3 μm. The testing samples were scaled-down brake discs (100 mm in diameter) against low-metallic brake pads. Two machined surface conditions (plain and grooved) with uncoated or ceramic-coated friction surfaces were selected for the investigation. The results showed that the grooved friction surface led to a higher
Toward the goal of “dual carbon economy” development, new energy hybrid commercial vehicles have become the main vehicles to meet the future fuel consumption and emission targets. In order to meet the high requirements of commercial vehicles on power and to minimize the influence of ambient temperature on the power of the vehicle, this study proposes a composite energy storage system (CESS) incorporating ultracapacitors. To further understand the impact of ultracapacitor on the dynamic performance of the vehicle, this study compares the dynamics of series range-extended hybrid pickup trucks with and without ultracapacitor at ambient and low temperatures, as well as the effect of ultracapacitor on the service life of lithium-ion batteries, by means of simulation. The results show that at room temperature (25°C), the addition of ultracapacitor shortens the 0–100 km/h acceleration time of the whole vehicle by 24.4% and improves the off-road climbing performance by 11.7%; at low
This article proposes a new model for a cooperative and distributed decision-making mechanism for an ad hoc network of automated vehicles (AVs). The goal of the model is to ensure safety and reduce energy consumption. The use of centralized computation resource is not suitable for scalable cooperative applications, so the proposed solution takes advantage of the onboard computing resources of the vehicle in an intelligent transportation system (ITS). This leads to the introduction of a distributed decision-making mechanism for connected AVs. The proposed mechanism utilizes a novel implementation of the resource-aware and distributed–vector evaluated genetic algorithm (RAD-VEGA) in the vehicular ad hoc network of connected AVs as a solver to collaborative decision-making problems. In the first step, a collaborative decision-making problem is formulated for connected AVs as a multi-objective optimization problem (MOOP), with a focus on energy consumption and collision risk reduction as