Comparative analysis of the emissions of carbon dioxide and toxic substances emitted by vehicles with ICE compared to the equivalent emissions of BEV

In the article were compared the vehicles (by pairing) the vehicles on the basis of selected criteria considering vehicles’: weight, length, wheel width, maximum output and acceleration time. The article was carried out by analysing the available source materials and specific energy mix based on coal. The emission of air pollutants (exhaustive) was estimated using the mathematical calculation. In order to carry out the analysis, the data provided by the manufacturers of the considered cars were used, concerning fuel consumption by the cars equipped with the internal combustion engines or electricity consumption in the case of cars with equipped with electric motors. The air pollutants that were taken into consideration: carbon monoxide, nitrogen oxides, sulphur dioxide, carbon dioxide, and total particulate matter. Apart from the exhaustive emissions, the total particular matter emissions from the tyre and brake wear and road abrasion is also included. The pollutant emission was estimated on the basis of emission factors using the average mileage characterizing for driving in European conditions.

Application of neural networks in predictions of brake wear particulate matter emission

According to the World Health Organization, air pollution with PM10 and PM2.5 (PM-particulate matter) is a significant problem that can have serious consequences for human health. Vehicles, as one of the main sources of PM10 and PM2.5 emissions, pollute the air and the environment both by creating particles by burning fuel in the engine, and by wearing of various elements in some vehicle systems. In this paper, the authors conducted the prediction of the formation of PM10 and PM2.5 particles generated by the wear of the braking system using a neural network (Artificial Neural Networks (ANN)). In this case, the neural network model was created based on the generated particles that were measured experimentally, while the validity of the created neural network was checked by means of a comparative analysis of the experimentally measured amount of particles and the prediction results. The experimental results were obtained by testing on an inertial braking dynamometer, where braking was performed in several modes, that is under different braking parameters (simulated vehicle speed, brake system pressure, temperature, braking time, braking torque). During braking, the concentration of PM10 and PM2.5 particles was measured simultaneously. The total of 196 measurements were performed and these data were used for training, validation, and verification of the neural network. When it comes to simulation, a comparison of two types of neural networks was performed with one output and with two outputs. For each type, network training was conducted using three different algorithms of backpropagation methods. For each neural network, a comparison of the obtained experimental and simulation results was performed. More accurate prediction results were obtained by the single-output neural network for both particulate sizes, while the smallest error was found in the case of a trained neural network using the Levenberg-Marquardt backward propagation algorithm. The aim of creating such a prediction model is to prove that by using neural networks it is possible to predict the emission of particles generated by brake wear, which can be further used for modern traffic systems such as traffic control. In addition, this wear algorithm could be applied on other vehicle systems, such as a clutch or tires.

Input Parameters for Airborne Brake Wear Emission Simulations: A Comprehensive Review

Non-exhaust emissions, generated by the wear of brake systems, tires, roads, clutches, and road resuspension, are responsible for a large part of airborne pollutants in urban areas. Brake wear accounts for 55% of non-exhaust emissions and significantly contributes to urban health diseases related to air pollution. A major part of the studies reported in the scientific literature are focused on experimental methods to sample and characterize brake wear particles in a reliable, representative, and repeatable way. In this framework, simulation is an important tool, which makes it possible to give interpretations of the experimental results, formulate new testing approaches, and predict the emission produced by brakes. The present comprehensive literature review aims to introduce the state of the art of the research on the different aspects of airborne wear debris resulting from brake systems which can be used as inputs in future simulation models. In this review, previous studies focusing on airborne emissions produced by brake systems are investigated in three main categories: the subsystem level, system level, and environmental level. As well as all the information provided in the literature, the simulation methodologies are also investigated at all levels. It can be concluded from the present review study that various factors, such as the uncertainty and repeatability of the brake wear experiments, distinguish the results of the subsystem and system levels. This gap should be taken into account in the development of future experimental and simulation methods for the investigation of airborne brake wear emissions.

Enclosure Design for Brake Wear Particle Measurement Using Computational Fluid Dynamics

The harmfulness of fine dust generated by automobile brakes to the environment has recently received attention. Therefore, we aimed to analyze and regulate the brake wear particles in dynamometers. To accurately measure the number of particles and particle mass, the sampling system used needs to minimize transportation losses and reduce the residence time in the brake enclosure system. The brake dust measurement system currently used can estimate the main transportation loss but cannot evaluate the complex flow field in the brake enclosure system under different design conditions. We used computational fluid dynamics (CFD) technology to predict the behavior of brake wear particles and analyze the static pressure characteristics, the uniformity of the system flow, and the residence time of the brake dust particles in the system. In addition, we compared the design of the basic structure of the brake enclosure system, combined with the four factors affecting the design of the brake dynamometer, with the enclosure system. As a result, we proposed that the design of the cross section of the brake dynamometer enclosure should be circular, the outlet angle of the enclosure should be 15°, the caliper should be fixed to 150°, and two sets of splitters should be added. This design improves pressure loss and reduces the residence time of brake dust particles in the brake enclosure system.