Fuel-Efficient Driving Strategies for Heavy-Duty Vehicles: A Platooning Approach Based on Speed Profile Optimization

A method for reducing the fuel consumption of a platoon of heavy-duty vehicles (HDVs) is described and evaluated in simulations for homogeneous and heterogeneous platoons. The method, which is based on speed profile optimization and is referred to as P-SPO, was applied to a set of road profiles of 10 km length, resulting in fuel reduction of 15.8% for a homogeneous platoon and between 16.8% and 17.4% for heterogeneous platoons of different mass configurations, relative to the combination of standard cruise control (for the lead vehicle) and adaptive cruise control (for the follower vehicle). In a direct comparison with MPC-based approaches, it was found that P-SPO outperforms the fuel savings of such methods by around 3 percentage points for the entire platoon, in similar settings. In P-SPO, unlike most common platooning approaches, each vehicle within the platoon receives its own optimized speed profile, thus eliminating the intervehicle distance control problem. Moreover, the P-SPO approach requires only a simple vehicle controller, rather than the two-layer control architecture used in MPC-based approaches

Analysis and Design of Vehicle Platooning Operations on Mixed-Traffic Highways

Platooning of connected and autonomous vehicles (CAVs) has a significant potential for throughput improvement. However, the interaction between CAVs and non-CAVs may limit the practically attainable improvement due to platooning. To better understand and address this limitation, we introduce a new fluid model of mixed-autonomy traffic flow and use this model to analyze and design platoon coordination strategies. We propose tandem-link fluid model that considers randomly arriving platoons sharing highway capacity with non-CAVs. We derive verifiable conditions for stability of the fluid model by analyzing an underlying M/D/1 queuing process and establishing a Foster-Lyapunov drift condition for the fluid model. These stability conditions enable a quantitative analysis of highway throughput under various scenarios. The model is useful for designing platoon coordination strategies that maximize throughput and minimize delay. Such coordination strategies are provably optimal in the fluid model and are practically relevant. We also validate our results using standard macroscopic (cell transmission model, CTM) and microscopic (Simulation for Urban Mobility, SUMO) simulation models

Адаптивні аеродинамічні елементи гоночного боліду класу «Formula SAE»

На основі аналізу конструкцій антикрил гоночних болідів команд «Formula SAE», визначено потребу в застосуванні прогресивних технологій виготовлення деталей аеродинамічного крила для покращення ходових характеристик автомобілю для участі в інженерно-спортивних змаганнях класу «Formula SAE». Такі технології є доступними для команд з середнім та високим рівнем достатку. В процесі роботи було проаналізовано конструкції аеродинамічних крил болідів та спроектовано адаптивне антикрило, яке змінює форму в залежності від умов. Для перевірки правильності проектування було виконано кінематичний та технологічний аналіз всіх вузлів та елементів. В результаті даної роботи було розроблено макет адаптивних антикрил з пластику та кріплення з металу. В дипломній роботі використовуються адитивні технології, а саме 3д друк скелету антикрила.On the basis of the analysis of the structures of the wing car racing Formula SAE teams, the need for the use of advanced technologies of manufacturing the parts of the aerodynamic wing to improve the running characteristics of the car for participation in engineering and sports competitions of the Formula SAE class was determined. Such technologies are available for mid- and high-level teams.In the process of the work, the car designs of previous seasons were analyzed and a new race car chassis and technological equipment for its production were designed. To verify the correct design, kinematic and technological analysis of all nodes and elements was performed. In the course of the work, the aerodynamic wings of the car were analyzed and an adaptive wing was designed, which changes shape depending on the conditions. To verify the correct design, kinematic and technological analysis of all nodes and elements was performed

Fuel-efficient driving strategies

This thesis is concerned with fuel-efficient driving strategies for vehicles driving on roads with varying topography, as well as estimation of road grade\ua0and vehicle mass for vehicles utilizing such strategies. A framework referred\ua0to as speed profile optimization (SPO), is introduced for reducing the fuel\ua0or energy consumption of single vehicles (equipped with either combustion\ua0or electric engines) and platoons of several vehicles. Using the SPO-based\ua0methods, average reductions of 11.5% in fuel consumption for single trucks,\ua07.5 to 12.6% energy savings in electric vehicles, and 15.8 to 17.4% average\ua0fuel consumption reductions for platoons of trucks were obtained. Moreover,\ua0SPO-based methods were shown to achieve higher savings compared to\ua0the commonly used methods for fuel-efficient driving. Furthermore, it was\ua0demonstrated that the simulations are sufficiently accurate to be transferred\ua0to real trucks. In the SPO-based methods, the optimized speed profiles were\ua0generated using a genetic algorithm for which it was demonstrated, in a\ua0discretized case, that it is able to produce speed profiles whose fuel consumption\ua0is within 2% of the theoretical optimum.A feedforward neural network (FFNN) approach, with a simple feedback\ua0mechanism, is introduced and evaluated in simulations, for simultaneous estimation of the road grade and vehicle mass. The FFNN provided road grade\ua0estimates with root mean square (RMS) error of around 0.10 to 0.14 degrees,\ua0as well as vehicle mass estimates with an average RMS error of 1%, relative\ua0to the actual value. The estimates obtained with the FFNN outperform road\ua0grade and mass estimates obtained with other approaches