Urban and extra-urban hybrid vehicles: a technological review

Pollution derived from transportation systems is a worldwide, timelier issue than ever. The abatement actions of harmful substances in the air are on the agenda and they are necessary today to safeguard our welfare and that of the planet. Environmental pollution in large cities is approximately 20% due to the transportation system. In addition, private traffic contributes greatly to city pollution. Further, “vehicle operating life” is most often exceeded and vehicle emissions do not comply with European antipollution standards. It becomes mandatory to find a solution that respects the environment and, realize an appropriate transportation service to the customers. New technologies related to hybrid –electric engines are making great strides in reducing emissions, and the funds allocated by public authorities should be addressed. In addition, the use (implementation) of new technologies is also convenient from an economic point of view. In fact, by implementing the use of hybrid vehicles, fuel consumption can be reduced. The different hybrid configurations presented refer to such a series architecture, developed by the researchers and Research and Development groups. Regarding energy flows, different strategy logic or vehicle management units have been illustrated. Various configurations and vehicles were studied by simulating different driving cycles, both European approval and homologation and customer ones (typically municipal and university). The simulations have provided guidance on the optimal proposed configuration and information on the component to be used

Impact of Embedded Carbon Fiber Heating Panel on the Structural/Mechanical Performance of Roadway Pavement

INE/AUTC 12.3

The constrained median : a way to incorporate side information in the assessment of food samples

A classical problem in the field of food science concerns the consensus evaluation of food samples. Typically, several panelists are asked to provide scores describing the perceived quality of the samples, and subsequently, the overall (consensus) scores are determined. Unfortunately, gathering a large number of panelists is a challenging and very expensive way of collecting information. Interestingly, side information about the samples is often available. This paper describes a method that exploits such information with the aim of improving the assessment of the quality of multiple samples. The proposed method is illustrated by discussing an experiment on raw Atlantic salmon (Salmo salar), where the evolution of the overall score of each salmon sample is studied. The influence of incorporating knowledge of storage days, results of a clustering analysis, and information from additionally performed sensory evaluation tests is discussed. We provide guidelines for incorporating different types of information and discuss their benefits and potential risks

The predictive functional control and the management of constraints in GUANAY II autonomous underwater vehicle actuators

Autonomous underwater vehicle control has been a topic of research in the last decades. The challenges addressed vary depending on each research group's interests. In this paper, we focus on the predictive functional control (PFC), which is a control strategy that is easy to understand, install, tune, and optimize. PFC is being developed and applied in industrial applications, such as distillation, reactors, and furnaces. This paper presents the rst application of the PFC in autonomous underwater vehicles, as well as the simulation results of PFC, fuzzy, and gain scheduling controllers. Through simulations and navigation tests at sea, which successfully validate the performance of PFC strategy in motion control of autonomous underwater vehicles, PFC performance is compared with other control techniques such as fuzzy and gain scheduling control. The experimental tests presented here offer effective results concerning control objectives in high and intermediate levels of control. In high-level point, stabilization and path following scenarios are proven. In the intermediate levels, the results show that position and speed behaviors are improved using the PFC controller, which offers the smoothest behavior. The simulation depicting predictive functional control was the most effective regarding constraints management and control rate change in the Guanay II underwater vehicle actuator. The industry has not embraced the development of control theories for industrial systems because of the high investment in experts required to implement each technique successfully. However, this paper on the functional predictive control strategy evidences its easy implementation in several applications, making it a viable option for the industry given the short time needed to learn, implement, and operate, decreasing impact on the business and increasing immediacy.Peer ReviewedPostprint (author's final draft

Design and practical implementation of a fractional order proportional integral controller (FOPI) for a poorly damped fractional order process with time delay

One of the most popular tuning procedures for the development of fractional order controllers is by imposing frequency domain constraints such as gain crossover frequency, phase margin and iso-damping properties. The present study extends the frequency domain tuning methodology to a generalized range of fractional order processes based on second order plus time delay (SOPDT) models. A fractional order PI controller is tuned for a real process that exhibits poorly damped dynamics characterized in terms of a fractional order transfer function with time delay. The obtained controller is validated on the experimental platform by analyzing staircase reference tracking, input disturbance rejection and robustness to process uncertainties. The paper focuses around the tuning methodology as well as the fractional order modeling of the process' dynamics

Modeling and Optimal Design of Machining-Induced Residual Stresses in Aluminium Alloys Using a Fast Hierarchical Multiobjective Optimization Algorithm

The residual stresses induced during shaping and machining play an important role in determining the integrity and durability of metal components. An important issue of producing safety critical components is to find the machining parameters that create compressive surface stresses or minimise tensile surface stresses. In this paper, a systematic data-driven fuzzy modelling methodology is proposed, which allows constructing transparent fuzzy models considering both accuracy and interpretability attributes of fuzzy systems. The new method employs a hierarchical optimisation structure to improve the modelling efficiency, where two learning mechanisms cooperate together: NSGA-II is used to improve the model’s structure while the gradient descent method is used to optimise the numerical parameters. This hybrid approach is then successfully applied to the problem that concerns the prediction of machining induced residual stresses in aerospace aluminium alloys. Based on the developed reliable prediction models, NSGA-II is further applied to the multi-objective optimal design of aluminium alloys in a ‘reverse-engineering’ fashion. It is revealed that the optimal machining regimes to minimise the residual stress and the machining cost simultaneously can be successfully located

The assessment of complex learning outcomes

The Engineering Professors' Council (EPC) produced an output standard in 2000 containing a setof 26 generic statements of what an engineering graduate should have an ability to tackle. In addition, Higher Education (HE) is concerned with the promotion of complex or advanced understanding of subject matter. This leads to complex learning outcomes, which need to be adequately assessed. Changing demands mean changing assessment practices. While good practice is being used in many cases, there is a need to ensure assessment stimulates complex learning. The article seeks to address these issues

The 60s Turnaround as a Test on the Causal Relationship between Sociability and Happiness

The nexus between social leisure and life satisfaction is riddled with endogeneity problems. In investigating the causal relationship going from the first to the second variable we start from considering that retirement is an event after which the time investable in (the outside job) relational life increases. We instrument social leisure with the probability of retirement of the three and four years younger cohorts. With such approach we document that social leisure has a positive and significant effect on life satisfaction. Our findings shed some light on the age-happiness pattern. Policy implications are also discussed.Life satisfaction, relational goods, social capital