Employment of Real-Time/FPGA Architectures for Test and Control of Automotive Engines

Nowadays the production of increasingly complex and electrified vehicles requires the implementation of new control and monitoring systems. This reason, together with the tendency of moving rapidly from the test bench to the vehicle, leads to a landscape that requires the development of embedded hardware and software to face the application effectively and efficiently. The development of application-based software on real-time/FPGA hardware could be a good answer for these challenges: FPGA grants parallel low-level and high-speed calculation/timing, while the Real-Time processor can handle high-level calculation layers, logging and communication functions with determinism. Thanks to the software flexibility and small dimensions, these architectures can find a perfect collocation as engine RCP (Rapid Control Prototyping) units and as smart data logger/analyser, both for test bench and on vehicle application. Efforts have been done for building a base architecture with common functionalities capable of easily hosting application-specific control code. Several case studies originating in this scenario will be shown; dedicated solutions for protype applications have been developed exploiting a real-time/FPGA architecture as ECU (Engine Control Unit) and custom RCP functionalities, such as water injection and testing hydraulic brake control.

Investigation of innovative combustion systems for reduced fuel consumption and increased specific power production

This work resumes a wide variety of research activities carried out with the main objective of increasing the efficiency and reducing the fuel consumption of Gasoline Direct Injection engines, especially under high loads. For this purpose, two main innovative technologies have been studied, Water Injection and Low-Pressure Exhaust Gas Recirculation, which help to reduce the temperature of the gases inside the combustion chamber and thus mitigate knock, being this one of the main limiting factors for the efficiency of modern downsized engines that operate at high specific power. A prototypal Port Water Injection system was developed and extensive experimental work has been carried out, initially to identify the benefits and limitations of this technology. This led to the subsequent development and testing of a combustion controller, which has been implemented on a Rapid Control Prototyping environment, capable of managing water injection to achieve knock mitigation and a more efficient combustion phase. Regarding Low-Pressure Exhaust Gas Recirculation, a commercial engine that was already equipped with this technology was used to carry out experimental work in a similar fashion to that of water injection. Another prototypal water injection system has been mounted to this second engine, to be able to test both technologies, at first separately to compare them on equal conditions, and secondly together in the search of a possible synergy. Additionally, based on experimental data from several engines that have been tested during this study, including both GDI and GCI engines, a real-time model (or virtual sensor) for the estimation of the maximum in-cylinder pressure has been developed and validated. This parameter is of vital importance to determine the speed at which damage occurs on the engine components, and therefore to extract the maximum performance without inducing permanent damages.

Modelling, control and testing of internal combustion engines to minimize consumption and pollutant emissions

The objective of the PhD thesis was to research technologies and strategies to reduce fuel consumption and pollutants emission produced by internal combustion engines. In order to meet this objective my activity was focused on the research of advanced controls based on cylinder pressure feedback. These types of control strategies were studied because they present promising results in terms of engine efficiency enhancement. In the PhD dissertation two study cases are presented. The first case is relative to a control strategy to be used at the test bench for the optimisation of the spark advance calibration of motorcycle Engine. The second case is relative to a control strategy to be used directly on board of mining engines with the objective or reducing the engine consumption and correct ageing effects. In both cases the strategies proved to be effective but their implementation required the use of specific toolchains for the measure of the cylinder pressure feedback that for a matter of cost makes feasible the strategy use only for applications: • At test bench • In small-markets like large off-road engines The major bottleneck that prevents the implementation of these strategies on mass production is the cost of cylinder pressure sensor. In order to tackle this issue, during the PhD research, the development of a low-cost sensor for the estimation of cylinder pressure was studied. The prototype was a piezo-electric washer designed to replace the standard spark-plug washer or high-pressure fuel injectors gasket. From the data analysis emerged the possibility to use the piezo-electric prototype signal to evaluate with accuracy several combustion metrics compatible for the implementation of advanced control strategies in on-board applications. Overall, the research shows that advanced combustion controls are feasible and beneficial, not only at the test bench or on stationary engines, but also in mass-produced engines.

Development of sexing systems functional to mass production of Aedes albopictus sterile males

Aedes albopictus is a vector able to transmit several arboviruses. Due to its high impact on human health, it is important to develop an efficient control strategy for this pest. Nowadays, control based on chemical insecticides is limited by the number of available active principles and the occurrence of resistance. A valuable alternative to the conventional control strategies is the sterile insect technique (SIT) which relies on releasing sterile males of the target insect. Mating between wild females and sterile males results in no viable offspring. A crucial aspect of SIT is the production of a large number of sterile males with a low presence of females that can bite and transmit viruses. The present thesis aimed to find, implement and study the most reliable mechanical sex sorter and protocol to implement male productivity and reduce female contamination. In addition, I evaluated different variables and sorting protocols to enable female recovery for breeding purposes. Furthermore, I studied the creation of a hyper-protandric strain potentially able to produce only males. I also assessed the integration of artificial intelligence with an optical unit to identify sexes at the adult stage. All these applications helped to realise a mass production model in Italy with a potential weekly production of 1 million males. Moreover, I studied and applied for aerial sterile male release in an urban environment. This technology could allow the release of males in a wide area, overcoming environmental and urban obstacles. However, the development and application of drone technologies in a metropolitan area close to airports, such as in Bologna area, must fit specific requirements. Lastly, at Réunion Island, during a Short Term Scientific Mission France (AIM-COST Action), Indian Ocean, I studied the Boosted SIT application. Coating sterile males with Pyriproxyfen may help spread the insecticide into the larval breeding sites.

RNA interference technology as a potential control method for fruit and horticultural crops pathogens Botrytis cinerea and Plasmopara viticola

Chapter 1, a general introduction on Botrytis cinerea and its threat to crop production is presented. What Botrytis looks like, its life cycle, why it is a threat to agricultural production, its worldwide pest status, and its current state of management is further elaborated on. Chapter 2, a general introduction on Plasmopara viticola, its threat to grape production and management strategies presented. Chapter 3, titled " RNA Interference Strategies for Future Management of Plant Pathogenic Fungi: Prospects and Challenges ", presents the rapid improvement and extensive implementation of RNA interference (RNAi) technology for the management of fungal pathogens. In this chapter, we describe the application of exogenous RNAi involved in plant pathogenic fungi and discuss dsRNA production, formulation, and RNAi delivery methods. Chapter 4, titled " Exogenous dsRNAs against chitin synthase and glucan synthase genes suppress the growth of the pathogenic fungus Botrytis cinerea " addresses two important questions: Is RNAi technology functional for B. cinerea control ? And which target genes can be exploited for RNAi-based B.cinerea disease control ? Upon target genes selections, an exogenous RNAi protocol was set up and we could effectively deliver a known dose of bacterially produced double stranded RNA (dsRNA) to induce RNAi in B. cinerea. Chapter 5, titled " Double-Stranded RNA Targeting Dicer-Like Genes Compromises the Pathogenicity of Plasmopara viticola on Grapevine “, which deals mainly on RNAi induction against Plasmopara viticola. This chapter addresses two main questions: Is RNAi technology functional in contrasting Plasmopara viticola? And which target genes can be exploited for RNAi-based disease control in Plasmopara viticola?. In the last Chapter (Chapter 6) titled “General discussions and perspectives for future research”, the major research findings from this thesis are discussed together with perspectives for future research.

Development and testing of methodologies for the control and diagnosis of innovative combustion systems

In pursuit of aligning with the European Union's ambitious target of achieving a carbon-neutral economy by 2050, researchers, vehicle manufacturers, and original equipment manufacturers have been at the forefront of exploring cutting-edge technologies for internal combustion engines. The introduction of these technologies has significantly increased the effort required to calibrate the models implemented in the engine control units. Consequently the development of tools that reduce costs and the time required during the experimental phases, has become imperative. Additionally, to comply with ever-stricter limits on 〖"CO" 〗_"2" emissions, it is crucial to develop advanced control systems that enhance traditional engine management systems in order to reduce fuel consumption. Furthermore, the introduction of new homologation cycles, such as the real driving emissions cycle, compels manufacturers to bridge the gap between engine operation in laboratory tests and real-world conditions. Within this context, this thesis showcases the performance and cost benefits achievable through the implementation of an auto-adaptive closed-loop control system, leveraging in-cylinder pressure sensors in a heavy-duty diesel engine designed for mining applications. Additionally, the thesis explores the promising prospect of real-time self-adaptive machine learning models, particularly neural networks, to develop an automatic system, using in-cylinder pressure sensors for the precise calibration of the target combustion phase and optimal spark advance in a spark-ignition engines. To facilitate the application of these combustion process feedback-based algorithms in production applications, the thesis discusses the results obtained from the development of a cost-effective sensor for indirect cylinder pressure measurement. Finally, to ensure the quality control of the proposed affordable sensor, the thesis provides a comprehensive account of the design and validation process for a piezoelectric washer test system.

Industrial Demilitarized Zone and Zero Trust cybersecurity models for Industrial Control Systems

Today more than ever, with the recent war in Ukraine and the increasing number of attacks that affect systems of nations and companies every day, the world realizes that cybersecurity can no longer be considered just as a “cost”. It must become a pillar for our infrastructures that involve the security of our nations and the safety of people. Critical infrastructure, like energy, financial services, and healthcare, have become targets of many cyberattacks from several criminal groups, with an increasing number of resources and competencies, putting at risk the security and safety of companies and entire nations. This thesis aims to investigate the state-of-the-art regarding the best practice for securing Industrial control systems. We study the differences between two security frameworks. The first is Industrial Demilitarized Zone (I-DMZ), a perimeter-based security solution. The second one is the Zero Trust Architecture (ZTA) which removes the concept of perimeter to offer an entirely new approach to cybersecurity based on the slogan ‘Never Trust, always verify’. Starting from this premise, the Zero Trust model embeds strict Authentication, Authorization, and monitoring controls for any access to any resource. We have defined two architectures according to the State-of-the-art and the cybersecurity experts’ guidelines to compare I-DMZ, and Zero Trust approaches to ICS security. The goal is to demonstrate how a Zero Trust approach dramatically reduces the possibility of an attacker penetrating the network or moving laterally to compromise the entire infrastructure. A third architecture has been defined based on Cloud and fog/edge computing technology. It shows how Cloud solutions can improve the security and reliability of infrastructure and production processes that can benefit from a range of new functionalities, that the Cloud could offer as-a-Service.We have implemented and tested our Zero Trust solution and its ability to block intrusion or attempted attacks.

Application of the Extended Kalman filter for speed sensorless control of PM synchronous machines

The increasing interest in the decarbonization process led to a rapidly growing trend of electrification strategies in the automotive industry. In particular, OEMs are pushing towards the development and production of efficient electric vehicles. Moreover, research on electric motors and their control are exploding in popularity. The increase of computational power in embedded control hardware is allowing the development of new control algorithm, such as sensorless control strategy. Such control strategy allows the reduction of the number of sensors, which implies reduced costs and increased system reliability. The thesis objective is to realize a sensorless control for high-performance automotive motors. Several algorithms for rotor angle observers are implemented in the MATLAB and Simulink environment, with emphasis on the Kalman observer. One of the Kalman algorithms already available in the literature has been selected, implemented and benchmarked, with emphasis on its comparison with the Sliding Mode observer. Different models characterized by increasing levels of complexity are simulated. A simplified synchronous motor with ”constant parameters”, controlled by an ideal inverter is first analyzed; followed by a complete model defined by real motor maps, and controlled by a switching inverter. Finally, it was possible to test the developed algorithm on a real electric motor mounted on a test bench. A wide range of different electric motors have been simulated, which led to an exhaustive review of the sensorless control algorithm. The final results underline the capability of the Kalman observer to effectively control the motor on a real test bench.

A deep learning model for controlling the galvanizing process in a production line

In the industry of steelmaking, the process of galvanizing is a treatment which is applied to protect the steel from corrosion. The air knife effect (AKE) occurs when nozzles emit a steam of air on the surfaces of a steel strip to remove excess zinc from it. In our work we formalized the problem to control the AKE and we implemented, with the R&D dept.of MarcegagliaSPA, a DL model able to drive the AKE. We call it controller. It takes as input the tuple : a tuple of the physical conditions of the process line (t,h,s) with the target value of the zinc coating (c); and generates the expected tuple of (pres and dist) to drive the mechanical nozzles towards the (c). According to the requirements we designed the structure of the network. We collected and explored the data set of the historical data of the smart factory. Finally, we designed the loss function as sum of three components: the minimization between the coating addressed by the network and the target value we want to reach; and two weighted minimization components for both pressure and distance. In our solution we construct a second module, named coating net, to predict the coating of zinc resulting from the AKE when the conditions are applied to the prod. line. Its structure is made by a linear and a deep nonlinear “residual” component learned by empirical observations. The predictions made by the coating nets are used as ground truth in the loss function of the controller. By tuning the weights of the different components of the loss function, it is possible to train models with slightly different optimization purposes. In the tests we compared the regularization of different strategies with the standard one in condition of optimal estimation for both; the overall accuracy is ± 3 g/m^2 dal target for all of them. Lastly, we analyze how the controller modeled the current solutions with the new logic: the sub-optimal values of pres and dist can be optimize of 50% and 20%.

Enhancing the value of lignocellulosic biomasses through the production of bionanocomposites

The aim of this work was to optimize a methodology to extract cellulose and to produce NC, from different lignocellulosic biomasses (sorghum, Sorghum bicolor (L.) Moench and sunn hemp, Crotalaria juncea L.). In addition, the NC produced was tested as a reinforcing agent in chitosan (Ch) films, to understand its effects on the properties of this biopolymer. The nanoparticles obtained from sorghum and sunn hemp were incorporated in Ch films at a rate of 2.5% w/w of chitosan, and the resultant bionanocomposites (Sorghum NC films and sunn hemp NC films) were fully characterized in terms of their morphology, mechanical and optical properties, permeability (water vapor), water wettability, and FT-IR spectra analysis. Chitosan films reinforced with commercial nanocellulose at the same rate were tested for comparison, as well as pristine chitosan (control). Bionanocomposites made from sorghum and sunn hemp NC were slightly more saturated and opaque than the pristine chitosan films, in particular outer sorghum NC films. Sunn hemp NC films also showed a slightly higher thickness than sorghum NC films and pristine chitosan films. Further, the results confirmed that sorghum NC improved the strength and stiffness of the chitosan biopolymer and that sunn hemp NC improved the plasticity of the chitosan polymer. Hence, results indicate that those lignocellulosic crops may afford a source of NC for the production of bionanocomposites. Considering the application of those bionanocomposites by the food packaging industry, sorghum NC - chitosan films showed more promising results than sunn hemp NC-chitosan films.

An Asp49 Phospholipase A2 From Snake Venom Induces Cyclooxygenase-2 Expression And Prostaglandin E2 Production Via Activation Of Nf-κb, P38mapk, And Pkc In Macrophages.

Phospholipases A2 (PLA2) are key enzymes for production of lipid mediators. We previously demonstrated that a snake venom sPLA2 named MT-III leads to prostaglandin (PG)E2 biosynthesis in macrophages by inducing the expression of cyclooxygenase-2 (COX-2). Herein, we explored the molecular mechanisms and signaling pathways leading to these MT-III-induced effects. Results demonstrated that MT-III induced activation of the transcription factor NF-κB in isolated macrophages. By using NF-κB selective inhibitors, the involvement of this factor in MT-III-induced COX-2 expression and PGE2 production was demonstrated. Moreover, MT-III-induced COX-2 protein expression and PGE2 release were attenuated by pretreatment of macrophages with SB202190, and Ly294002, and H-7-dihydro compounds, indicating the involvement of p38MAPK, PI3K, and PKC pathways, respectively. Consistent with this, MT-III triggered early phosphorylation of p38MAPK, PI3K, and PKC. Furthermore, SB202190, H-7-dihydro, but not Ly294002 treatment, abrogated activation of NF-κB induced by MT-III. Altogether, these results show for the first time that the induction of COX-2 protein expression and PGE2 release, which occur via NF-κB activation induced by the sPLA2-MT-III in macrophages, are modulated by p38MAPK and PKC, but not by PI3K signaling proteins.

Impaired Incretin Secretion And Pancreatic Dysfunction With Older Age And Diabetes.

To estimate the impact of aging and diabetes on insulin sensitivity, beta-cell function, adipocytokines, and incretin production. Hyperglycemic clamps, arginine tests and meal tolerance tests were performed in 50 non-obese subjects to measure insulin sensitivity (IS) and insulin secretion as well as plasma levels of glucagon, GLP-1 and GIP. Patients with diabetes and healthy control subjects were divided into the following groups: middle-aged type 2 diabetes (MA-DM), aged Type 2 diabetes (A-DM) and middle-aged or aged subjects with normal glucose tolerance (MA-NGT or A-NGT). IS, as determined by the homeostasis model assessment, glucose infusion rate, and oral glucose insulin sensitivity, was reduced in the aged and DM groups compared with MA-NGT, but it was similar in the MA-DM and A-DM groups. Insulinogenic index, first and second phase insulin secretion and the disposition indices, but not insulin response to arginine, were reduced in the aged and DM groups. Postprandial glucagon production was higher in MA-DM compared to MA-NGT. Whereas the GLP-1 production was reduced in A-DM, no differences between groups were observed in GIP production. In non-obese subjects, diabetes and aging impair insulin sensitivity. Insulin production is reduced by aging, and diabetes exacerbates this condition. Aging associated defects superimposed diabetic physiopathology, particularly regarding GLP-1 production. On the other hand, the glucose-independent secretion of insulin was preserved. Knowledge of the complex relationship between aging and diabetes could support the development of physiopathological and pharmacological based therapies.

Hypothalamic Inflammation And The Central Nervous System Control Of Energy Homeostasis.

The control of energy homeostasis relies on robust neuronal circuits that regulate food intake and energy expenditure. Although the physiology of these circuits is well understood, the molecular and cellular response of this program to chronic diseases is still largely unclear. Hypothalamic inflammation has emerged as a major driver of energy homeostasis dysfunction in both obesity and anorexia. Importantly, this inflammation disrupts the action of metabolic signals promoting anabolism or supporting catabolism. In this review, we address the evidence that favors hypothalamic inflammation as a factor that resets energy homeostasis in pathological states.

Chitosan/tripolyphosphate Nanoparticles Loaded With Paraquat Herbicide: An Environmentally Safer Alternative For Weed Control.

Paraquat is a fast acting nonselective contact herbicide that is extensively used worldwide. However, the aqueous solubility and soil sorption of this compound can cause problems of toxicity in nontarget organisms. This work investigates the preparation and characterization of nanoparticles composed of chitosan and sodium tripolyphosphate (TPP) to produce an efficient herbicidal formulation that was less toxic and could be used for safer control of weeds in agriculture. The toxicities of the formulations were evaluated using cell culture viability assays and the Allium cepa chromosome aberration test. The herbicidal activity was investigated in cultivations of maize (Zea mays) and mustard (Brassica sp.), and soil sorption of the nanoencapsulated herbicide was measured. The efficiency association of paraquat with the nanoparticles was 62.6 ± 0.7%. Encapsulation of the herbicide resulted in changes in its diffusion and release as well as its sorption by soil. Cytotoxicity and genotoxicity assays showed that the nanoencapsulated herbicide was less toxic than the pure compound, indicating its potential to control weeds while at the same time reducing environmental impacts. Measurements of herbicidal activity showed that the effectiveness of paraquat was preserved after encapsulation. It was concluded that the encapsulation of paraquat in nanoparticles can provide a useful means of reducing adverse impacts on human health and the environment, and that the formulation therefore has potential for use in agriculture.

Influence Of Gastric Emptying On The Control Of Postprandial Glycemia: Physiology And Therapeutic Implications.

The maintenance of glucose homeostasis is complex and involves, besides the secretion and action of insulin and glucagon, a hormonal and neural mechanism, regulating the rate of gastric emptying. This mechanism depends on extrinsic and intrinsic factors. Glucagon-like peptide-1 secretion regulates the speed of gastric emptying, contributing to the control of postprandial glycemia. The pharmacodynamic characteristics of various agents of this class can explain the effects more relevant in fasting or postprandial glucose, and can thus guide the individualized treatment, according to the clinical and pathophysiological features of each patient.