Development of an Adaptive Efficient Thermal/Electric Skipping Control Strategy Applied to a Parallel Plug-in Hybrid Electric Vehicle

In recent years automobile manufacturers focused on an increasing degree of electrification of the powertrains with the aim to reduce pollutants and CO2 emissions. Despite more complex design processes and control strategies, these powertrains offer improved fuel exploitation compared to conventional vehicles thanks to intelligent energy management. A simulation study is here presented aiming at developing a new control strategy for a P3 parallel plug-in hybrid electric vehicle. The simulation model is implemented using vehicle modeling and simulation toolboxes in MATLAB/Simulink. The proposed control strategy is based on an alternative utilization of the electric motor and thermal engine to satisfy the vehicle power demand at the wheels (Efficient Thermal/Electric Skipping Strategy-ETESS). The choice between the two units is realized through a comparison between two equivalent fuel rates, one related to the thermal engine and the other related to the electric consumption. An adaptive function is introduced to develop a charge-blended control strategy. The novel adaptive control strategy (A-ETESS) is applied to estimate fuel consumption along different driving cycles. The control algorithm is implemented on a dedicated microcontroller unit performing a Processor-In-the-Loop (PIL) simulation. To demonstrate the reliability and effectiveness of the A-ETESS, the same adaptive function is built on the Equivalent Consumption Minimization Strategy (ECMS). The PIL results showed that the proposed strategy ensures a fuel economy similar to ECMS (worse of about 2% on average) and a computational effort reduced by 99% on average. This last feature reveals the potential for real-time on-vehicle applications

Potential of hydrogen addition to natural gas or ammonia as a solution towards low- or zero-carbon fuel for the supply of a small turbocharged SI engine

Nowadays there is an increasing interest in carbon-free fuels such as ammonia and hydrogen. Those fuels, on one hand, allow to drastically reduce CO2 emissions, helping to comply with the increasingly stringent emission regulations, and, on the other hand, could lead to possible advantages in performances if blended with conventional fuels. In this regard, this work focuses on the 1D numerical study of an internal combustion engine supplied with different fuels: pure gasoline, and blends of methane-hydrogen and ammonia-hydrogen. The analyses are carried out with reference to a downsized turbocharged two-cylinder engine working in an operating point representative of engine operations along WLTC, namely 1800 rpm and 9.4 bar of BMEP. To evaluate the potential of methane-hydrogen and ammonia-hydrogen blends, a parametric study is performed. The varied parameters are air/fuel proportions (from 1 up to 2) and the hydrogen fraction over the total fuel. Hydrogen volume percentages up to 60% are considered both in the case of methane-hydrogen and ammonia-hydrogen blends. Model predictive capabilities are enhanced through a refined treatment of the laminar flame speed and chemistry of the end gas to improve the description of the combustion process and knock phenomenon, respectively. After the model validation under pure gasoline supply, numerical analyses allowed to estimate the benefits and drawbacks of considered alternative fuels in terms of efficiency, carbon monoxide, and pollutant emissions

Efficient Thermal Electric Skipping Strategy Applied to the Control of Series/Parallel Hybrid Powertrain

The optimal control of hybrid powertrains represents one of the most challenging tasks for the compliance with the legislation concerning CO2 and pollutant emission of vehicles. Most common off-line optimization strategies (Pontryagin minimum principle-PMP-or dynamic programming) allow to identify the optimal control along a predefined driving mission at the expense of a quite relevant computational effort. On-line strategies, suitable for on-vehicle implementation, involve a certain performance degradation depending on their degree of simplification and computational effort. In this work, a simplified control strategy is presented, where the conventional power-split logics, typical of the above-mentioned strategies, is here replaced with an alternative utilization of the thermal and electric units for the vehicle driving (Efficient Thermal Electric Skipping Strategy-ETESS). The choice between the units is realized at each time and is based on the comparison between the effective fuel rate of the thermal engine and an equivalent fuel rate related to the electrical power consumption. The equivalent fuel rate in a pure electric driving is associated to a combination of brake specific fuel consumption of the thermal engine, and electro-mechanical efficiencies along the driveline. The ETESS is applied for the simulation of segment C hybrid vehicle, equipped with a thermal engine and two electric units (motor and generator). The methodology is tested along regulatory driving cycles (WLTP, Artemis) and RDE, with different powertrain variants. Numerical results underline that the proposed approach performs very close to most common control strategies (consumed fuel per kilometer higher than PMP of about 1% on average). The main advantage is a reduced computational effort (decrease of 99% on average). The ETESS is straightforwardly adapted for an on-line implementation, through the introduction of an adaptative factor, preserving the computational effort and the fuel economy

1D numerical and experimental investigations of an ultralean pre-chamber engine

In recent years, lean-burn gasoline Spark-Ignition (SI) engines have been a major subject of investigations. With this solution, in fact, it is possible to simultaneously reduce NOx raw emissions and fuel consumption due to decreased heat losses, higher thermodynamic efficiency, and enhanced knock resistance. However, the real applicability of this technique is strongly limited by the increase in cyclic variation and the occurrence of misfire, which are typical for the combustion of homogeneous lean air/fuel mixtures. The employment of a Pre-Chamber (PC), in which the combustion begins before proceeding in the main combustion chamber, has already shown the capability of significantly extending the lean-burn limit. In this work, the potential of an ultralean PC SI engine for a decisive improvement of the thermal efficiency is presented by means of numerical and experimental analyses. The SI engine is experimentally investigated with and without the employment of the PC with the aim to analyze the real gain of this innovative combustion system. For both configurations, the engine is tested at various speeds, loads, and air-fuel ratios. A commercial gasoline fuel is directly injected into the Main Chamber (MC), while the PC is fed in a passive or active mode. Compressed Natural Gas (CNG) or Hydrogen (H2) is used in the actual case. A 1D model of the engine under study is implemented in a commercial modeling framework and is integrated with “in-house developed” sub-models for the simulation of the combustion and turbulence phenomena occurring in this unconventional engine. The numerical approach proves to reproduce the experimental data with good accuracy, without requiring any case-dependent tuning of the model constants. Both the numerical and experimental results show an improvement of the indicated thermal efficiency of the active PC, compared to the conventional ignition device, especially at high loads and low speeds. The injection of H2 into the PC leads to a significant benefit only with very lean mixtures. With the passive fueling of the PC, the lean-burn limit is less extended, with the consequent lower improvement potential for thermal efficiency

The European Association for the Study of Obesity (EASO) Endorses the Milan Charter on Urban Obesity

The Milan Charter on Urban Obesity highlights the challenges of urban environments as a battleground for human health, as cities are often organized to subvert public health goals, and promote rather than prevent the development of obesity and consequent non-communicable diseases. The Charter articulates ten principles which detail actions and strategies through which general practitioners, diverse medical specialists, related healthcare professionals, administrators and healthcare practice managers, policy actors - within health systems and at a national level - along with experts across disciplines, and citizens, can work in cooperation to meet this challenge and improve publichealth. The Charter urges the adoption of decisions that deliver the following: (i) policies which enable our cities to become healthier and less obesogenic, more supportive of well-being and less health-disruptive in general, and (ii) policies that fully support primary prevention strategies, that address social stigma, and that ensure fair access to treatment for people living with obesity. The Milan Charter on Urban Obesity aims to raise awareness of our shared responsibility for the health of all citizens, and focuses on addressing the health of people living with obesity - not only as a challenge in its own right, but a gateway to other major non-communicable diseases, including cardiovascular diseases, type 2 diabetes, and some cancers

Assessing chemical mechanisms underlying the effects of sunflower pollen on a gut pathogen in bumble bees

Many pollinator species are declining due to a variety of interacting stressors including pathogens, sparking interest in understanding factors that could mitigate these outcomes. Diet can affect host-pathogen interactions by changing nutritional reserves or providing bioactive secondary chemicals. Recent work found that sunflower pollen (Helianthus annuus) dramatically reduced cell counts of the gut pathogen Crithidia bombi in bumble bee workers (Bombus impatiens), but the mechanism underlying this effect is unknown. Here we analyzed methanolic extracts of sunflower pollen by LC-MS and identified triscoumaroyl spermidines as the major secondary metabolite components, along with a flavonoid quercetin-3-O-hexoside and a quercetin-3-O-(6-O-malonyl)-hexoside. We then tested the effect of triscoumaroyl spermidine and rutin (as a proxy for quercetin glycosides) on Crithidia infection in B. impatiens, compared to buckwheat pollen (Fagopyrum esculentum) as a negative control and sunflower pollen as a positive control. In addition, we tested the effect of nine fatty acids from sunflower pollen individually and in combination using similar methods. Although sunflower pollen consistently reduced Crithidia relative to control pollen, none of the compounds we tested had significant effects. In addition, diet treatments did not affect mortality, or sucrose or pollen consumption. Thus, the mechanisms underlying the medicinal effect of sunflower are still unknown; future work could use bioactivity-guided fractionation to more efficiently target compounds of interest, and explore non-chemical mechanisms. Ultimately, identifying the mechanism underlying the effect of sunflower pollen on pathogens will open up new avenues for managing bee health

Adaptive ECMS based on speed forecasting for the control of a heavy-duty fuel cell vehicle for real-world driving

Aiming at reducing pollutant emissions, hydrogen and fuel cell hybrid electric vehicles (FCVs) represent a promising technological solution. In this scenario, this paper proposes an adaptive energy management strategy (A-EMS) based on speed forecasting for a heavy-duty FCV, in order to achieve stable battery charge sustenance in realistic driving conditions. A validated and optimized fuel cell system model has been integrated into a complete vehicle model developed in the GT-Suite environment. A short-term velocity prediction layer based on a long short term memory (LSTM) neural network has been built in the A-EMS framework. The network has been trained and tested with realistic driving data simulated by GT-Real Drive for routes of the Trans-European Transport Network. The vehicle speed prevision has been realized over different forecasting horizons (5, 10, and 20 s). The adaptive equivalent consumption minimization strategy (A-ECMS) combined with short-term vehicle speed prediction is the A-EMS core algorithm of the presented work. Its results are here compared with the standard ECMS (S-ECMS) for four different driving cycles, including both standardized (HDDT) and realistic driving profiles. Three different European routes, with varying characteristics and from different countries, have been selected to test the proposed strategy in various conditions. The short-term prediction layer achieves satisfactory forecasting accuracy, with a RMSE ranging from 1.76 km/h to 13.37 km/h. The A-ECMS provides an improved by an order of magnitude battery charge sustenance, evaluated in terms of maximum battery state of charge (SoC) variation and fluctuation degree, with a hydrogen consumption increase ranging from 3.76% to 11.40% compared to the S-ECMS, for which the driving cycle is supposed to be known beforehand. As an example, in the HDDT cycle, the absolute maximum SoC variation and its fluctuation degree are lowered by about 76% and 79%, respectively. In conclusion, the proposed A-ECMS demonstrated that it is applicable for real driving conditions without prior knowledge of the driving cycle while improving battery charge sustaining for a FCV

Development of an efficient thermal electric skipping strategy for the management of a series/parallel hybrid powertrain

In recent years, the development of hybrid powertrain allowed to substantially reduce the CO2 and pollutant emissions of vehicles. The optimal management of such power units represents a challenging task since more degrees of freedom are available compared to a conventional pure-thermal engine powertrain. The a priori knowledge of the driving mission allows identifying the actual optimal control strategy at the expense of a quite relevant computational effort. This is realized by the off-line optimization strategies, such as Pontryagin minimum principle—PMP—or dynamic programming. On the other hand, for an on-vehicle application, the driving mission is unknown, and a certain performance degradation must be expected, depending on the degree of simplification and the computational burden of the adopted control strategy. This work is focused on the development of a simplified control strategy, labeled as efficient thermal electric skipping strategy—ETESS, which presents performance similar to off-line strategies, but with a much-reduced computational effort. This is based on the alternative vehicle driving by either thermal engine or electric unit (no power-split between the power units). The ETESS is tested in a “backward-facing” vehicle simulator referring to a segment C car, fitted with a hybrid series-parallel powertrain. The reliability of the method is verified along different driving cycles, sizing, and efficiency of the power unit components and assessed with conventional control strategies. The outcomes put into evidence that ETESS gives fuel consumption close to PMP strategy, with the advantage of a drastically reduced computational time. The ETESS is extended to an online implementation by introducing an adaptative factor, resulting in performance similar to the well-assessed equivalent consumption minimization strategy, preserving the computational effort

A phenomenological model for the description of unburned hydrocarbons emission in ultra-lean engines

The adoption of lean-burn concepts for internal combustion engines working with a homogenous air/fuel charge is under development as a path to simultaneously improve thermal efficiency, fuel consumption, nitric oxides, and carbon monoxide emissions. This technology may lead to a relevant emission of unburned hydrocarbons (uHC) compared to a stoichiometric engine. The uHC sources are various and the relative importance varies according to fuel characteristics, engine operating point, and some geometrical details of the combustion chamber. This concern becomes even more relevant in the case of engines supplied with natural gas since the methane has a global warming potential much greater than the other major pollutant emissions. In this work, a simulation model describing the main mechanisms for uHC formation is proposed. The model describes uHC production from crevices and flame wall quenching, also considering the post-oxidation. The uHC model is implemented in commercial software (GT-Power) under the form of “user routine”. It is validated with reference to two large bore engines, whose bores are 31 and 46 cm (engines named accordingly W31 and W46). Both engines are fueled with natural gas and operated with lean mixtures (λ > 2), but with different ignition modalities (pre-chamber device or dual fuel mode). The engines under study are preliminarily schematized in the 1D simulation tool. The consistency of 1D engine schematizations is verified against the experimental data of BMEP, air flow rate, and turbocharger rotational speed over a load sweep. Then, the uHC model is validated against the engine-out measurements. The averaged uHC predictions highlight an average error of 7% and 10 % for W31 and W46 engines, respectively. The uHC model reliability is evidenced by the lack of need for a case-dependent adjustment of its tuning constants, also in presence of relevant variations of both engine load and ring pack design