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Fuels are formulated by a variety of different components characterized by chemical and physical properties spanning a wide range of values. Changing the ratio between the mixture component molar fractions, it is possible to fulfill different requirements. One of the main properties that can be strongly affected by mixture composition is the volatility that represents the fuel tendency to vaporize. For example, changing the mixture ratio between alcohols and hydrocarbons, it is possible to vary the mixture saturation pressure, therefore the fuel vaporization ratio during the injection process. This paper presents a 1D numerical model to simulate the superheated injection process of a gasoline-ethanol mixture through real nozzle geometries. In order to test the influence of the mixture properties on flash atomization and flash evaporation, the simulation is repeated for different mixtures characterized by different gasoline-ethanol ratio.

Standard compressor and turbine maps obtained from steady-state test bench measurements are not sufficient for assessing transient turbocharger behavior. This also makes them inappropriate for gauging combustion-engine response and fuel consumption. Nor do they allow for the widely differing operating conditions which, apart from aerodynamics, have a major influence on heat transfer and turbocharger efficiency. This paper looks at a more complex approach of modeling the turbocharger as well developing appropriate measurement methods (“advanced turbocharger model”). This includes non-destructive measurements under various heat transfer conditions to define the turbocharger's adiabatic behavior needed to describe charge-air pressure increase in the compressor and engine exhaust gas backpressure from the turbine for transient engine operation.

Increasing emissions regulations, diagnostics capability, and other demands in vehicle refinement, have led to the need for increasingly complex engine control systems. These demands have led to in-cylinder combustion control, especially for the diesel engine. Diesel engine combustion relies heavily on the auto-ignition process. Therefore accurate control of this process is important and will become even more important for HCCI-engines. This paper discusses the configuration of a diesel engine for in-cylinder combustion control. It describes the digital evaluation of the cylinder pressure signal and the computation of the physical parameters necessary for proper combustion analysis, along with methods for using the calculated combustion parameter for engine control. The paper demonstrates the advantages of electronic engine control combined with in-cylinder pressure information. The paper also addresses some of the future challenges of engine control.

Compression-ignited engines are still considered the most efficient and reliable technology for automotive applications. However, current and future emission regulations, which severely limit the production of NOx, particulate matter and CO2, hinder the use of diesel-like fuels. As a matter of fact, the spontaneous ignition of directly-injected Diesel leads to a combustion process that is heterogeneous by nature, therefore characterized by the simultaneous production of particulate matter and NOx. In this scenario, several innovative combustion techniques have been investigated over the past years, the goal being to benefit from the high thermal efficiency of compression-ignited engines, which results primarily from high Compression Ratio and lean and unthrottled operation, while simultaneously mitigating the amount of pollutant emissions.

Measurement of particle number was introduced in the Euro 5/6 light duty vehicle emissions regulation. Due to the complex nature of combustion exhaust particles, and to transportation, transformation and deposition mechanisms, such type of measurement is particularly complex, and regression analysis is commonly used for the comparison of different measurement systems. This paper compares various commercial instruments, developing a correlation analysis focused on PN (Particle Number) measurement, and isolating the factors that mainly influence each measuring method. In particular, the experimental activity has been conducted to allow critical comparisons between measurement techniques that are imposed by current regulations and instruments that can be used also on the test cell. The paper presents the main results obtained by analyzing instruments based on different physical principles, and the effects of different sampling locations and different operating parameters.

Still today, two-stroke engine layout is characterized by a wide share on the market thanks to its simpler construction that allows to reduce production and maintenance costs respecting the four-stroke engine. Two of the main application areas for the two-stroke engines are on small motorbikes and on handheld machines like chainsaws, brush cutters, and blowers. In both these application areas, two-stroke engines are generally equipped by a carburettor to provide the air/fuel mixture formation while the engine cooling is assured by forcing an air stream all around the engine head and cylinder surfaces. Focusing the attention on the two-stroke air-cooling system, it is not easy to assure its effectiveness all around the cylinder surface because the air flow easily separates from the cylinder walls producing local hot-spots on the cylinder itself. This problem can be bounded only by the optimization of the cylinder fin design placed externally to the cylinder surface.

The current legislation for industrial applications and construction equipment including earthmoving machines and crane engines allows different strategies to fulfill the corresponding exhaust emission limits. Liebherr Machines Bulle SA developed their engines to accomplish these limits using SCRonly technology. IAV supported this development, carrying out engine as well as SCR aftertreatment system and vehicle calibration work including the OBD and NOx Control System (NCS) calibration, as well as executing the homologation procedures at the IAV development center. The engines are used in various Liebherr applications certified for EU Stage IIIb, EPA TIER 4i, China GB4 and IMO MARPOL Tier II according to the regulations “97/68/EC”, “40 CFR Part 1039”, “GB17691-2005” and “40 CFR Parts 9, 85, et al.” using the same SCR hardware for all engine power variants of the corresponding I6 and V8 engine families.

This paper presents an optimization algorithm, based on discrete dynamic programming, that aims to find the optimal control inputs both for energy and thermal management control strategies of a Plug-in Hybrid Electric Vehicle, in order to minimize the energy consumption over a given driving mission. The chosen vehicle has a complex P1-P4 architecture, with two electrical machines on the front axle and an additional one directly coupled with the engine, on the rear axle. In the first section, the algorithm structure is presented, including the cost-function definition, the disturbances, the state variables and the control variables chosen for the optimal control problem formulation. The second section reports the simplified quasi-static analytical model of the powertrain, which has been used for backward optimization. For this purpose, only the vehicle longitudinal dynamics have been considered.

The powertrain electrification is currently not only taking place in public road mobility vehicles, but is also making its way to the racetrack, where it’s driving innovation for developments that will later be used in series production vehicles. The current development focus for electric vehicles is the balance between driving power, range and weight, which is given even greater weighting in racing. To redefine the current limits, IAV developed a complete e-powertrain for a racing MX motorcycle and integrated it into a real drivable demonstrator bike. The unique selling point is the innovative direct phase-change cooling (PCC) of the three-phase e-motor and its power electronics, which enables significantly increased continuous power (Pe = 40 kW from 7,000 rpm to 9,000 rpm) without thermal power reduction. The drive unit is powered by a replaceable Lithium-Ion round cell battery (Ubat,max = 370V) with an energy storage capacity of Ebat = 5 kWh.

Deployment of autonomous vehicles requires an extensive evaluation of developed control, perception, and localization algorithms. Therefore, increasing the implemented SAE level of autonomy in road vehicles requires extensive simulations and verifications in a realistic simulation environment before proving ground and public road testing. The level of detail in the simulation environment helps ensure the safety of a real-world implementation and reduces algorithm development cost by allowing developers to complete most of the validation in the simulation environment. Considering sensors like camera, LiDAR, radar, and V2X used in autonomous vehicles, it is essential to create a simulation environment that can provide these sensor simulations as realistically as possible.

Despite a large body of analytical work characterizing the dynamic motion of planetary gears, supporting experimental data is limited. Experimental results are needed to support computer modeling and offer practical optimization guidelines to gear designers. This paper presents the design and implementation of a test facility and precision test fixtures for accurate measurement of planetary gear vibration at operating conditions. Acceleration measurements are made on all planetary bodies under controlled torque/speed conditions. Custom, high-precision test fixtures accommodate instrumentation, ensure accurate alignment, help isolate gear dynamics, and allow for variability in future testing. Results are compared with finite element and lumped parameter models.

The future emission standards, including real driving emissions (RDE) measurements are big challenges for engine and after-treatment development. Also for development of a robust control system, in real driving emissions cycles under varied operating conditions and climate conditions, like low ambient temperature as well as high altitude are advanced physical-based algorithms beneficial in order to realize more precise, robust and efficient control concepts. A fast-running novel physical-based ignition delay model for diesel engine combustion simulation and additionally, for combustion control in the next generation of ECUs is presented and validated in this study. Detailed chemical reactions of the ignition processes are solved by a n-heptane mechanism which is coupled to the thermodynamic simulation of in-cylinder processes during the compression and autoignition phases.

The Selective Catalytic Reduction (SCR) system installed on the exhaust line is currently widely used on Diesel heavy-duty trucks and it is considered a promising technique for light and medium duty trucks, large passenger cars and off-highway vehicles, to fulfill future emission legislation. Some vehicles of these last categories, equipped with SCR, have been already put on the market, not only in the US, where the emission legislation on Diesel vehicles is more restrictive, but also in Europe, demonstrating to be already compliant with the upcoming Euro 6. Moreover, new and more stringent emission regulations and homologation cycles are being proposed all over the world, with a consequent rapidly increasing interest for this technology. As a matter of fact, a physical model of the Diesel Exhaust Fluid (DEF) supply system is very useful, not only during the product development phase, but also for the implementation of the on-board real-time controller.

Electronic throttle control is increasingly being considered as a viable alternative to conventional air management systems in modern spark-ignition engines. In such a scheme, driver throttle commands are interpreted by the powertrain control module together with many other inputs; rather than directly commanding throttle position, the driver is now simply requesting torque - a request that needs to be appropriately interpreted by the control module. Engine management under these conditions will require optimal control of the engine torque required by the various vehicle subsystems, ranging from HVAC, to electrical and hydraulic accessories, to the vehicle itself. In this context, the real-time estimation of engine and load torque can play a very important role, especially if this estimation can be performed using the same signals already available to the powertrain control module.

With the enhancements in vehicle electrification and autonomous vehicles, Traffic systems are also being improved at an accelerated rate to aid the development of improving fuel economy standards. For this to be possible, it is essential that traffic can be accurately modeled and predicted. The existing toolsets are proprietary and expensive and traffic modeling is not a trivial task due to its dependence on various factors such as place, time, and weather. To address these issues, an entirely open-source Software-In-Loop (SIL) fleet-focused traffic modeling toolset has been developed with the ability to take environmental factors with powertrain-in-the-loop into account leveraging Simulation of Urban Mobility (SUMO) and python. The proposed SIL toolset encompasses the creation of a microscopic traffic distribution which accounts for the usual traffic trends of a typical day.

One challenge for the development of commercial vehicles is the reduction of CO2 greenhouse, where hydrogen can help to reduce the fleet CO2. For instance, in Europe a drop in fleet consumption of 15% and 30% is set as target by the regulation until 2025 and 2030. Another challenge is EURO VII in EU or even already approved CARB HD Low NOx Regulation in USA, not only for Diesel but also for hydrogen combustion engines. In this study, first the requirements for the combustion and after-treatment system of a hydrogen engine are defined based on future emission regulations. The major advantages regarded to hydrogen combustion are due to the wide range of flammability and very high flame speed numbers compared to other fossil based fuels. Thus, it can be well used for lean burn combustion with much better fuel efficiency and very low NOx emissions with an ultra lean combustion. A comprehensive experimental investigation is performed on a HD 2 L single-cylinder engine.

The EcoCAR 2: Plugging into the Future team at the Ohio State University is designing a Parallel-Series Plug-in Hybrid Electric Vehicle capable of 50 miles of all-electric range. The vehicle features a 18.9-kWh lithium-ion battery pack with range extending operation in both series and parallel modes. This is made possible by a 1.8-L ethanol (E85) engine and 6-speed automated manual transmission. This vehicle is designed to drastically reduce fuel consumption, with a utility factor weighted fuel economy of 51 miles per gallon gasoline equivalent (mpgge), while meeting Tier II Bin 5 emissions standards. This report details the fabrication and control implementation process followed by the Ohio State team during Year 2 of the competition. The fabrication process includes finalizing designs based on identified requirements, building and assembling components, and performing extensive validation testing on the mechanical, electrical and control systems.

Future heavy-duty (HD) concepts should fulfill very tight tail-pipe NOx emissions and simultaneously fulfill the fuel efficiency targets. In current HD Euro VII discussions, real working cycles become key to ensure emission conformity. For instance, cold start and cold ambient conditions during testing with low load profiles starting from 0% payload, require external heating measures. Knowing the trade-off between fuel consumption and tail-pipe NOx emissions a holistic engine and EAT system optimization with innovative thermal management is required. Towards a carbon neutral mobility, Hydrogen combustion engines are one of the key solutions. Advanced combustion system development enables maximal usage of lean burning as the major advantage of the Hydrogen fuel for efficiency improvement and NOx reduction.

Further tightening of NOx emission standards as well as CO2 emission limits for commercial vehicles are currently under discussion. In the on-road market, lowering NOx emissions up to 90%, down to 0.02 g/bhp-hr, has been proposed by CARB and is evaluated by US EPA. Testing for in-service conformity using a portable emission measurement system (PEMS) is currently under review in the US. In Europe, CO2 emission limits are anticipated and a CO2 monitoring program is ongoing. PEMS legislation has been recently tightened and further restrictions can be expected. Stage V legislation has been introduced in Europe and it is foreseeable that further tightening of off-road standards will take place in the future. This study deals with virtual development and evaluation of future engine and exhaust aftertreatment (EAT) technology solutions to fulfill the diverse future emission requirements with emphasis on off-road applications.

The latest legislative tendencies for on-highway heavy duty vehicles in the United States such as the feasibility assessment of low NOX standards of CARB or EPA’s memorandum forecast further tightening of the NOX emissions limits. In addition, the GHG Phase 2 legislation and also phased-in regulations in the EU enforce a continuous reduction in CO2 emissions resp. fuel consumption. In order to meet such low NOX emission limits, a rapid heat-up of the exhaust after-treatment system (EATS) is inevitable. However, the required thermal management results in increased fuel consumption, i.e. CO2 emissions as shown in numerous previous works also by the authors. A NOX-CO2 trade-off for cumulative cycle emissions can be observed, which can be optimized by using more advance technologies on the engine and/or on the EATS side.