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This study focuses on evaluation of various fuels within a conventional gasoline internal combustion engine (ICE) vehicle and the implementation of advanced emissions reduction technology. It shows the robustness of the implemented technology packages for achieving ultra-low tailpipe emissions to different market fuels and demonstrates the potential of future GHG neutral powertrains enabled by drop-in lower carbon fuels (LCF). An ultra-low emission (ULE) sedan vehicle was set up using state-of-the-art engine technology, with advanced vehicle control and exhaust gas aftertreatment system including a prototype rapid catalyst heating (RCH) unit. Currently regulated criteria pollutant emission species were measured at both engine-out and tailpipe locations. Vehicle was run on three different drive cycles at the chassis dynamometer: two standard cycles (WLTC and TfL) at 20°C, and a real driving emission (RDE) cycle at -7°C.

The 2023 FISITA White Paper (for which the author was a contributor) on managing in-service emissions and transportation options, to reduce CO2 (CO2-e or carbon footprint) from the existing vehicle fleet, proposed 6 levers which could be activated to complement the rapid transition to vehicles using only renewable energy sources. Another management opportunity reported here is optimizing the vehicle’s life in-service to minimize the life-cycle CO2 impact of a range of present and upcoming vehicles. This study of the US vehicle fleet has quite different travel and composition characteristics to European (EU27) vehicles. In addition, the embodied CO2 is based on ANL’s GREET data rather than EU27 SimaPro methodology. It is demonstrated that in-service, whole-of-life mileage has a significant influence on the optimum life cycle CO2 for BEVs and H2 fuelled FCEVs, as well as ICEs and PHEVs.

E-Mobility and low noise IC Engines has pushed product development teams to focus more on sound quality rather than just on reduced noise levels and legislative needs. Furthermore, qualification of products from a sound quality perspective from an end of line testing requirement is also a major challenge. End of line (EOL) NVH testing is key evaluation criteria for product quality with respect to NVH and warranty. Currently for subsystem or component level evaluation, subjective assessment of the components is done by a person to segregate OK and NOK components. As human factor is included, the process becomes very subjective and time consuming. Components with different acceptance criteria will be present and it’s difficult to point out the root cause for NOK components. In this paper, implementation of machine learning is done for acoustic source detection at end of line testing.

Particulate matter emissions from internal combustion engines have become an increasingly important area of focus for development teams in recent years. This is due to greater regulatory scrutiny on vehicles globally, and especially on particulate emissions. The chemical composition and bulk physical properties of the fuel have been shown to influence the particulate number emissions characteristics. Although some predictive models have been proposed, the causality of specific properties or constituents has not been demonstrated due to the co-linearity of the variables considered in previous studies. In this work, fuels were formulated to capture the expected variation in three key properties of United States (US) market gasoline fuels. Specifically, total aromatics, volatility, and particulate matter index (PMI) were varied across market extremes within regulatory limits--while holding other properties constant.

High-pressure gasoline injection can improve combustion efficiency and lower engine-out emissions; however, the spray characteristics of high-pressure gasoline (>500 bar) are not well known. Effects of different injector nozzle geometry on high-pressure gasoline sprays were studied using a constant volume chamber. Five nozzles with controlled internal flow features including differences in nozzle inlet rounding, conicity, and outlet diameter were investigated. Reference grade gasoline was injected at fuel pressures of 300, 600, 900, 1200, and 1500 bar. The chamber pressure was varied using nitrogen at ambient temperature and pressures of 1, 5, 10, and 20 bar. Spray development was recorded using diffuse backlit shadowgraph imaging methods.

This paper presents an experimental investigation of the impact of EGR dilution on the tradeoff between flame and end-gas autoignition heat release in a Spark-Assisted Compression Ignition (SACI) combustion engine. The mixture was maintained stoichiometric and fuel-to-charge equivalence ratio (ϕ′) was controlled by varying the EGR dilution level at constant engine speed. Under all conditions investigated, end-gas autoignition timing was maintained constant by modulating the mixture temperature and spark timing. Experiments at constant intake pressure and constant spark timing showed that as ϕ′ is increased, lower mixture temperatures are required to match end-gas autoignition timing. Higher ϕ′ mixtures exhibited faster initial flame burn rates, which were attributed to the higher laminar flame speeds immediately after spark timing and their effect on the overall turbulent burning velocity.

Automated driving systems (ADSs) for road vehicles are being developed that can perform the entire dynamic driving task without a human driver in the loop. However, current regulatory frameworks for assuring vehicle safety may restrict the deployment of ADSs that can use machine learning to modify their functionality while in service. A review was undertaken to identify and assess key initiatives and research relevant to the safety assurance of adaptive safety-critical systems that use machine learning, and to highlight assurance concepts that could benefit from further research. The primary objective was to produce findings and recommendations that can inform policy and regulatory reform relating to ADS safety assurance.

Compressed natural gas (CNG) is an attractive, alternative fuel for spark-ignited (SI), internal combustion (IC) engines due to its high octane rating, and low energy-specific CO2 emissions compared with gasoline. Directly-injected (DI) CNG in SI engines has the potential to dramatically decrease vehicles’ carbon emissions; however, optimization of DI CNG fueling systems requires a thorough understanding of the behavior of CNG jets in an engine environment. This paper therefore presents an experimental and modeling study of DI gaseous jets, using methane as a surrogate for CNG. Experiments are conducted in a non-reacting, constant volume chamber (CVC) using prototype injector hardware at conditions relevant to modern DI engines. The schlieren imaging technique is employed to investigate how the extent of methane jets is impacted by changing thermodynamic conditions in the fuel rail and chamber.

Non-reacting spray behaviors of the Engine Combustion Network “Spray G” gasoline fuel injector were investigated at flash and non-flash boiling conditions in an optically accessible single cylinder engine and a constant volume spray chamber. High-speed Mie-scattering imaging was used to determine transient liquid-phase spray penetration distances and observe general spray behaviors. The standardized “G2” and “G3” test conditions recommended by the Engine Combustion Network were matched in this work and the fuel was pure iso-octane. Results from the constant volume chamber represented the zero (stationary piston) engine speed condition and single cylinder engine speeds ranged from 300 to 2,000 RPM. As expected, the present results indicated the general spray behaviors differed significantly between the spray chamber and engine. The differences must be thoughtfully considered when applying spray chamber results to guide spray model development for engine applications.

Gasoline Direct Injection (GDI) has become the preferred technology for spark-ignition engines resulting in greater specific power output and lower fuel consumption, and consequently reduction in CO2 emission. However, GDI engines face a substantial challenge in meeting new and future emission limits, especially the stringent particle number (PN) emissions recently introduced in Europe and China. Studies have shown that the fuel used by a vehicle has a significant impact on engine out emissions. In this study, nine fuels with varying chemical composition and physical properties were tested on a modern turbo-charged side-mounted GDI engine with design changes to reduce particulate emissions. The fuels tested included four fuels meeting US certification requirements; two fuels meeting European certification requirements; and one fuel meeting China 6 certification requirements being proposed at the time of this work.

High-pressure gasoline fuel injection is a means to improve combustion efficiency and lower engine-out emissions. The objective of this study was to quantify the effects of fuel injection pressure on transient gasoline fuel spray development for a wide range of injection pressures, including over 1000 bar, using a constant volume chamber and high-speed imaging. Reference grade gasoline was injected at fuel pressures of 300, 600, 900, 1200, and 1500 bar into the chamber, which was pressurized with nitrogen at 1, 5, 10, and 20 bar at room temperature (298 K). Bulk spray imaging data were used to quantify spray tip penetration distance, rate of spray tip penetration and spray cone angle. Near-nozzle data were used to evaluate the early spray development.

Today, 99% of the two wheelers in India operate with carburetor based fuel delivery system. But with implementation of Bharath Stage VI emission norms, compliance to emission limits along with monitoring of components in the system that contributes towards tail pipe emissions would be challenging. With the introduction of the OBD II (On-Board Diagnostics) and emission durability, mass migration to electronically controlled fuel delivery system is very much expected. The new emission norms also call for precise metering of the injected fuel and therefore demands extended calibration effort. The calibration of engine management system starts with the generation of pre-calibration dataset capable of operating the engine at all operating points followed by base calibration of the main parameters such as air charge estimation, fuel injection quantity, injection timing and ignition angles relative to the piston position.

Combustion in modern spark-ignition (SI) engines is increasingly knock-limited with the wide adoption of downsizing and turbocharging technologies. Fuel autoignition conditions are different in these engines compared to the standard Research Octane Number (RON) and Motor Octane Numbers (MON) tests. The Octane Index, OI = RON - K(RON-MON), has been proposed as a means to characterize the actual fuel anti-knock performance in modern engines. The K-factor, by definition equal to 0 and 1 for the RON and MON tests respectively, is intended to characterize the deviation of modern engine operation from these standard octane tests. Accurate knowledge of K is of central importance to the OI model; however, a single method for determining K has not been well accepted in the literature.

The focus of internal combustion (IC) engine research is the improvement of fuel economy and the reduction of the tailpipe emissions of CO2 and other regulated pollutants. Promising solutions to this challenge include the use of both direct-injection (DI) and alternative fuels such as liquefied petroleum gas (LPG). This study uses Mie-scattering and schlieren imaging to resolve the liquid and vapor phases of propane and iso-octane, which serve as surrogates for LPG and gasoline respectively. These fuels are imaged in a constant volume chamber at conditions that are relevant to both naturally aspirated and boosted, gasoline direct injection (GDI) engines. It is observed that propane and iso-octane have different spray behaviors across these conditions. Iso-octane is subject to conventional spray breakup and evaporation in nearly all cases, while propane is heavily flash-boiling throughout the GDI operating map.

Low-pressure cooled EGR (LP-cEGR) systems can provide significant improvements in spark-ignition engine efficiency and knock resistance. However, open-loop control of these systems is challenging due to low pressure differentials and the presence of pulsating flow at the EGR valve. This research describes a control structure for Low-pressure cooled EGR systems using closed loop feedback control along with internal model control. A Smith Predictor based PID controller is utilized in combination with an intake oxygen sensor for feedback control of EGR fraction. Gas transport delays are considered as dead-time delays and a Smith Predictor is one of the conventional methods to address stability concerns of such systems. However, this approach requires a plant model of the air-path from the EGR valve to the sensor.

Low pressure (LP) and cooled EGR systems are capable of increasing fuel efficiency of turbocharged gasoline engines, however they introduce control challenges. Accurate exhaust pressure modeling is of particular importance for real-time feedforward control of these EGR systems since they operate under low pressure differentials. To provide a solution that does not depend on physical sensors in the exhaust and also does not require extensive calibration, a coupled temperature and pressure physics-based model is proposed. The exhaust pipe is split into two different lumped sections based on flow conditions in order to calculate turbine-outlet pressure, which is the driving force for LP-EGR. The temperature model uses the turbine-outlet temperature as an input, which is known through existing engine control models, to determine heat transfer losses through the exhaust.

This paper presents a combined experimental and numerical method for analysing energy flows within a spark ignition engine. Engine dynamometer data is combined with physical models of in-cylinder convection and the engine's thermal impedances, allowing closure of the First Law of Thermodynamics over the entire engine system. In contrast to almost all previous works, the coolant and metal temperatures are not assumed constant, but rather are outputs from this approach. This method is therefore expected to be most useful for lean burn engines, whose temperatures should depart most from normal experience. As an example of this method, the effects of normalised air-fuel ratio (λ), compression ratio and combustion chamber geometry are examined using a hydrogen-fueled engine operating from λ = 1.5 to λ = 6. This shows large variations in the in-cylinder wall temperatures and heat transfer with respect to λ.

The use of Low Pressure - Exhaust Gas Recirculation (EGR) is intended to allow displacement reduction in turbocharged gasoline engines and improve fuel economy. Low Pressure EGR designs have an advantage over High Pressure configurations since they interfere less with turbocharger efficiency and improve the uniformity of air-EGR mixing in the engine. In this research, Low Pressure (LP) cooled EGR is evaluated on a turbocharged direct injection gasoline engine with variable valve timing using both simulation and experimental results. First, a model-based calibration study is conducted using simulation tools to identify fuel efficiency gains of LP EGR over the base calibration. The main sources of the efficiency improvement are then quantified individually, focusing on part-load de-throttling of the engine, heat loss reduction, knock mitigation as well as decreased high-load fuel enrichment through exhaust temperature reduction.

This paper presents an overview of the evolution & revolution of automotive E/E architectures and how we at Bosch, envision the technology in the future. It provides information on the bottlenecks for current E/E architectures and drivers for their evolution. Functionalities such as automated driving, connectivity and cyber-security have gained increasing importance over the past few years. The importance of these functionalities will continue to grow as these cutting-edge technologies mature and market acceptance increases. Implementation of these functionalities in mainstream vehicles will demand a paradigm shift in E/E architectures with respect to in-vehicle communication networks, power networks, connectivity, safety and security. This paper expounds on these points at a system level.

This paper presents a numerical study of trace knocking combustion of ethanol/gasoline blends in a modern, single cylinder SI engine. Results are compared to experimental data from a prior, published work [1]. The engine is modeled using GT-Power and a two-zone combustion model containing detailed kinetic models. The two zone model uses a gasoline surrogate model [2] combined with a sub-model for nitric oxide (NO) [3] to simulate end-gas autoignition. Upstream, pre-vaporized fuel injection (UFI) and direct injection (DI) are modeled and compared to characterize ethanol's low autoignition reactivity and high charge cooling effects. Three ethanol/gasoline blends are studied: E0, E20, and E50. The modeled and experimental results demonstrate some systematic differences in the spark timing for trace knock across all three fuels, but the relative trends with engine load and ethanol content are consistent. Possible reasons causing the differences are discussed.