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The paper presents a robust adaptive control technique for precise regulation of a port fuel injection + direct injection (PFI+DI) system, a dual fuel injection configuration adopted in modern gasoline engines to boost performance, fuel efficiency, and emission reduction. Addressing parametric uncertainties on the actuators, inherent in complex fuel injection systems, the proposed approach utilizes an indirect model reference adaptive control scheme. To accommodate the increased control complexity in PFI+DI and the presence of additional uncertainties, a nonlinear plant model is employed, incorporating dynamics of the exhaust burned gas fraction. The primary objective is to optimize engine performance while minimizing fuel consumption and emissions in the presence of uncertainties. Stability and tracking performance of the adaptive controller are evaluated to ensure safe and reliable system operation under various conditions.

When an SI engine is equipped with individual cylinder pressure transducers, combustion timing of each cylinder can be precisely controlled by adjusting spark timing in real-time. In this paper, a novel method based on principal component analysis (PCA) is introduced to control the combustion timing with a significantly less computational burden than a conventional method.

Crankshaft bearings function to maintain the lubrication oil films needed to support crankshaft journals in hydrodynamic regime of rotation. Discontinuous oil films will cause the journal-bearing couple to be in a mixed or boundary lubrication condition, or even a bearing seizure or a spun bearing. This condition may further force the crankshaft to break and an engine shutdown. Spun bearings have been identified to be one of the top reasons in field returned engines. Excessive investigations have found large, embedded hard debris particles on the bearings are inevitably the culprit of destroying continuity of the oil films. Those particles, in particular the suspicious steel residues, in the sizes of hundreds of micrometers, are large enough to cause oil film to break, but rather fine and challenging for materials engineers to characterize their metallurgical features. This article presents the methodology and steps of debris analyses on bearings at different stages of engine build.

DC fast charging (DCFC) also referred to as L3 charging, is the fastest charging technology to replenish the drivable range of an electric vehicle. DCFC provides the convenience of faster charging time compared to L1 and L2 at the expense of potentially increased battery health degradation. It is known to accelerate battery capacity fade leading to reduced range and lifetime of the EV battery. While there are active efforts and several means to reduce the downsides of DCFC at cell chemistry level, this trade-off is still an important consideration for most battery cells in automotive propulsion applications. Since DCFC is a customer driven technology, informing drivers of the trade-off of each DCFC event can potentially result in better outcomes for the EV battery life. Traditionally, the driver is advised to limit DCFC events without providing quantifiable metrics to inform their decisions during EV charging.

The world is moving towards E-mobility solutions and Battery Electric Vehicles (BEVs) are the main enabler towards it. Li-ion cells are the fundamental building block of any BEVs. There are three common types of Li-ion cell design i.e., cylindrical cells, Prismatic Cells and Pouch cells. Ensuring safety of BEVs are critical to gain customer trust and acceptance over Internal Combustion Engine (ICE) vehicles. EV fire is found to be one of the major concerns related to using higher energy batteries. During a crash event, Post-Crash Electrical Integrity of the BEV is to be ensured and hence primary focus is on mitigation of Li-ion cell internal short circuit. It has been seen in prior published articles that cell internal short circuit can be triggered by physical intrusion of cell. This paper primarily focusses on simulating the mechanical behavior of cylindrical cell under various crush conditions.

Cast aluminum cylinder blocks are frequently used in gasoline and diesel internal combustion engines because of their light-weight advantage. However, the disadvantage of aluminum alloys is their relatively low strength and fatigue resistance which make aluminum blocks prone to fatigue cracking. Engine blocks must withstand a combination of low-cycle fatigue (LCF) thermal loads and high-cycle fatigue (HCF) combustion and dynamic loads. Reliable computational methods are needed that allow for accurate fatigue assessment of cylinder blocks under this combined loading. In several publications, the mechanism-based thermomechanical fatigue (TMF) damage model DTMF describing the growth of short fatigue cracks has been extended to include the effect of both LCF thermal loads and superimposed HCF loadings. This approach is applied to the finite life fatigue assessment of an aluminum cylinder block. The required material properties related to LCF are determined from uniaxial LCF tests.

Turbocharger housings in internal combustion engines are subjected to severe mechanical and thermal cyclic loads throughout their life-time or during engine testing. The combination of thermal transients and mechanical load cycling results in a complex evolution of damage, leading to thermo-mechanical fatigue (TMF) of the material. For the computational TMF life assessment of high temperature components, the DTMF model can provide reliable TMF life predictions. The model is based on a short fatigue crack growth law and uses local finite-element (FE) results to predict the number of cycles to failure for a technical crack. In engine applications, it is nowadays often acceptable to have short cracks as long as they do not propagate and cause loss of function of the component. Thus, it is necessary to predict not only potential crack locations and the corresponding number of cycles for a technical crack, but also to determine subsequent crack growth or even a possible crack arrest.

The power loss of bearings is a significant factor in the overall efficiency in a drive unit system. Such bearings are subject to combined radial and axial loading needed to support the gear mesh forces. An experimental methodology has been developed to perform sets of power loss measurements on TRB, 4PCBB and DGBB. These measurements were performed under a variety of speed, load, temperature, and lubrication conditions. The loss behaviors of these types of the bearings are discussed, along with the tradeoff of different bearing arrangements for the fuel economy cycles. Several power loss models are employed to assess the accuracy of the estimations as compared to the experimental measurements. At low speed some models showed good correlations for TRB and DGBB, while at higher speed, they start deviating from the testing results. A higher fidelity model for estimating the losses at high speed, especially speed around 20krpm and beyond, needs to be developed.

Stochastic Preignition (SPI) is an abnormal combustion phenomenon for internal combustion engines (ICE), which has been a significant impact to automotive companies developing high efficiency, turbocharged, direct fuel injection, spark ignited engines. It is becoming clearer what fuel properties are related to the cause of SPI, whether directly with fuel preparation in the cylinder, or mechanisms related to the deposit build-up which contributes to initial and follow-on SPI events. The purpose of this paper is to provide a summary of global market gasoline fuel properties with special attention given to properties and specific compounds from the fuel and fuel additives that can contribute to SPI and the deposit build-up in engines. Based on a review of the global fuel quality, it appears that the fuel quality has not caught up to meet the technology requirements for fuel economy from modern technology engines.

Thermal cabin comfort is the largest consumer of battery energy second only to propulsion in Battery Electric Vehicles (BEV’s). Accurate prediction of thermal comfort in the vehicle cabin with fast turnaround times will allow engineers to study the impact of various thermal comfort technologies and develop energy efficient Heating, Ventilation and Air Conditioning (HVAC) systems. In this study a novel data-driven model based on physics-guided Sparse Identification of Nonlinear Dynamics (SINDy) method was developed to predict Equivalent Homogeneous Temperature (EHT), Mean Radiant Temperature (MRT) and cabin air temperature under transient conditions and drive cycles. EHT is a recognized measure of the total heat loss from the human body that can be used to characterize highly non-uniform thermal environments such as a vehicle cabin. The SINDy model was trained on drive cycle data from Climatic Wind Tunnel (CWT) for a representative Battery Electric Vehicle.

Turbochargers are widely employed in internal combustion engines, in both, diesel and gasoline vehicle, to boost the power without any extra fuel usage. Turbocharger comes in different sizes based upon the boost pressure to increase. Capacity of turbocharger are available in great range in the market which are designed to match the requirement. From structural point of view, key component of an automotive turbocharger is rotor. This rotor consists of compressor wheel, turbine wheel, shaft and bearing (journal/ball) mainly. In industries, design & development of turbocharger rotor for its dynamic characteristics is done using virtual engineering technique (Computer Aided Engineering). Multibody dynamic (MBD) analysis simulation is one of the best approaches which is used to study the rotor in great details. In this current MBD procedure fluid-structure interaction problem is solved by modelling oil film in the journal bearing and solving it using “Reynolds equation”.

A computational study based on unsteady Reynolds-Averaged-Navier-Stokes that resolves the gas-liquid interface was performed to examine the unsteady multiphase flow in a 4 cylinder Inline (i-4) engine. In this study, the rotating motion of the crankshaft and reciprocating motion of the pistons were accounted for to accurately predict the oil distribution in various parts of the engine. Three rotational speeds of the crankshaft have been examined: 1000, 2800, and 4000 rpm. Of particular interest is to examine the mechanisms governing the process of oil drawdown from the engine head into the case. The oil distributions in other parts of the engine have also been investigated to understand the overall crankcase breathing process. Results obtained show the drawdown of oil from the head into the case to be strongly dependent on the venting strategy for the foul air going out of the engine through the PCV system.

Stochastic Preignition (SPI) is an abnormal combustion event that occurs in a turbocharged engine and can lead to the loss in fuel economy and engine hardware damage, and in turn result in customer dissatisfaction. It is a significant limiting factor on the use and continued downsizing of turbocharged spark ignited direct injection (SIDI) gasoline engines. Understanding and mitigating all the factors that cause and influence the rate and severity of SPI occurrence are of critical importance to the engine’s continued use and fuel economy improvements for future designs. Previous studies have shown that the heavy molecular weight components of the fuel formulations are one factor that influences the rate of SPI from a turbocharged SIDI gasoline engine. All the previous studies have involved analyzing the fuel’s petroleum hydrocarbon chemistry, but not specifically the additives that are put in the fuel to protect and clean the internal components over the life of the engine.

Cast Al-Si alloys are widely used in automotive industry to produce structural components, such as engine block and cylinder head, because of the increasing demands in reducing mass for improved fuel efficiency. The fatigue performance of the castings is critical in their application. Porosity is highly detrimental to the fatigue behavior of cast Al-Si alloys. Therefore, accurate measurement of pore sizes is important in order to develop the correlations between porosity and fatigue strength. However, quantification of porosity is challenging and shows large variation depending on the measurement methods, particularly for micro-shrinkage porosity due to the torturous and complex morphology. The conventional metallographic image analysis method in the 2D polished surface often underestimates the actual pore size particularly when the porosity morphology is complex.

The battery cell unit and battery module constitute the building blocks for the battery pack in an electric vehicle. It is important to rigorously understand the vibration induced response of the battery pack as it is a prerequisite for the safety of an electric vehicle. An accurate finite element (FE) model plays a key role in predicting the dynamic response of the battery pack simulation. In this paper, finite element analysis (FEA) results are compared with the experimental set up of the battery components and a 60-cell battery module. Using orthotropic elastic constants instead of isotropic properties to model the fiber reinforced polymer (FRP) made battery components produced better modal results correlation. Modal frequency values for the brick components have been improved by 25% to 50%. For the battery module, swapping of mode shape behavior is observed between finite element model and experimental results.

Gasoline Particulate Filters (GPF) are widely employed in exhaust aftertreatment systems of gasoline engines to meet the stringent particulate emissions requirements of Euro 6 and China 6 standard. Optimization of GPF performance requires a delicate trade-off between fuel economy, engine performance and drivability. This results in a complex lengthy and iterative calibration development process which uses a lot of hardware resources. To improve the calibration process and reduce hardware testing, physics-based modeling of the GPF system is used. A 1-D chemical model supplemented with 3D CFD solver is utilized to evaluate pressure drop and soot burning performance characteristics of the GPF under engine dynamometer test conditions. The chemical kinetics of soot burning for the 1D model is developed using test data obtained from well controlled laboratory environment.

An experimental piston compounded engine was designed with guidance from thermodynamic modeling, then was built and tested to compare the model predictions to measured results. The piston-compounded concept has shown great potential for improvements in efficiency over current state-of-the-art light-duty engines through the use of an efficient second expansion process to more fully recover energy still present in the exhaust gasses, and was further developed into the Downsized Boosted Dilute Combustion, Exhaust Compounded (DBDC+EC) engine presented here. This paper documents some of the more unique design elements of this engine as well as a performance comparison between test data and modeling expectations. Ultimately, an experimental stoichiometric spark-ignited piston compounded engine was designed, five blocks were built, and collectively they were run for thousands of hours.

An experimental piston compounded engine was designed with guidance from thermodynamic modeling, then was built and tested to compare the model predictions to measured results. This Downsized Boosted Dilute Combustion, Exhaust Compounded (DBDC+EC) engine concept has shown great potential for improvements in efficiency at high loads through extended second expansion process, but suffered from excessive expander cylinder pumping and low exhaust temperatures at low loads. Four expander operating strategies were experimentally tested and simulated at a range of engine speeds and loads to determine the most efficient method to deactivate the piston compounding at low loads. The most effective method involved deactivating all the expander valves and operating it as an air-spring while diverting power cylinder exhaust gasses through a separate bypass port.

Automotive manufacturers relentlessly explore engine technology combinations to achieve reduced fuel consumption under continued regulatory, societal and economic pressures. For example, technologies enabling advanced combustion modes, increased expansion to effective compression ratio, and reduced parasitics continue to be developed and integrated within conventional and hybrid propulsion strategies across the industry. A high-efficiency gasoline engine capable for use in conventional or hybrid electric vehicle platforms is highly desirable. This paper is the first to two papers describing the development of a combustion system combining lean-stratified combustion with Miller cycle for downsized boosted applications. The work was completed under a multi-year US DOE project. The goal was to define a light-duty engine package capable of achieving a 35% fuel economy improvement at US Tier 3 emission standards over a naturally aspirated stoichiometric baseline vehicle.

Automotive manufacturers relentlessly explore engine technology combinations to achieve reduced fuel consumption under continued regulatory, societal and economic pressures. For example, technologies enabling advanced combustion modes, increased expansion to effective compression ratio and reduced parasitics continue to be developed and integrated within conventional and hybrid propulsion strategies across the industry. A high-efficiency gasoline engine capable for use in conventional or hybrid electric vehicle platforms is highly desirable. This paper is the second of two papers describing the multi-cylinder integration of a technology package combining lean-stratified combustion with Miller cycle for downsized boosted applications. The first paper describes the design, analysis and single-cylinder testing conducted to down-select the combustion system deployed to the multi-cylinder engine.