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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.

A gasoline’s distillation profile is directly related to its hydrocarbon composition and the volatility (boiling points) of those hydrocarbons. Generally, the volatility profiles of U.S. market fuels are characterized using a very simple, low theoretical plate distillation separation, detailed in the ASTM D86 test method. Because of the physical chemistry properties of some compounds in gasoline, this simple still or retort distillation has some limitations: separating azeotropes, isomers, and heavier hydrocarbons. Chemists generally rely on chromatographic separations when more detailed and precise results are needed. High-boiling aromatic compounds are the primary source of particulate emissions from spark ignited (SI), internal combustion engines (ICE), hence a detailed understanding and high-resolution separation of these heavy compounds is needed.

Methanol is currently being evaluated as a promising alternative fuel for internal combustion engines, due to being attainable by carbon neutral or negative pathways (renewable energy and carbon capture technology). The low ignitability of methanol has made it attractive mostly as a fuel for spark ignition engines, however the low sooting properties of the fuel could potentially reduce the NOx-soot tradeoff present in compression ignition engines. In this work, using a 4-cylinder engine with compression ratio modified from 16:1 to 19:1, methanol combustion is evaluated under five operating conditions in terms of fuel consumption, criteria pollutants, CO2 emissions and engine efficiency in addition to the qualitative assessment of the combustion stability. It was found that combustion is stable at medium to high loads, with medium load NOx emissions levels at least 30% lower than the original diesel engine and comparable emissions at maximum load conditions.

Speaker performance in Acoustic Vehicle Alerting System (AVAS) plays a crucial role for pedestrian safety. Sound radiation from AVAS speaker has obvious directivity pattern. Considering this feature is critical for accurately simulating the exterior sound field of electrical vehicles. This paper proposes a new process to characterize the sound directivity pattern of AVAS speaker. The first step of the process is to perform an acoustic testing to measure the sound pressure radiated from the speaker at a certain number of microphone locations in a free field environment. Based on the geometry of a virtual speaker, the locations of each microphone and measured sound pressure data, an inverse method, namely the inverse pellicular analysis, is adopted to recover a set of vibration pattern of the virtual speaker surface. The recovered surface vibration pattern can then be incorporated in the full vehicle numerical model as an excitation for simulating the exterior sound field.

Zinc-based electrogalvanized (EG) and hot-dip galvanized (HDGI) coatings have been widely used in automotive body-in-white components for corrosion protection. The formability of zinc coated sheet steels depends on the properties of the sheet and the interactions at the interface between the sheet and the tooling. The frictional behavior of zinc coated sheet steels is influenced by the interfacial conditions present during the forming operation. Friction behavior has also been found to deviate from test method to test method. In this study, various lubrication conditions were applied to both bending under tension (BUT) test and a draw bead simulator (DBS) test for friction evaluations. Two different zinc coated steels; electrogalvanized (EG) and hot-dip galvanized (HDGI) were included in the study. In addition to the coated steels, a non-coated cold roll steel was also included for comparison purpose.

Accelerating product development cycles and incentives to reduce costs in product development are strong motivators to move to virtual development and validation processes. Challenges to moving to a virtual paradigm include a wealth of historical data and context for hardware tests, uncertainty over dependencies, and a lack of a clear path of transition to virtual methods. In this paper we will discuss approaches to understanding the value created by hardware tests and aligning that value to virtual processes. We will also discuss the need for a virtual context to be added to SAE J1739 [1] (DFMEA detection criteria), and how to create paths to maximize the value of virtual assessments. Finally, we will also discuss the cultural and organizational changes required to support.

The front camera module is a fundamental component of a modern vehicle’s active safety architecture. The module supports many active safety features. Perception of the road environment, requests for driver notification or alert, and requests for vehicle actuation are among the camera software’s key functions. This paper presents a novel method of testing these functions virtually. First, the front camera module software is compiled and packaged in a Docker container capable of running on a standard Linux computer as a software in the loop (SiL). This container is then integrated with the active safety simulation tool that represents the vehicle plant model and allows modeling of test scenarios. Then the following simulation components form a closed loop: First, the active safety simulation tool generates a video data stream (VDS). Using an internet protocol, the tool sends the VDS to the camera SiL and other vehicle channels.

Elastomers are widely used in many automotive components such as seals, gaskets etc., for their hyperelastic properties. They can undergo large strain and can return to their original state with no significant deformation making them suitable for energy dissipation applications. Most common testing procedures include uniaxial tension, pure shear, biaxial tension and volumetric compression under quasi-static loading conditions. The results from these tests are used to generate material models for different finite element (FE) solvers, such as LS-DYNA. Commonly used material models for elastomers in LS-DYNA are the Ogden Material Model (MAT77), which uses parameter-based approach and the Simplified Rubber Material Model (MAT181), which uses tabulated input data. Prediction of rate dependent behavior of elastomers is gaining interest as, for example, during a crash simulation the components undergo impact under different strain rates.

The validation of brake discs has remained, to this day, heavily reliant on “Thermal Abuse” or “Thermal Cracking” type testing, with many procedures so dated that most engineers active in the industry today cannot even recall the origin of the test. These procedures - of which there are many variants - all share the trait of greatly accelerating durability testing by performing repeated high power (high speed and high deceleration) brake applies to drive huge temperature gradients and internal stress, and often allowing the disc to get very hot, to where the strength of the material from which the disc is constructed is significantly degraded. There is little debate about whether these procedures work; by and large disc durability issues in the field are extremely rare.

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.

The continuous improvement of internal combustion engines (ICEs) with strategies that can be applied to existing vehicle platforms, either directly or with minor modifications, can improve efficiency and reduce GHG emissions to help achieve Paris climate targets. Low carbon fuels (LCF) as diesel substitutes for light and heavy-duty vehicles are currently being considered as a promising alternative to reduce well-to-wheel (WTW) CO2 emissions by taking advantage of the carbon offset their synthesis pathway can promote, which could capture more CO2 than it releases into the atmosphere. Additionally, some low carbon fuels, like OMEx blends, have non-sooting properties that can significantly improve the NOx-soot tradeoff. The current work studies the calibration optimization of a EU6D-TEMP light-duty engine using various LCFs with different renewable contents with the goal of reduced NOx emissions.

The automotive industry has increased reliance on electronics technology and wireless communication systems and the demand for these systems is still increasing. With this demand there is a need to ensure these systems do not interfere with each other in a way which may cause system performance degradation or even failure. Electromagnetic compatibility (EMC) is a discipline that deals with interaction between electronic and wireless systems. During EMC testing the device under test (DUT) is isolated from the surrounding environment to facilitate measurement of the component’s electromagnetic characteristics. Geometric aspects of an EMC test setup may impact test results without the knowledge of the test engineer. In this paper, electromagnetic simulation and measurement results will show the impact of one of the least obvious but most often experienced issues in an EMC setup - grounding.

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.

Automated driving systems (ADS) are one of the key modern technologies that are changing the way we perceive mobility and transportation. In addition to providing significant access to mobility, they can also be useful in decreasing the number of road accidents. For these benefits to be realized, candidate ADS need to be proven as safe, robust, and reliable; both by design and in the performance of navigating their operational design domain (ODD). This paper proposes a multi-pronged approach to evaluate the safety performance of a hypothetical candidate system. Safety performance is assessed through using a set of test cases/scenarios that provide substantial coverage of those potentially encountered in an ODD. This systematic process is used to create a library of scenarios, specific to a defined domain. Beginning with a system-specific ODD definition, a set of core competencies are identified.

A gasoline’s chemical composition impacts a vehicle’s sooting tendency and therefore has been the subject of numerous emissions studies. From these studies, several mathematical correlation equations have been developed to predict a gasoline’s sooting tendency in modern spark-ignited internal combustion engine vehicles. This paper reviews the recently developed predictive tool methods and summarizes five years of global market fuel survey data to characterize gasoline sooting tendency trends around the world. Additionally, the paper will evaluate and suggest changes to the predictive methods to improve emissions correlations.

Thermoplastics find application in many automotive components. Off late, hardware testing is supplemented by analysis using finite element (FE) codes. One of the factors determining the analysis accuracy is the representation of the components with suitable material models. While a uniaxial tensile test on the specimens typically provides engineering stress-strain data, material plasticity models in commercial FE solvers, such as LS-DYNA and ABAQUS, require equivalent plastic strain versus true stress as input. Engineering stress and strain can be converted to the corresponding true stress and true strain using equations based on the constant volume assumption; however, these equations are valid only up to the point of necking.

The establishment of highly-diluted combustion strategies is one of the major challenges that the next generation of sustainable internal combustion engines must face. The desirable use of high EGR rates and of lean mixtures clashes with the tolerable combustion stability. To this aim, the development of numerical models able to reproduce the degree of combustion variability is crucial to allow the virtual exploration and optimization of a wide number of innovative combustion strategies. In this study ignition experiments using a conventional coil system are carried out in a closed volume combustion vessel with side-oriented flow generated by a speed-controlled fan. Acquisitions for four combinations of premixed propane/air mixture quality (Φ=0.9,1.2), dilution rate (20%-30%) and lateral flow velocity (1-5 m/s) are used to assess the modelling capabilities of a newly developed spark-ignition model for large-eddy simulation (GLIM, GruMo-UniMORE LES Ignition Model).

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.

In order to further understand the sequence of events leading to stochastic preignition in a spark-ignition engine, a methodology previously developed by the authors was used to evaluate the propensity of a wide range of fuels to establishing propagating flames under conditions representative of those at which stochastic preignition (SPI) occurs. The fuel matrix included single component hydrocarbons, binary mixtures, and real fuel blends. The propensity of each fuel to establish a flame was correlated to multiple fuel properties and shown to exhibit consistent blending behaviors. No single parameter strongly predicted a fuel’s propensity to establish a flame, while multiple reactivity-based parameters exhibited moderate correlation. A two-stage model of the flame establishment process was developed to interpret and explain these results.