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GM's R oad-to- L ab-to- M ath (RLM) initiative is a fundamental engineering strategy leading to higher quality design, reduced structural cost, and improved product development time. GM started the RLM initiative several years ago and the RLM initiative has already provided successful results. The purpose of this paper is to detail the specific RLM efforts at GM related to powertrain controls development and calibration. This paper will focus on the current state of the art but will also examine the history and the future of these related activities. This paper will present a controls development environment and methodology for providing powertrain controls developers with virtual (in the absence of ECU and vehicle hardware) calibration capabilities within their current desktop controls development environment.

Complex chassis systems operate in various environments such as low-mu surfaces and highly dynamic maneuvers. The existing metrics for lateral motion hazard by Neukum [13] and Amberkar [17] have been developed and correlated to driver behavior against disturbances on straight line driving on a dry surface, but do not cover low-mu surfaces and dynamic driving scenarios which include both linear and nonlinear region of vehicle operation. As a result, an improved methodology for evaluating vehicle yaw dynamics is needed for safety analysis. Vehicle yaw dynamics safety analysis is a methodical evaluation of the overall vehicle controllability with respect to its yaw motion and change of handling characteristic.

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.

Low-temperature gasoline combustion (LTGC) engines can deliver high efficiencies, with ultra-low emissions of nitrogen oxides (NOx) and particulate matter (PM). However, controlling the combustion timing and maintaining robust operation remains a challenge for LTGC engines. One promising technique to overcoming these challenges is spark assist (SA). In this work, well-controlled, fully premixed experiments are performed in a single-cylinder LTGC research engine at 1200 rpm using a cylinder head modified to accommodate a spark plug. Compression ratios (CR) of 16:1 and 14:1 were used during the experiments. Two different fuels were also tested, with properties representative of premium- and regular-grade market gasolines. SA was found to work well for both CRs and fuels. The equivalence ratio (ϕ) limits and the effect of intake-pressure boost on the ability of SA to compensate for a reduced Tin were studied. For the conditions studied, ϕ=0.42 was found to be most effective for SA.

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.

Gasoline Particulate Filters (GPF) are widely employed in exhaust aftertreatment systems of gasoline engines to meet the stringent particulate emissions requirements of Euro6 and China6 standard. While providing an effective filtration of particles, the GPF increases the engine backpressure as a penalty due to accumulation of soot. To clean the accumulated soot, periodical burning of soot is achieved by the onboard control models and lot of effort is spent on calibrating the same. In order to understand pressure drop behavior across GPF, detailed pressure drop measurements were conducted at clean, soot and ash loaded conditions at engine dynamometer and at vehicle conditions. Effect of degreening of GPF was studied to take into account any change in pressure drop characteristics of onboard control models during GPF aging in the vehicle.

This paper describes the design of a multivariable, constrained Model Predictive Control (MPC) system for torque tracking in turbocharged gasoline engines scheduled for production by General Motors starting in calendar year 2018. The control system has been conceived and co-developed by General Motors and ODYS. The control approach consists of a set of linear MPC controllers scheduled in real time based on engine operating conditions. For each MPC controller, a linear model is obtained by system identification with data collected from engines. The control system coordinates throttle, wastegate, intake and exhaust cams in real time to track a desired engine torque profile, based on measurements and estimates of engine torque and intake manifold pressure.

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.

A primary goal of large eddy simulation, LES, is to capture in-cylinder cycle-to-cycle variability, CCV. This is a first step to assess the efficacy of 35 consecutive computed motored cycles to capture the kinetic energy in the TCC-III engine. This includes both the intra-cycle production and dissipation as well as the kinetic energy CCV. The approach is to sample and compare the simulated three-dimensional velocity equivalently to the available two-component two-dimensional PIV velocity measurements. The volume-averaged scale-resolved kinetic energy from the LES is sampled in three slabs, which are volumes equal to the two axial and one azimuthal PIV fields-of-view and laser sheet thickness. Prior to the comparison, the effects of sampling a cutting plane versus a slab and slabs of different thicknesses are assessed. The effects of sampling only two components and three discrete planar regions is assessed.

In today’s race for improved fuel economy and lower emissions from gasoline engines, precise metering of delivered fuel is essential. Gasoline Direct Injection fuel systems provide the means for improved combustion efficiency through mixture preparation and better atomization. These improvements can be achieved from both increasing fuel pressure and using multiple injection events, which significantly reduce the required energizing time per injection, and in a number of cases, force the injector to operate at less than full stroke. When the injector operates in this condition, the influence of variation in injector dynamics account for a large percentage of the delivered fuel and require compensation to ensure accurate fuel delivery. Injector dynamics such as opening delay and closing time are influenced by operating conditions such as fuel pressure, energizing time, and temperature.

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.

Electric vehicles have a strong potential to reduce a continued dependence on fossil fuels and help the environment by reducing pollution. Despite the desirable advantage, the introduction of electrified vehicles into the market place continues to be a challenge due to cost, safety, and life of the batteries. General Motors continues to bring vehicles to market with varying level of hybrid functionality. Since the introduction of Li-ion batteries by Sony Corporation in 1991 for the consumer market, significant progress has been made over the past 25 years. Due to market pull for consumer electronic products, power and energy densities have significantly increased, while costs have dropped. As a result, Li-ion batteries have become the technology of choice for automotive applications considering space and mass is very critical for the vehicles.

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.

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.

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.

Electrical connections have a normal operational temperature range. A high resistance, such as a poor connection, in an electrical circuit has been reported to cause a temperature increase exceeding normal operational range at the connection. This study measures the temperature increase in a typical automotive bolted battery cable connection with low to zero torque values and simulated high resistance under different load conditions. The torque is changed from maximum design value to 0 Nm and the temperature increase at the connection is measured. The high resistance connections, manually created by adjusting the contacts, are tested for several power loss values at the connection. The temperature rise under these conditions at the connection is measured and subsequently recorded. The maximum temperature increase at the bolted cable connection recorded at low torque values including 0 Nm torque compared to the maximum typical design value of 17 Nm is 10.5 °C.

There have been tremendous improvements in China fuel quality in recent years in conjunction with newly implemented vehicle emissions standards to combat air pollution. The focus of concern is particulate emissions from gasoline engines especially from high volume gasoline direct inject (GDI) engines, therefore the China 6 (GB 18351.6-2016) emission standard introduces strict PM/PN requirements. Because the fuel and vehicle are an integrated system, the composition of gasoline is one of the factors affecting PM/PN emissions. Ethanol and aromatics are widely used as octane boosters, changing the composition of China’s gasoline pool. In this study, two gasoline oxygenates, ethanol and methyl tert-butyl ether (MTBE), and heavy aromatic hydrocarbons were studied in vehicles with a GDI engines. Vehicle tests were performed on the Worldwide Harmonized Light Vehicles Test Cycle (WLTC).

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.

The Particulate Matter Index (PMI) is a helpful tool which provides an indication of a fuel’s sooting tendency. Currently, the index is being used by various laboratories and OEMs as a metric to understand the gasoline fuels impact on both sooting found on engine hardware and vehicle out emissions. This paper will explore a new method that could be used to give indication of the sooting tendency of the gasoline range fuels, called the Particulate Evaluation Index (PEI), and provide the detailed equation in its initial form. In addition, the PEI will be shown to have a good correlation agreement to PMI. The paper will then give a detailed explanation of the data used to develop it. Initial vehicle PM/PN data will also be presented that shows correlations of the indices to the vehicle response.

Stochastic or Low-Speed Preignition (SPI or LSPI) is an undesirable abnormal combustion phenomenon encountered in spark-ignition engines. It is characterized by very early heat release and high cylinder pressure and can cause knock, noise and ultimately engine damage. Much of the focus on mitigating SPI has been directed towards the engine oil formulation, leading to the emergence of the Sequence IX test and second-generation GM dexos® oil requirements. Engine design, calibration and fuels also contribute to the prevalence of SPI. As part of a recently completed research consortium, a series of engine tests were completed to determine the impact of fuel composition on SPI frequency. The fuel blends had varying levels of paraffins, olefins, aromatics and ethanol.