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Active safety systems will have a great impact in the next generation of vehicles. This is partly originated by the increasing consumer's interest for safety and partly by new traffic safety laws. Control actions in the vehicle are based on an extensive environment model which contains information about relevant objects in vehicle surroundings. Sensor data fusion integrates measurements from different surround sensors into this environment model. In order to avoid system malfunctions, high reliability in the interpretation of the situation, and therefore in the environment model, is essential. Hence, the main idea of data fusion is to make use of the advantages of using multiple sensors and different technologies in order to fulfill these requirements, which are especially high due to autonomous interventions in vehicle dynamics (e. g. automatic emergency braking).

A method for identification of object impact location and bumper stiffness curve is presented in this paper. The method calculates an offset distance of object impact based on intrusions obtained from three accelerometers mounted in the bumper fascia. The method also evaluates a center strength based on an absolute sum of acceleration. A characteristic line has been introduced in a two-dimensional domain consisting of intrusion-based offset and center strength. When test data are projected onto the characteristic line, an improved object impact location can be achieved. An intrusion curve over offset distance is obtained for impact tests striking at different locations with the same object and same speed. Then, a bumper stiffness curve can be identified by taking a reciprocal of the intrusion curve. This study shows a bumper stiffness curve can be used for an impact object classification for the pedestrian protection system.

Global demand for alternative fuels to combat rising energy costs has sparked a renewed interest in catalysts that can effectively remediate NOx emissions resulting from combustion of a range of HC based fuels. Because many of these new engine technologies rely on lean operating environments to produce efficient power, the resulting emissions are also present in a lean atmosphere. While HCs are easily controlled in such environments, achieving high NOx conversion to N2 has continued to elude fully satisfactory solution. Until recently, most approaches have relied on catalysts with precious metals to either store NOx and subsequently release it as N2 under rich conditions, or use NH3 SCR catalysts with urea injection to reduce NOx under lean conditions. However, new improvements in Ag based technologies also look very promising for NOx reduction in lean environments.

This paper focuses on the combustion development portion of the Advanced Combustion Controls Enabling Systems and Solutions (ACCESS) project, a joint research project partially funded by a Department of Energy grant. The main goal of the project is to improve fuel economy in a gasoline fueled light-duty vehicle by 30% while maintaining similar performance and meeting SULEV emission standards for the Federal Test Procedure (FTP) cycle. In this study, several combustion modes Spark Ignited (SI), Homogeneous Charge Compression Ignition (HCCI), Spark- Assisted Compression Ignition (SACI)) were compared under various conditions (naturally aspirated, boosted, lean, and stoichiometric) to compare the methods of controlled auto-ignition on a downsized, boosted multi-cylinder engine with an advanced valvetrain system capable of operating under wide negative valve overlap (NVO) conditions.

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.

In this paper, dynamics and stability of an articulated vehicle in the yaw plane are examined through analysis, simulations, and vehicle testing. Control of a vehicle-trailer combination using active braking of the towing vehicle is discussed. A linear analytical model describing lateral and yaw motions of a vehicle-trailer combination is used to study the effects of parameter variations of the trailer on the dynamic stability of the system and limitations of different control strategies. The results predicted by the analytical model are confirmed by testing using a vehicle with a trailer in several configurations. Design of the trailer makes it possible to vary several critical parameters of the trailer. The test data for vehicle with trailer in different configurations is used to validate the detailed non-linear simulation model of the vehicle-trailer combination.

Selective Catalytic Reduction (SCR) is the dominant solution for meeting future NOx reduction regulations for heavy-duty diesel powertrains. SCR systems benefit from closed-loop control if an appropriate exhaust gas sensor were available. An ammonia sensor has recently been developed for use as a feedback element in closed-loop control of urea dosing in a diesel SCR aftertreatment system. Closed-loop control of SCR dosing enables the SCR system to be robust against disturbances and to meet conformity of production (COP) and in-use compliance norms. The ammonia sensor is based on a non-equilibrium electrochemical principle and outputs emf signals. The sensor performs well when tested in a diesel engine exhaust environment and has minimum cross interference with CO, HC, NO, NO2, SO2, H2O and O2. Previous work, done in a simulation environment, demonstrated that an ammonia sensor provides the optimal feedback for urea dosing control algorithms in closed-loop SCR systems.

With increasingly stringent emissions regulations and concurrent requirements for enhanced engine thermal efficiency, a comprehensive characterization of the automotive gasoline fuel spray has become essential. The acquisition of accurate and repeatable spray data is even more critical when a combustion strategy such as gasoline direct injection is to be utilized. Without industry-wide standardization of testing procedures, large variablilities have been experienced in attempts to verify the claimed spray performance values for the Sauter mean diameter, Dv90, tip penetration and cone angle of many types of fuel sprays. A new SAE Recommended Practice document, J2715, has been developed by the SAE Gasoline Fuel Injection Standards Committee (GFISC) and is now available for the measurement and characterization of the fuel sprays from both gasoline direct injection and port fuel injection injectors.

Low-cost lean NOx aftertreatment is one of the main challenges facing high-efficiency gasoline and diesel engines operating with lean mixtures. While there are many candidate technologies, they all offer tradeoffs. We have investigated a multi-component Dual SCR aftertreatment system that is capable of obtaining NOx reduction efficiencies of greater than 90% under lean conditions, without the use of precious metals or urea injection into the exhaust. The Dual SCR approach here uses an Ag HC-SCR catalyst followed by an NH3-SCR catalyst. In bench reactor studies from 150 °C to 500 °C, we have found, for modest C/N ratios, that NOx reacts over the first catalyst to predominantly form nitrogen. In addition, it also forms ammonia in sufficient quantities to react on the second NH3-SCR catalyst to improve system performance. The operational window and the formation of NH3 are improved in the presence of small quantities of hydrogen (0.1–1.0%).

High technology, spark ignition direct injection (SIDI), engines are currently capable of achieving optimum horsepower and ULEV emissions levels. However, to meet the requirements of modern automotive powertrains, the task of increasing power density, improving fuel economy and reaching SULEV2 emissions is much more challenging. To achieve this, direct injection (DI) fuel systems offer the greatest precision and flexibility for engine fuel control. Features like high pressure start and improved catalyst heating, through multiple injections per combustion cycle, produce low engine-out emissions without the need for a secondary air injection system. This paper describes the analytical and experimental work done to achieve SULEV emissions levels for a twin-turbocharged derivative of General Motors (GM) high feature V6 engine.

A method for detection of ethanol content in fuel for an engine equipped with direct injection (DI) is presented. The methodology is based on in-cylinder pressure measurements during the compression stroke and exploits the different charge cooling properties of ethanol and gasoline. The concept was validated using dynamometer data of a 2.0L DI turbocharged engine with variable valve timing (VVT). An algorithm was developed to process the experimental data and generate a residue from the complex cycle-to-cycle in-cylinder pressure evolution which captures the charge cooling effect. The experimental results show that there is a monotonic correlation between the residues and the fuel ethanol percentage in the majority of the cases. However, the correlation varies for different engine operating parameters; such as, speed, load, valve timing, fuel rail pressure, intake and exhaust temperature and pressure.

When designing the vehicle cooling system, accurate knowledge of the required airflow through the heat exchangers is necessary for proper specification of the cooling fan, the heat exchangers, and the associated electrical loads. The simplest method of expressing the engine cooling fan performance requirement is based on the “open air” performance curve measured on the airflow test chamber, excluding effects of the heat exchangers and vehicle environment. However, the difference between open air and on-system airflow performance and noise (installed on the heat exchangers) can be significant due to the influence of the heat exchangers, fan shroud, and downstream blockage on the airflow through the fan. If these factors are neglected in the evaluation of the cooling fan, incorrect specification of the fan performance can result.

The primary function of an airbag control module is to detect crashes, discriminate and predict if a deployment is necessary, then deploy the restraint systems including airbags and where applicable, pretensioners. At General Motors (GM), the internal term for airbag control module is Sensing and Diagnostic Module (SDM). In the 1994 model year, GM introduced its SDM on some of its North American airbag-equipped vehicles. A secondary function of that SDM and all subsequent SDMs is to record crash related data. This data can include data regarding impact severity from internal accelerometers and pre-crash vehicle data from various chassis and powertrain modules. Previous researchers have addressed the accuracy of both the velocity change data, recorded by the SDM, and the pre-crash data, but the assessment of the timing of the pre-crash data has been limited to a single family of modules (Delphi SDM-G).

An experimental study is performed for homogeneous charge compression ignition (HCCI) combustion focusing on late phasing conditions with high cyclic variability (CV) approaching misfire. High CV limits the feasible operating range and the objective is to understand and quantify the dominating effects of the CV in order to enable controls for widening the operating range of HCCI. A combustion analysis method is developed for explaining the dynamic coupling in sequences of combustion cycles where important variables are residual gas temperature, combustion efficiency, heat release during re-compression, and unburned fuel mass. The results show that the unburned fuel mass carries over to the re-compression and to the next cycle creating a coupling between cycles, in addition to the well known temperature coupling, that is essential for understanding and predicting the HCCI behavior at lean conditions with high CV.

This paper focuses on the engine design portion of the Advanced Combustion Controls Enabling Systems and Solutions (ACCESS) project, a joint research project partially funded by a Department of Energy grant. The main goal of the project is to improve fuel economy in a gasoline fueled light-duty vehicle by 25% while maintaining similar performance and meeting SULEV emission standards. A Cadillac CTS with a high-feature naturally-aspirated 3.6L V6 engine was chosen as the baseline vehicle. To achieve the target fuel economy improvement over the baseline engine configuration, gasoline turbocharged direct-injection (GTDI) technology was utilized for engine downsizing in combination with part-load lean homogeneous charge compression ignition (HCCI) operation for further fuel economy gains. The GM 2.0L I4 GTDI Ecotec engine was used as the platform for the basis of this design.

The paper describes a new strategy for real-time sensor diagnostics that is based on the statistical correlation of various sensor signal pairs. During normal fault-free operation there is a certain correlation between the sensor signals which is lost in the event of a fault. The proposed algorithm quantifies the correlation between sensor signal pairs using real-time scalar metrics based on the Mahalanobis-distance concept. During normal operation all metrics follow a similar pattern, however in the event of a fault; metrics involving the faulty sensor would increase in proportion to the magnitude of the fault. Thus, by monitoring this pattern and using a suitable fault-signature table it is possible to isolate the faulty sensor in real-time. Preliminary simulation results suggest that the strategy can mitigate the false-alarms experienced by most model-based diagnostic algorithms due to an intrinsic ability to distinguish nonlinear vehicle behavior from actual sensor faults.

The implementation of connected and automated vehicle (CAV) technologies enables a novel computational framework for real-time control aimed at optimizing energy consumption with associated benefits. In this paper, we implement an optimal control framework, developed previously, in an Audi A3 etron plug-in hybrid electric vehicle, and demonstrate that we can improve the vehicle’s efficiency and travel time in a corridor including an on-ramp merging, a speed reduction zone, and a roundabout. Our exposition includes the development, integration, implementation and validation of the proposed framework in (1) simulation, (2) hardware-in-the-loop (HIL) testing, (3) connectivity enabled virtual reality based bench-test, and (4) field test in Mcity. We show that by adopting such inexpensive, yet effective process, we can efficiently integrate and test the control framework, establish proper connectivity and data transmission between different modules of the system, and reduce uncertainty.

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.

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.

A single-cylinder engine was used to study the potential of a high-efficiency combustion concept called gasoline direct-injection compression-ignition (GDCI). Low temperature combustion was achieved using multiple injections, intake boost, and moderate EGR to reduce engine-out NOx and PM emissions engine for stringent emissions standards. This combustion strategy benefits from the relatively long ignition delay and high volatility of regular unleaded gasoline fuel. Tests were conducted at 6 bar IMEP - 1500 rpm using various injection strategies with low-to-moderate injection pressure. Results showed that triple injection GDCI achieved about 8 percent greater indicated thermal efficiency and about 14 percent lower specific CO2 emissions relative to diesel baseline tests on the same engine. Heat release rates and combustion noise could be controlled with a multiple-late injection strategy for controlled fuel-air stratification. Estimated heat losses were significantly reduced.