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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.

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.

This work discusses the development of SAE procedure J2747, “Hydraulic Pump Airborne Noise Bench Test”. This is a test procedure describing a standard method for measuring radiated sound power levels from hydraulic pumps of the type typically used in automotive power steering systems, though it can be extended for use with other types of pumps. This standard was developed by a committee of industry representatives from OEM's, suppliers and NVH testing firms familiar with NVH measurement requirements for automotive hydraulic pumps. Details of the test standard are discussed. The hardware configuration of the test bench and the configuration of the test article are described. Test conditions, data acquisition and post-processing specifics are also included. Contextual information regarding the reasoning and priorities applied by the development committee is provided to further explain the strengths, limitations and intended usage of the test procedure.

Production software validation is critical during software development, allowing potential quality issues that could occur in the field to be minimized. By developing automated and repeatable software test methods, test cases can be created to validate targeted areas of the control software for confirmation of the expected results from software release to release. This is especially important when algorithm/software development timing is aggressive and the management of development activities in a global work environment requires high quality, and timely test results. This paper presents a hardware-in-the-loop (HIL) test bench for the validation of production transmission controls software. The powertrain model used within the HIL consists of an engine model and a detailed automatic transmission dynamics model. The model runs in an OPAL-RT TestDrive based HIL system.

This paper describes a new tool to capture cylinder pressure information, calculate combustion parameters, and implement control algorithms. There are numerous instrumentation and prototyping systems which can provide some or all of this capability. The Cylinder Pressure Development Controller (CPDC) is unique in that it uses advanced high volume automotive grade circuitry, packaging, and software methodologies. This approach provides insight regarding the implementation of cylinder pressure based controls in a production engine management system. A high performance data acquisition system is described along with a data reduction technique to minimize data processing requirements. The CPDC software architecture is discussed along with model-based algorithm development and autocoding. Finally, CPDC calculated combustion parameters are compared with those from a well established combustion analysis system and thermodynamic simulations.

Advanced chassis control systems enable a vehicle to achieve new levels of performance in handling stability and responsiveness. In recent work by NHTSA and others, the performance of Electronic Stability Control (ESC) systems has been studied with focus on yaw stability and roll stability of vehicles on high friction surfaces. However, it is recognized that vehicle handling responsiveness is also an important aspect that should be maintained. This paper explores the trade-offs between yaw rate, side slip, and roll motions of a vehicle, and their relationships to handling stability and handling responsiveness. This paper further describes how various control systems are able to manage these motions. The paper also discusses methods to assess vehicle stability and responsiveness using specific maneuvers and measurements, and it includes data from vehicle tests on a slippery surface.

The paper describes the development of a vehicle stability indicator based on the correlation between various current vehicle chassis sensors such as hand wheel angle, yaw rate and lateral acceleration. In general, there is a correlation between various pairs of sensor signals when the vehicle operation is linear and stable and a lack of correlation when the vehicle is becoming unstable or operating in a nonlinear region. The paper outlines one potential embodiment of the technology that makes use of the Mahalanobis distance metric to assess the degree of correlation among the sensor signals. With this approach a single scalar metric provides an accurate indication of vehicle stability.

During the production controller and software development process, one critical step is the controller and software verification. There are various ways to perform this verification. One of the commonly used methods is to utilize an HIL (hardware-in-the-loop) test bench to emulate powertrain hardware for development and validation of powertrain controllers and software. A key piece of an HIL bench is the plant dynamics model used to emulate the external environment of a modern controller, such as engine (ECM), transmission (TCM) or powertrain controller (PCM), so that the algorithms and their software implementation can be exercised to confirm the desired results. This paper presents a 6-speed automatic transmission plant dynamics model development for hardware-in-the-loop (HIL) test bench for the validation of production transmission controls software. The modeling method, model validation, and application in an HIL test environment are described in details.

This paper presents a hardware-in-the-loop (HIL) test bench for the validation of production transmission controls software, with a focus on a closed-loop vehicle drive-train model incorporating a detailed automatic transmission plant dynamics model developed for certain applications. Specifically, this paper presents the closed-loop integration of a 6-speed automatic transmission model developed for our HIL transmission controller and algorithm test bench (Opal-RT TestDrive based). The model validation, integration and its application in an HIL test environment are described in details.

In a CAS system, the distance and relative velocity between front and host vehicles are estimated to calculate time-to-collision (TTC). The distance estimates by different methods will certainly include noise which should be removed to ensure the accuracy of TTC calculations. Kalman filter is a good tool to filter such type of noise. Nevertheless, Kalman filter is a model based filter, which means a correct model is important to get the good filtering results. Usually, a vehicle is either moving with a constant velocity (CV) or constant acceleration (CA) maneuvers. This means the distance data between front and host vehicles can be described by either constant velocity or constant acceleration model. In this paper, first, CV and CA models are used to design two Kalman filters and an interacting multiple model (IMM) is used to dynamically combine the outputs from two filters.

The need for improved emissions control in lean exhaust to meet tightening, world-wide NOx emissions standards has led to the development of selective catalytic reduction of NOx with ammonia as a major technology for emissions control. Current systems are being designed to use a solution of urea (32.5 wt %) dissolved in water or Diesel Exhaust Fluid (DEF) as the ammonia source. While DEF or AdBlue® is widely used as a source of ammonia, it has a number of issues at low temperatures, including freezing below −12 °C, solid deposit formation in the exhaust, and difficulties in dosing at exhaust temperatures below 200 °C. Additionally creating a uniform ammonia concentration can be problematic, complicating exhaust packaging and usually requiring a discrete mixer.

This paper presents the development of a transmission closed loop pressure control system. The objective of this system is to improve transmission pressure control accuracy by employing closed-loop technology. The control system design includes both feed forward and feedback control. The feed forward control algorithm continuously learns solenoid P-I characteristics. The closed loop feedback control has a conventional PID control with multi-level gain selections for each control channel, as well as different operating points. To further improve the system performance, Robust Optimization is carried out to determine the optimal set of control parameters and controller hardware design factors. The optimized design is verified via an L18 experiment on spin dynamometer. The design is also tested on vehicle.

The perceived interior noise has been one of the major driving factors in the design of automotive interior assemblies. Buzz, Squeak and Rattle (BSR) issues are one of the major contributors toward the perceived quality in a vehicle. Traditionally BSR issues have been identified and rectified through extensive hardware testing. In order to reduce the product development cycle and minimize the number of costly hardware builds, however, one must rely on engineering analysis and simulation upfront in the design cycle. In this paper, an analytical and experimental study to identify potential BSR locations in a cockpit assembly is presented. The analytical investigation utilizes a novel and practical methodology, implemented in the software tool Nhance.BSR, for identification and ranking of potential BSR issues. The emphasis here is to evaluate the software for the BSR predictions and the identification of modeling issues, rather than to evaluate the cockpit design itself for BSR issues.

Automotive rollover is a complex mechanical phenomenon. In order to understand the mechanism of rollover and develop any potential countermeasures for occupant protection, efficient and repeatable laboratory tests are necessary. However, these tests are not well understood and are still an active area of research interest. It is not always easy or intuitive to estimate the necessary initial and boundary conditions for such tests to assure repeatability. This task can be even more challenging when rollover is a second or third event (e.g. frontal impact followed by a rollover). In addition, often vehicle and occupant kinematics need to be estimated a-priori, first for the safe operation of the crew and equipment safety, and second for capturing and recording the event. It is important to achieve the required vehicle kinematics in an efficient manner and thus reduce repetitive tests. Mathematical modeling of the phenomenon can greatly assist in understanding such kinematics.

Adaptive Cruise Control (ACC) technology is presently emerging in the automotive market as a convenience function intended to reduce driver workload. It allows the host vehicle to maintain a set speed and distance from preceding vehicles by a forward object detection sensor. The forward object detection sensor is the focal point of the ACC control system, which determines and regulates vehicle acceleration and deceleration through a powertrain torque control system and an automatic brake control system. This paper presents a design of an automatic braking system that utilizes a microprocessor-controlled brake hydraulic modulator. The alternatively qualified automatic braking means is reviewed first. The product level requirements of the performance, robustness, and durability for an automatic brake system are addressed. A brief overview of the presented system architecture is described.

This paper proposes the concept of Generalized Diagnostic Component (GDC) and presents a modular fault diagnostic strategy for safety critical automotive systems. The diagnostic strategy makes full use of hierarchical techniques, integrates the generalized diagnostic design into all-purpose vehicle diagnoses based on reconfiguration of the GDCs, and inherits the model-based diagnostic algorithms developed for Steering/Braking-By-Wire systems. The GDC-based approach simplifies the design and integration of diagnostics in complex dynamical control systems, and has been successfully implemented in an eight degrees of freedom NAVDyn (Non-Linear Analysis of Vehicle Dynamics) simulation model using Matlab Simulink. The simulation results are provided in this paper to testify that the diagnostic strategy and implementation are feasible, efficient and dependable.

With the requirements for reducing the emissions and improving the fuel economy, the automotive companies are developing hybrid, 42 V and fuel cell vehicles. Power electronics is an enabling technology for the development of environmental friendly vehicles, and to implement the various vehicle electrical architectures to obtain the best performance. In this paper, the requirements of the power semiconductor devices and the criteria for selecting the power devices for various types of low emission vehicles are presented. A comparative study of the most commonly used power devices is presented. A brief review of the future power devices that would enhance the performance of the automotive power conversion systems is also presented.

In this paper, we review existing software safety standards, guidelines, and other software safety documents. Common software safety elements from these documents are identified. We then describe an adaptable software safety process for automotive safety-critical systems based on these common elements. The process specifies high-level requirements and recommended methods for satisfying the requirements. In addition, we describe how the proposed process may be integrated into a proposed system safety process, and how it may be integrated with an existing software development process.

Computer modeling and simulation have become one of the primary methods for development and design of automobile occupant protection systems (OPS). To ensure the accuracy and reliability of a math-based OPS design, the correlation quality assessment of mathematical models is essential for program success. In a typical industrial approach, correlation quality is assessed by comparing chart characteristics and scored based on an engineer's modeling experience and judgment. However, due to the complexity of the OPS models and their responses, a systematic approach is needed for accuracy and consistency. In this paper, a correlation grading methodology for the OPS models is presented. The grading system evaluates a wide spectrum of a computer model's performances, including kinematics, dynamic responses, and dummy injury measurements. Statistical analysis is utilized to compare the time histories of the tested and simulated dynamic responses.

Regulatory and market pressures continue to challenge the automotive industry to develop technologies focused on reducing exhaust emissions and improving fuel economy. This paper introduces a practical model, which evaluates the economic value of various technologies based on their ability to reduce fuel consumption, improve emissions or provide consumer benefits such as improved performance. By evaluating the individual elements of economic value as viewed by the OEM manufacturer, while keeping the end consumer in mind, technology selection decisions can be made. These elements include annual fuel usage, vehicle performance, mass reduction and emissions, among others. The following technologies are discussed and evaluated: gasoline direct injection, variable valvetrain technologies, common-rail diesel and hybrid vehicles.