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Modern exhaust systems contain not only a piping network to transport hot gas from the engine to the atmosphere, but also functional components such as the catalytic converter and turbocharger. The turbocharger is common place in the automotive industry due to their capability to increase the specific power output of reciprocating engines. As the exhaust system is a main heat source for the under body of the vehicle and the turbocharger is located within the engine bay, it is imperative that accurate surface temperatures are achieved. A study by K. Haehndel [1] implemented a 1D fluid stream as a replacement to solving 3D fluid dynamics of the internal exhaust flow. To incorporate the 3D effects of internal fluid flow, augmented Nusselt correlations were used to produce heat transfer coefficients. It was found that the developed correlations for the exhaust system did not adequately represent the heat transfer of the turbocharger.

Contrails and aircraft-induced cirrus clouds are reputed being the largest components of aviation-induced global warming, even greater than carbon dioxide (CO2) exhaust emissions by aircraft. This article presents a contrail model algorithm specifically developed to be integrated within a multi-objective flight trajectory optimization software framework. The purpose of the algorithm is to supply to the optimizer a measure of the estimated radiative forcing from the contrails generated by the aircraft while flying a specific trajectory. In order to determine the precise measure, a comprehensive model is employed exploiting the Schmidt-Appleman criterion and ice-supersaturation regions. Additional parameters such as the solar zenith angle, contrail lifetime and spread are also considered.

Intense competition in the automotive industry requires continuous reduction in innovation cycle time, even as corporations are downsizing and system complexity is increasing. Subsequently, the application of recently introduced Rapid Algorithm Development (RAD) tools has facilitated significant advances in the development of embedded control systems. The RAD steps include system modeling, control algorithm design, simulation analysis, automated calibration design, and vehicle implementation through automatic code generation. The application of RAD tools and the associated benefits are described, specifically in the context of Engine Management Systems (EMS). Such benefits include significant reductions in development cycle time, open architecture, automated calibration, and information reuse.

When presented with new technology that removes past constraints, it is often beneficial to revisit old learning's to see if they still hold, and to understand how these can be best applied to the new technology. Brake-By-Wire (BBW) systems replace all the mechanical linkages of conventional hydraulic brake systems with ‘dry’ electrical components [2],[3]. The advent of this technology poses the possibility of revisiting conventional ABS control systems by utilizing the continuous nature that BBW offers. Presented is a BBW model based wheel slip controller using a generic continuous time Model Predictive Control (MPC) algorithm [15]. The result being the first of many steps taken in understanding the full potential that BBW systems offer.

This paper presents a brake pressure estimation algorithm for Delphi Traction Control Systems (TCS). A control oriented lumped parameter model of a brake control system is developed using Matlab/Simulink. The model is derived based on a typical brake system and is generic to other types of brake control hardware systems. For application purposes, the model is simplified to capture the dominant dynamic brake pressure response. Vehicle experimental data collected under various scenarios are used to validate the algorithm. Simulation results show that the algorithm gives accurate pressure estimation. In addition, the calibration procedure is greatly simplified

This paper presents a theoretical and experimental study of a cylinder deactivation valvetrain system for the integration into an Engine Management System (EMS). A control-oriented lumped parameter model of the deactivation valvetrain system is developed and implemented using Matlab/Simulink, and validated by experimental data. Through simulation and experimental data analysis, the effect of operating conditions on the dynamic response is captured and characterized, over a wide range of operating conditions. The algorithm provides a basis for the calibration of the deactivation hardware. The generic characterization of the dynamic response can simplify the calibration parameters for the implementation in engine management systems.

This paper describes an environment for the development of production Engine Management Systems (EMS). This includes a formal framework and modeling methodology. The environment is based on using Simulink/Stateflow for developing a control system executable specification and a plant model. This allows for simulations of the system to be performed at the engineer's desk, which is identical performance with production software. We provide the details for incorporating production legacy code into the Simulink/Stateflow control system. The system includes a multi-rate, and event driven operating system. This system is developed to facilitate new algorithm development and automated software testing. Based on Simulink/Stateflow this specification will be suitable for use with commercial automatic code generation tools.

This paper describes the verification and comparison of position control algorithms for a continuously-variable cam phaser. Robust Engineering techniques are used. Two non-linear PID control algorithms are designed to control cam phaser position. The first algorithm is a more complex control strategy while the second is a thrifted approach that seeks to reduce throughput requirements. An L18 orthogonal array is established with noise factors that affect the quality of cam phaser control. Using the orthogonal array, the number of experiment test points required to characterize the control algorithm response is reduced from 8,748 to thirty-six. The test points of the orthogonal array are investigated experimentally on a motored engine outfitted with cam phaser hardware. The desired and actual cam position data are compared and analyzed for all points in the orthogonal array.

This paper describes the development and implementation of an Engine Drag Control algorithm to improve vehicle stability performance. Engine drag can occur on low and high coefficient surfaces when the driver suddenly releases the throttle. If the engine drag force becomes larger than the frictional force between the tire and the road, the tires will break loose from the surface and slip. This could induce vehicle instability especially with rear drive vehicles on low-coefficient surfaces. The EDC algorithm has been developed to provide accurate control of the wheels. EDC will help reduce the yaw rate of the vehicle and thus achieve greater vehicle stability. The paper also presents methods used to test the robustness of such a system. The purpose of the testing was to ensure that there would be no false activations of EDC under normal driving conditions and also to ensure that, when the system is active, it is mostly transparent to the driver.

Today automotive system suppliers develop more-or-less independent systems, such as brake, power steering and suspension systems. In the future, car manufacturers like Volvo will build up vehicle control systems combining their own algorithms with algorithms provided by automotive system suppliers. Standardization of interfaces to actuators, sensors and functions is an important enabler for this vision and will have major consequences for functionality, prices and lead times, and thus affects both vehicle manufacturers and automotive suppliers. The investigation of the level of appropriate interfaces, as part of the European BRAKE project, is described here. Potential problems and consequences are discussed from both a technical and a business perspective. This paper provides a background on BRAKE and on the functional decomposition upon which the interface definitions are based. Finally, the interface definitions for brake system functionality are given.

Delphi is developing a new combustion technology called Gasoline Direct-injection Compression Ignition (GDCI), which has shown promise for substantially improving fuel economy. This new technology is able to reuse some of the controls common to traditional spark ignition (SI) engines; however, it also requires several new sensors and actuators, some of which are not common to traditional SI engines. Since this is new technology development, the required hardware set has continued to evolve over the course of the project. In order to support this development work, a highly capable and flexible electronic control system is necessary. Integrating all of the necessary functions into a single controller, or two, would require significant up-front controller hardware development, and would limit the adaptability of the electronic controls to the evolving requirements for GDCI.

An algorithm for estimation of vehicle yaw rate and side slip angle using steering wheel angle, wheel speed, and lateral acceleration sensors is proposed. It is intended for application in vehicle stability enhancement systems, which use controlled brakes or steering. The algorithm first generates two initial estimates of yaw rate from wheel speeds and from lateral acceleration. A new estimate is subsequently calculated as a weighted average of the two initial ones, with the weights proportional to confidence levels in each estimate. This preliminary estimate is fed into a closed loop nonlinear observer, which generates the final estimate of yaw rate along with estimates of lateral velocity and side slip angle. Parameters of the observer depend on the estimated surface coefficient of adhesion, thus providing adaptation to changes in road surface coefficient of adhesion.

A finite element model of a folded airbag with the module cover and steering wheel system was developed to estimate the injury numbers of a 5th percentile female dummy in an out-of-position (OOP) situation. The airbag model was correlated with static airbag deployments and standard force plate tests. The 5th percentile finite element dummy model developed by First Technology Safety Systems (FTSS) was used in the simulation. The following two OOP tests were simulated with the airbag model including a validated steering wheel finite element model: 1. Chest on air bag module for maximum chest interaction from pressure loading (MS6-D) and 2. Neck on air bag module for maximum neck interaction from membrane loading (MS8-D). These two simulations were then compared to the test results. Satisfactory correlation was found in both the cases.

Compromises inherent with fixed valve lift and event timing have prompted engine designers to consider Variable Valve Actuation (VVA) systems for many decades. In recent years, some relatively basic forms of VVA have been introduced into production engines. Greater performance and driveability expectations of customers, more stringent emission regulations set by government legislators, and the mutual desire for higher fuel economy are increasingly at odds. As a solution, many OEM companies are seriously considering large-scale application of higher function VVA mechanisms in their next generation vehicles. This paper describes the continuing development progress of a mechanical VVA system. Design features and operation of the mechanism are explained. Test results are presented in two sections: motored cylinder head test data focuses on VVA system friction, control system performance, valve lift and component stress.

Automotive occupant safety continues to evolve. At present this area has gathered a strong consumer interest which the vehicle manufacturers are tapping into with the introduction of many new safety technologies. Initially, individual passive devices and features such as seatbelts, knee- bolsters, structural crush zones, airbags etc., were developed for to help save lives and minimize injuries in accidents. Over the years, preventive measures such as improving visibility, headlights, windshield wipers, tire traction etc., were deployed to help reduce the probability of getting into an accident. With tremendous new research and improvements in electronics, we are at the stage of helping to actively avoid accidents in certain situations as well as providing increased protection to vehicle occupants and pedestrians.

Since the late 1980s, Delphi Automotive Systems has been very involved with the practical development of a variety of Collision Avoidance products for the near- and long-term automotive market. Many of these complex collision avoidance products will require the integration of various vehicular components/systems in order to provide a cohesive functioning product that is seamlessly integrated into the vehicle infrastructure. One such example of this system integration process was the development of an Adaptive Cruise Control system on an Opel Vectra. The design approach heavily incorporated system engineering processes/procedures. The critical issues and other technical challenges in developing these systems will be explored. Details on the hardware and algorithms developed for this vehicle, as well as the greater systems integration issues that arose during its development will also be presented.

A Barometric Pressure Estimator (BPE) algorithm was implemented in a production speed-density Engine Management System (EMS). The BPE is a model-based, easily calibrated algorithm for estimating barometric pressure using a standard set of production sensors, thereby avoiding the need for a barometric pressure sensor. An accurate barometric pressure value is necessary for a variety of engine control functions. By starting with the physics describing the flow through the induction system, an algorithm was developed which is simple to understand and implement. When used in conjunction with the Pneumatic and Thermal State Estimator (PSE and TSE) algorithms [2], the BPE requires only a single additional calibration table, generated with an automated processing routine, directly from measured engine data collected at an arbitrary elevation, in-vehicle or on a dynamometer. The algorithm has been implemented on several different engines.

In this paper we discuss in detail an algorithm that addresses cylinder-to-cylinder imbalance issues. Maintaining even equivalence-ratio (ϕ) control across all the cylinders of an engine is confounded by imbalances which include fuel-injector flow variations, fresh-air intake maldistribution and uneven distribution of Exhaust Gas Re-circulation (EGR). Moreover, in markets that are growing increasingly cost conscious, with ever tightening emissions regulations, correcting for such mismatches must not only be done, but done at little or no additional cost. To address this challenge, we developed an Individual Cylinder Fuel Control (ICFC) algorithm that estimates each cylinder's individual ϕ and then compensates to correct for any imbalance using only existing production hardware. Prior work in this area exists1,2, yet all disclosed production-intent work was performed using wide-range oxygen sensors, representing cost increases.

Both evaporative emissions and tailpipe emissions have been reduced by more than 90% from uncontrolled levels in state-of-the-art. However, now that the objective is to reach near-zero emission levels, the need for aggressive purging of the canister and fuel tank and the need for extremely precise control of engine Air/Fuel ratio (A/F) come into conflict. On-board diagnostics and the wide variation in operating conditions and fuel properties in the “real world” add to the challenge of resolving these conflicting requirements. An advanced canister purge algorithm has been developed which substantially eliminates the effect of canister purge on A/F control by estimating and compensating for the fuel and air introduced by the purge system. This paper describes the objectives and function of this algorithm and the validation of its performance.

Accurate and robust tracking of objects is of growing interest amongst the computer vision scientific community. The ability of a multi-sensor system to detect and track objects, and accurately predict their future trajectory is critical in the context of mission- and safety-critical applications. Remotely Piloted Aircraft System (RPAS) are currently not equipped to routinely access all classes of airspace since certified Detect-and-Avoid (DAA) systems are yet to be developed. Such capabilities can be achieved by incorporating both cooperative and non-cooperative DAA functions, as well as providing enhanced communications, navigation and surveillance (CNS) services. DAA is highly dependent on the performance of CNS systems for Detection, Tacking and avoiding (DTA) tasks and maneuvers.