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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.

In the field of vehicle diagnostics accurate instantaneous engine speed information enables the detection and diagnosis of many engine problems, even subtle ones. Currently, there is a limited choice in the ways of obtaining such information. For example, it is known that one can tap into the crank sensor wiring, or use a separate, intrusive method, such as mounting a sensor in the bell housing to sense the rotation of the ring gear. However, the shortcomings of these approaches are locating and gaining access to the crank sensor connector, the location of which varies from vehicle to vehicle. Thus, authors proposed a novel, robust and manufacturing friendly speed sensor. The concept is based on the Villari effect. The sensor, which is attached to the front end of the engine crankshaft, consists of a coil of magnetostrictive wire supplied with AC current. During engine rotation the magnetostrictive wire become stressed due to centrifugal force.

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.

Traffic engineers use time-of-day travel time databases to characterize normal travel times on roads. This information is used by traffic management centers together with information from sensors in the highway to identify problems and to make alternate route recommendations. In this paper, the travel time database concept is extended to a vehicle-to-vehicle communications network for traffic and safety information, wherein the travel time database is generated and stored by vehicles in the network, and used by the vehicles to identify abnormal traffic conditions. This infrastructure-free approach is attractive due to the potential to eliminate highway sensor and sensor maintenance costs, which are major factors that limit the growth of traffic information beyond major roadways in urban regions. Initial work indicates that database storage requirements in the vehicle should be manageable.

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.

In this paper, a comparative study of the production applications of hybrid electric powertrains is presented. Vehicles studied include the Toyota Prius, Honda Insight, Toyota Estima, Toyota Crown, Honda Civic Hybrid, and Nissan Tino. The upcoming Ford Escape Hybrid and General Motors Parallel Hybrid Truck (PHT) will also be included, although advance information is limited. The goal of this paper is to look at what hybrid drivetrain architectures have actually been selected for production and what are the underlying details of these drivetrains. Since hybridizing a powertrain involves significant changes, the powertrain architectures are presented in diagram form, with analysis as to the similarities and advantages represented in these architectures. The specific hybrid functions used to save fuel are discussed. Peak power-to-weight ratio and degree of hybridization are plotted for the vehicles. System voltage versus electric power level are also plotted and analyzed.

Implementation of engine turnoff at idle is desirable to gain improvements in vehicle fuel economy. There are a number of alternatives for implementation of the restarting function, including the existing cranking motor, a 12V or 36V belt-starter, a crankshaft integrated-starter-generator (ISG), and other, more complex hybrid powertrain architectures. Of these options, the 12V belt-alternator-starter (BAS) offers strong potential for fast, quiet starting at a lower system cost and complexity than higher-power 36V alternatives. Two challenges are 1) the need to accelerate a large engine to idle speed quickly, and 2) dynamic torque control during the start for smoothness. In the absence of a higher power electrical machine to accomplish these tasks, combustion-assisted starting has been studied as a potential method of aiding a 12V accessory drive belt-alternator-starter in the starting process on larger engines.

Modern military ground vehicles are dependent not only on armor and munitions, but also on their electronic equipment. Advances in battlefield sensing, targeting, and communications devices have resulted in military vehicles with a wide array of electrical and electronic loads requiring power. These vehicles are typically designed to supply this power via a main internal combustion engine outfitted with a generator. Batteries are also incorporated to allow power to be supplied for a limited time when the engine is off. It is desirable to use a subset of the battlefield electronics in the vehicle while the engine is off, in a mode called “silent watch.” Operating time in this mode is limited, however, by battery capacity unless an auxiliary power unit (APU) is used or the main engines are restarted.

The intensity of a combustion flame ionization current signal (ionsense) can be used to monitor and control combustion in individual cylinders during a cold engine start. The rapid detection of poor or absence of combustion can be used to determine fuel delivery corrections that may prevent engine stalls. With the ionsense cold start control active, no start failures were recorded even when the initially (prior to ionsense correction) commanded fueling had failed to produce a combustible mixture. This new dimension in fuel control allows for leaner cold start calibrations that would still be robust against the possible use of low volatility gasoline. Consequently, when California Phase 2 fuel is used, cold start hydrocarbon emissions could be lowered without the risk of an engine stall if the appropriate fuel is replaced with a less volatile one.

Brake performance can be divided into two distinct classes: base brake performance and controlled brake performance. A base brake event can be described as a normal or typical stop in which the driver maintains the vehicle in its intended direction at a controlled deceleration level that does not closely approach wheel lock. All other braking events where additional intervention may be necessary, such as wheel brake pressure control to prevent lock-up, application of a wheel brake to transfer torque across an open differential, or application of an induced torque to one or two selected wheels to correct an under- or oversteering condition, may be classified as controlled brake performance. Statistics from the field indicate the majority of braking events stem from base brake applications and as such can be classified as the single most important function.

Rollovers are an important vehicle safety issue. Various technologies have been developed to help prevent rollovers from occurring, but the evaluation of rollover resistance typically involves vehicle-handling tests that are conducted on flat road surfaces with a uniform or split coefficient of friction. The purpose of this study is to determine the precipitating events leading to rollovers by analyzing real-world rollover crashes. This is a first step in identifying and developing vehicle tests that are representative of the principal driving scenarios leading to rollovers. The sequence of events leading to rollovers was determined from 63 in-depth investigated cases in the NASS-CDS database from 1995-1999. The sequence was evaluated by vehicle maneuvers, vehicle stability, surface type, road and shoulder transition condition, posted and estimated speeds, vehicle type and driver injury severity.

The laboratory test method commonly known as “random vibration” is almost always used for Squeak & Rattle testing in today's automotive applications due to its obvious advantages: the convenience in simulating the real road input, the relatively low cost, and efficiency in obtaining the desired test results. Typically, Loudness N10 is used to evaluate the Squeak & Rattle (S&R) performance. However, due to the nature of random distribution of the excitation input, the repeatability of the loudness N10 measurements may vary significantly. This variation imposes a significant challenge when one is searching for a fine design improvement solution in minimizing S&R noise, such as a six-sigma study. This study intends to investigate (1) the range of the variations of random vibration control method as an excitation input with a given PSD, (2) the possibility of using an alternate control method (“time-history replication”) to produce the vibration of a given PSD for a S&R evaluation.

Close-coupled or manifold catalysts have been extensively employed to reduce emissions during cold start by achieving quick catalyst light-off. These catalysts must have good thermal durability, high intrinsic light-off activity and high HC/CO/NOx conversions at high temperature and flow conditions. A number of studies have been dedicated to engine control, manifold design and converter optimization to reduce cold start emissions. The current paper focuses on the effect of catalyst design parameters and their performance response to different engine operating conditions. Key design parameters such as catalyst formulation (CeO2 vs. non CeO2), precious metal loading and composition (Pd vs. Pd/Rh), washcoat loading, catalyst thermal mass, substrate properties and key application (in use) parameters such as catalyst aging, exhaust A/F ratio, A/F ratio modulation, exhaust temperature, temperature rise rate and exhaust flow rate were studied on engine dynamometers in a systematic manner.

As automotive electronic control systems continue to increase in usage and complexity, the challenges for developing automotive diagnostics also increase. Reduced development cycle times, the increased significance of diagnostics for safety critical systems, and the integration of vehicle systems across multiple control systems all add to the tasks of developing diagnostics for the automobiles of today and tomorrow. Addressing automotive diagnostics now requires the Tier 1 supplier to utilize a formal diagnostic development methodology. There are also opportunities for Tier 1 suppliers to add value by developing vehicle-level supervisory diagnostic strategies, in addition to subsystem and system-level diagnostic strategies. There is also a prospect to provide strategies and tools to enhance service at the vehicle level. This paper proposes an approach for Tier 1 suppliers to address diagnostic and service issues at the component, system, and vehicle level.

With the inception of model-based design and automatic code generation, many organizations are developing controls and diagnostics algorithms in model-based development tools to meet customer and regulatory requirements. Advances in model-based design have made it easier to generate C code from models and help software engineers streamline their workflow. Typically, after the software has been developed, the models are handed over to a calibration team responsible for calibrating the features to meet specified customer and regulatory requirements. However, once the models are handed over to the calibration team, the calibration engineers are unaware of how to calibrate the features because documentation is not available. Typically, model documentation trails behind the software process because it is created manually, most of this time is spent on formatting. As a result, lack of model documentation or up-to date documentation causes a lot of pain for OEM’s and Tier 1 suppliers.