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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.

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.

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.

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.

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.

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.

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.

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.

Robust Engineering techniques developed by Taguchi have traditionally applied to the optimization of engineering designs. Robust Engineering methods also may be applied to software testing of ECU algorithms. The net result is an approach capable of improving the software algorithm in one of two ways. First the approach can identify the range of areas which prove problematic to the software such that a robust solution may be developed. Conversely, the approach can be used as a general strategy to verify that the software is robust over the range of inputs tested. The robust engineering methods applied to software testing utilize orthogonal array experiments to test software over a range of inputs. The actual software trials are best performed in the simulation environment and also via automated test hardware in the loop configurations in realtime. This paper outlines a process for applying Robust Engineering methods to software testing.

A new optimal control strategy for dealing with braking actuator failures in a vehicle equipped with a brake-by-wire and steer-by- wire system is described. The main objective of the control algorithm during the failure mode is to redistribute the control tasks to the functioning actuators, so that the vehicle performance remains as close as possible to the desired performance in spite of a failure. The desired motion of the vehicle in the yaw plane is determined using driver steering and braking inputs along with vehicle speed. For the purpose of synthesizing the control algorithm, a non-linear vehicle model is developed, which describes the vehicle dynamics in the yaw plane in both linear and non-linear ranges of handling. A control allocation algorithm determines the control inputs that minimize the difference between the desired and actual vehicle motions, while satisfying all actuator constraints.

In this paper a method of mitigating the consequences of potential brake actuator failure in vehicles with brake-by-wire (BBW) and possibly with steer-by-wire (SBW) systems is described. The proposed control algorithm is based on rules derived from general principles of vehicle dynamics. When a failure of one actuator is detected, the algorithm redistributes the braking forces among the remaining actuators in such a way that the desired deceleration of vehicle is followed as closely as possible, while the magnitude and the rate of change of the yaw moment caused by asymmetric braking are properly managed. When vehicle is equipped with BBW system only, or when the desired deceleration can be obtained by redistributing of braking forces, without generating an undesired yaw moment, no steering correction is used. Otherwise, a combination of brake force redistribution and steering correction (to counter the yaw moment generated by non-symmetric braking) is applied.

Electro-mechanical brakes (EMBs) are emerging as a new approach to enhance brake system features as well as braking performance. This paper takes a fresh look at the switched reluctance (SR) drive as a possible prime mover technology for EMB applications. The switched reluctance motor has attractive potential, in view of its robustness, dynamic bandwidth and fault tolerance. An overall assessment of the approach is made based on bench performance of a prototype EMB caliper with an SR drive executing typical braking patterns. It is shown that the SR motor can provide the required overall brake actuator performance. Various implementation options are examined to lower cost, with particular focus on electronic design, control algorithms and motor position sensing.

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.