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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.

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 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.

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.

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.

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.

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 requirement of many modern safety-critical automotive applications is to provide failsafe operation. Several analysis methods are available to help confirm that automotive safety-critical systems are designed properly and operate as intended to prevent potential hazards from occurring in the event of system failures. One element of safety-critical system design is to help verify that the software and microcontroller are operating correctly. The task of incorporating failsafe capability within an embedded microcontroller design may be achieved via hardware or software techniques. This paper surveys software failsafe techniques that are available for application within a microcontroller design suitable for use with safety-critical automotive systems. Safety analysis techniques are discussed in terms of how to identify adequate failsafe coverage.

This paper will address the electronic development in the wireless industry and compare it to the electronic development in the automotive industry. The wireless industry is characterized by rapid, dramatic high tech changes with a less than two-year cycle time and an equivalent life cycle. The automotive electronics industry is working toward reducing the typical 2 to 3 year development cycle down 1 to 2 years but with a life cycle of 10 years or more. In addition to realizing the electronic development benefits seen in the wireless industry, the automotive industry places significantly more emphasis on the quality and reliability aspects of their designs as many of them are targeted toward, or interface with, safety critical applications. One of the lessons learned from the wireless industry is the development process; where the hardware selection process can be accomplished in a virtual environment in conjunction with concurrent software development.

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.

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.

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.

A new single-brick Ba + alkali metals NOx-Trap catalyst has been developed to replace a two-brick NOx-Trap system containing a downstream three-way catalyst. Major development efforts include: 1) platinum group metals selection for higher HC oxidation with potassium-containing washcoat, 2) alumina and ceria selection, and Rh architecture design for more efficient NOx reduction and 3) NiO to suppress H2S odor. Mitsubishi Motors' 1.8L GDI™ with this Delphi new NOx-Trap catalyst with H2S control achieves J-LEV standard with less cost and lower backpressure compared to the previous model. It is further discovered that incorporation of NiO into the NOx-Trap washcoat is effective for H2S control during sulfur purge but has a negative impact on thermal durability and sulfur resistance. Further study to improve this trade-off has been made and preliminary results of an advanced washcoat design are presented in this paper. Details will be reported in a future publication.

Among the performance concerns in brake design, drag and fluid displacement are getting more attention in the requirement definition. High drag not only affects fuel efficiency and lining life, it is also a contributing factor to rotor thickness variation and brake pulsation. In this paper, a system approach to drag performance of a disc brake caliper is presented. A one-dimensional simulation model, which considers all the significant factors, including lining stiffness and hysteresis, housing stiffness, seal/groove characteristic, and stick-slide behavior between the seal and piston, is developed to capture the interactive impact of each parameter to caliper drag performance. The system model is validated with experimental measurements for caliper fluid displacement and piston retraction. A parameter study is then conducted to investigate the component interactive impact to the drag performance.