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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.

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.

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.

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.

This paper presents a methodology to predict component and system reliability and durability. The methodology is illustrated with an electronic diesel fuel injector case study that integrates customer usage data, component failure distribution, system failure criteria, manufacturing variation, and variation in customer severity. Extension to the vehicle system level enables correlation between component and system requirements. Further, this analysis provides the basis to establish a knowledge-based test option for a success test validation program to demonstrate reliability.

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.

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.

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.

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.