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Electrification is the well-accepted solution to address carbon emissions and modernize vehicle controls. Batteries play a critical in the journey of electrification and modernization with battery voltage prediction as the foundation for safe and efficient operation. Due to its strong dependency on prior information, battery voltage was estimated with recurrent neural network methods in the recent literatures exploring a variety of deep learning techniques to estimate battery behaviors. In these studies, standard recurrent neural networks, gated recurrent units, and long-short term memory are popular neural network architectures under review. However, in most cases, each neural network architecture is individually assessed and therefore the knowledge about comparative study among three neural network architecture is limited. In addition, many literatures only studied either the dynamic voltage response or the voltage relaxation.

A flexible, easily configuration data acquisition system was designed and built for detailed studies of the steady state and dynamic properties of lean NOx traps for an engine dynamometer environment. The system is based on the industry standard VXI backplane. The overriding design philosophy was to design and develop a data acquisition system that was user friendly and could be operated easily by engine laboratory technicians, as well as by test engineers. The primary requirements guiding the design were the following: (1) the ability easily to configure, save, recall, modify, and print test configurations. (2) The ability to configure the gain, channel name, and engineering units for each analog channel. (3) The ability to trigger from one analog input channel. (4) A provision for numeric auto-incrementing of data file names. (5) The ability to save data in Excel™ compatible ASCII format. (6) The utilization of off-the shelf VXI hardware.

Although there was a safety awareness from the earliest days of the automobile, systematic approaches to designing for safety became more widespread after 1950 when large numbers of vehicles came into use in both the United States and Europe, and governments in both continents undertook a widespread highway development. Industry response to safety objectives and also to government regulation has produced a large number of safety enhancing engineering developments, including radial tires, disc brakes, anti-lock brakes, improved vehicle lighting systems, better highway sign support poles, padded instrument panels, better windshield retention systems, collapsible hood structures, accident sensitive fuel pump shut-off valves, and other items. A significant development was the design of the energy absorbing front structures.

A hybrid approach to predict road-induced loads in vehicle structures is presented. The technique involves full vehicle dynamic simulation using measured wheel forces, absolute wheel vertical displacements, and steering angle as input. The wheel vertical displacement is derived from the measured wheel acceleration. This approach avoids the use of tire-road interface modeling. It also improves the conventional loads measuring process with minimum instrumentation and data acquisition. Existing load data from a test vehicle is used to validate this approach. Computed component loads show good agreement with measurements.

A Microcomputer Based Eight Channel Data Acquisition System has been developed for customer correlation and routine vehicle field testing applications. The eight channel system includes a self-contained signal conditioning system designed for a variety of transducer types and data frequency requirements. Calibration, signal gain, and channel zero offset adjustments can be performed under software control. The microcomputer system is based on a Motorola M6800 microprocessor and a non-volatile core memory module. The paper describes the design, development, field performance, and data processing characteristics of the system and presents specific automotive applications and field test results.

A microcomputer-based, multichannel data acquisition system has been developed to acquire high frequency transient information typified by, but not limited to, automotive vehicle crash test applications. The system, which has been designed to be mounted on the test vehicle during a vehicle crash, will accommodate up to 240 channels. Each channel is comprised of a stand-alone microcomputer, memory for data storage, signal conditioning for piezoresistive transducers, automatic calibration and zero offsets, and programmable gain amplifier. The microcomputer is based upon a Motorola 6801/68701 microcomputer. The paper describes the design, development, and data processing characteristics of the prototype system.

A portable in-vehicle NVH data acquisition and analysis system is required to support the product development timing necessary to be competitive in today's automotive market. The components of such a system should include rugged hardware and software to support NVH data acquisition and analysis for frequently performed tests. The system should be easy for the vehicle development engineers to operate while producing results with a high confidence level. Once the data has been measured and analyzed, the system should support automated reporting and databasing of the results. The availability of such a system would make it easy for the vehicle development engineers to perform standardized tests with standardized analysis and reporting. Such a system has been successfully developed at Ford Motor Company.

New vehicle control algorithms are needed to meet future emissions and fuel economy mandates that are quite likely to require a measurement of ambient specific humidity (SH). Current practice is to obtain the SH by measurement of relative humidity (RH), temperature and barometric pressure with physical sensors, and then to estimate the SH using a fit equation. In this paper a novel approach is described: a system of neural networks trained to estimate the SH using data that already exists on the vehicle bus. The neural network system, which is referred to as a virtual SH sensor, incorporates information from the global navigation satellite system such as longitude, latitude, time and date, and from the vehicle climate control system such as temperature and barometric pressure, and outputs an estimate of SH. The conclusion of this preliminary study is that neural networks have the potential of being used as a virtual sensor for estimating ambient and intake manifold's SH.

About 10 years ago in the US, an automotive OEM consortium formed the Oxygenated Fuels Task Force which in turn created the SAE Cooperative Research Project Group 2 to develop a simple rational method for qualifying materials. At that time the focus was Methanol/Gasoline blends. This work resulted in SAE J1681, Gasoline/Methanol Mixtures for Materials Testing. Recently this document was rewritten to make it the single, worldwide, generic source for fuel system test fluids. The paper will describe the rationale for selecting the fuel surrogate fluids and why this new SAE standard should replace all existing test fuel or test fluid standards for fuel system materials testing.

The small-displacement direct-injection (DI) diesel engine is a prime candidate for future transportation needs because of its high thermal efficiency combined with near term production feasibility. Ford Motor Company and FEV Engine Technology, Inc. are working together with the US Department of Energy to develop a small displacement DI diesel engine that meets the key challenges of emissions, NVH, and power density. The targets for the engine are to meet ULEV emission standards while maintaining a best fuel consumption of 200g/kW-hr. The NVH performance goal is transparency with state-of-the-art, four-cylinder gasoline vehicles. Advanced features are required to meet the ambitious targets for this engine. Small-bore combustion systems enable the downsizing of the engine required for high fuel economy with the NVH advantages a four- cylinder has over a three-cylinder engine.

A vehicle's evaporative emission control system is continuously working, even when the vehicle is not running, due to generation of vapors from the fuel tank during ambient temperature variations. Diurnal temperature cycles cause the fuel tank to breathe the fuel vapor in and out, and thus the activated carbon canister is constantly loading and purging the hydrocarbon vapors. This paper discusses a study undertaken at Ford to evaluate the relationship between carbon canister condition and fuel tank vapor generation during diurnal cycles. The results of an extensive set of experiments are presented, and the data from these experiments are compared to the output of a fuel vapor system model also developed at Ford. Key parameters relating to the migration of hydrocarbons during the experimental conditions studied, including initial canister condition, canister volume, and canister geometry, are discussed.

This paper proposes a novel algorithm. This algorithm is called Self-Organizing Fuzzy Neural Network (SOFNN). SOFNN revolutionizes how researchers apply control theories, image/signal processing on control systems and other applications. In general, SOFNN is an identification technique that automatically initiates, builds and fine-tunes the required network parameters. SOFNN evaluates required structures without predefined parameters or expressions regarding systems. SOFNN sets out to learn and configure a system's characteristics. Self-constructing and self-tuning features enable SOFNN to handle complex, non-linear, and time-varying systems with higher accuracy, making systems identification easier. SOFNN constructs and fine-tunes the system parameter through two phases. The two phases are the construction and the parameter-tuning phase. The two phases run concurrently allowing SOFNN to identify systems on-line.

A highly adaptable fatigue testing computer system is presented for controlling single or multichannel test machines. The system imposes most common varieties of waveforms and also provides time synchronization between channels, such as in the case of variable amplitude biaxial load histories, and monitors various feedback signals for both data acquisition and alarm purposes. The program operates in a real-time Unix system as a separate stand-alone process. Communication with other users or the operator is done only through a reserved common block of shared memory. This feature allows control and monitoring of all tests over the computer network. A user can simply login remotely and check the test or start a data acquisition task from any workstation in the company, and then take the data files and analyze them on other computers. This paper describes the operation of the software, the methodology behind the hardware selection and the software structure.

A number of advancements have been made in the coulometric sulfur trace instrumental technique for the real-time measurement of engine oil economy. These advancements include modification of the coulometric cell to improve reliability and reproducibility. The instrument has been interfaced with a microcomputer for instrument control as well as data acquisition, storage, and analysis. Studies were undertaken which demonstrate sufficient sensitivity and linearity for determination of engine oil economy at levels better than 10,000 miles/quart. Applications to steady-state engine oil consumption mapping and to instantaneous oil consumption during transient engine cycling are described. These instruments are being produced by an outside supplier for use in various company locations in both the engine production and engine research environments.

Various methods are available to predict future cylinder air charge for improved air/fuel control. However, there can never be perfect prediction. This paper presents an algorithm to correct for imperfect cylinder charge prediction. This is done by expanding the air/fuel control boundary to include the catalyst, and correcting prediction errors as soon as possible using small corrective changes to later cylinder fuel inputs. The method was experimentally tested and showed improved air/fuel control as indicated by reduced variability of catalyst downstream air/fuel ratio. Additional vehicle testing showed potential to further reduce emissions.

This paper outlines an approach to highway transportation research which considers the interrelationship of the major subsystems. It describes the framework, the variables, surveillance techniques, and new vehicle instrumentation. A model is described which serves as the basis for field testing and subsequent mathematical analyses. Surveillance systems including instrumented vehicles, ground, aerial, and space platforms are required as components of a real-time system. A research project, designed to evaluate driver stress, is discussed and sample computer data are shown.

This case study presents a new automated production noise test for power steering pumps. The test included adaptive noise cancellation, and a neural network implementation. The result mapped the pump acceleration signature into an objective repeatable noise metric. The test algorithm was a distributed DSP architecture designed for real-time measurement and decision processing. It was implemented with no increase in test cycle time. It accomplished the correlation of in-vehicle power steering pump noise to it's vibration characteristics, and retrofitting of accelerometers in place of microphones for acceptance testing.

New instrumentation designs require extensive proveout in the vehicle environment. The sheer magnitude of information required to evaluate today’s microprocessor-based systems precludes manual data collection and analysis. A method of automating the data collection process through direct communication with the instrumentation module is discussed. A design for an automatic data collector, or datalogger, is presented.

Modern project management including brake testing includes the exchange of reliable results from different sources and different locations. The ISO TC22/SWG2-Brake Lining Committee established a task force led by Ford Motor Co. to determine and analyze root causes for variability during dynamometer brake performance testing. The overall goal was to provide guidelines on how to reduce variability and how to improve correlation between dynamometer and vehicle test results. This collaborative accuracy study used the ISO 26867 Friction behavior assessment for automotive brake systems. Future efforts of the ISO task force will address NVH and vehicle-level tests. This paper corresponds to the first two phases of the project regarding performance brake dynamometer testing and presents results, findings and conclusions regarding repeatability (within-lab) and reproducibility (between-labs) from different laboratories and different brake dynamometers.

This paper describes a new, open architecture data acquisition and calibration system, called CALVIN, developed for use in the automotive environment. The design is standards based and allows for growth with future technological breakthroughs. A major driver for the design has been the need to use commercial tools and capabilities. CALVIN, based on Windows95/NT/98 and with the careful partitioning of the hardware and software, has allowed the system to achieve the goals of de-coupling the vehicle calibration development process from the tool while allowing for the protection of user-specific intellectual property. The distributed nature of the design optimizes both the utilization cost and performance and thus, allows for an easy growth path as the environment and needs change. Automation of data acquistion and calibration is available through applications that are compatible with OLE/COM such as Visual Basic and C++.