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Electric Power Assisted Steering (EPAS) is widely adopted in modern vehicles to reduce steering effort. It is probable that some EPAS systems will experience a shutdown due to reliability issues stemming from electrical and/or electronic components. In the event of EPAS failure, power assist becomes unavailable and the steering system reverts to a fully manual state, leading to excessive steering torque demands from the driver to maneuver the vehicle at lower speeds, i.e., under 30 mph. This situation has resulted in dozens of reported crashes and several OEM safety recalls in the past few years. Inspired by recent work which utilizes independent driving torque of in-wheel-motor vehicles to reduce steering torque, this paper proposes the use of Differential Braking Assisted Steering (DBAS) to alleviate steep increases in steering torque upon EPAS failure. DBAS requires software upgrades with minimal hardware modification to EPAS, which is preferable for a backup system.

Lane change events can be a source of traffic accidents; drivers can make improper lane changes for many reasons. In this paper we present a comprehensive study of a passive method of predicting lane changes based on three physiological signals: electrocardiogram (ECG), respiration signals, and galvanic skin response (GSR). Specifically, we discuss methods for feature selection, feature reduction, classification, and post processing techniques for reliable lane change prediction. Data were recorded for on-road driving for several drivers. Results show that the average accuracy of a single driver test was approx. 70%. It was greater than the accuracy for each cross-driver test. Also, prediction for younger drivers was better.

The Chevrolet Volt is an electric vehicle with extended-range that is capable of operation on battery power alone, and on engine power after depletion of the battery charge. First generation Chevrolet Volts were driven over half a billion miles in North America from October 2013 through September 2014, 74% of which were all-electric [1, 12]. For 2016, GM has developed the second-generation of the Volt vehicle and “Voltec” propulsion system. By significantly re-engineering the traction power inverter module (TPIM) for the second-generation Chevrolet Volt extended-range electric vehicle (EREV), we were able to meet all performance targets while maintaining extremely high reliability and environmental robustness. The power switch was re-designed to achieve efficiency targets and meet thermal challenges. A novel cooling approach enables high power density while maintaining a very high overall conversion efficiency.

Great efforts have been made to develop the ability to accurately and quickly predict the durability and reliability of vehicles in the early development stage, especially for welded joints, which are usually the weakest locations in a vehicle system. A reliable and validated life assessment method is needed to accurately predict how and where a welded part fails, while iterative testing is expensive and time consuming. Recently, structural stress methods based on nodal force/moment are becoming widely accepted in fatigue life assessment of welded structures. There are several variants of structural stress approaches available and two of the most popular methods being used in automotive industry are the Volvo method and the Verity method. Both methods are available in commercial software and some concepts and procedures related the nodal force/moment have already been included in several engineering codes.

An advanced variable valve actuation (VVA) system is characterized following end-of-life testing to enable fuel economy solutions for passenger car applications. The system consists of a switching roller finger follower (SRFF) combined with a dual feed hydraulic lash adjuster and an oil control valve that are integrated into a four cylinder gasoline engine. The SRFF provides discrete valve lift capability on the intake valves. The motivation for designing this type of VVA system is targeted to improve fuel economy by reducing the air pumping losses during part load engine operation. This paper addresses the durability of a SRFF for meeting passenger car durability requirements. Extensive durability tests were conducted for high speed, low speed, switching, and cold start operation. High engine speed test results show stable valvetrain dynamics above 7000 engine rpm. System wear requirements met end-of-life criteria for the switching, sliding, rolling and torsion spring interfaces.

Suspension design is influenced by many factors, especially by vehicle dynamics performance in ride, handling and durability. In the global automotive industry it is common to “customize” or tune suspension parameters so that a vehicle is more acceptable to a different customer base and in a different driving environment. This paper seeks to objectively quantify certain aspects of tuning via ride optimization, taking account of market differences in road surface spectral properties and loading conditions. A computationally efficient methodology for suspension optimization is developed using stochastic techniques. A small (B-class) vehicle is chosen for the study and the following main suspension parameters are selected for optimization - spring stiffness, damping rate and vertical tire stiffness. The road is characterized as a stationary random process, using scaling and shaping filters representative of comparable roads in India and the USA.

This study involves an application of Principal Component Analysis (PCA) conducted in support of a Design for Six Sigma (DFSS) project. Primary focus of the project is to optimize seat parameters that influence Low Speed Rear Impact (LSRI) whiplash performance. During the DFSS study, the project team identified a need to rank order critical design factors statistically and establish their contribution to LSRI performance. It is also required to develop a transfer function for the LSRI rating in terms of test response parameters that can be used for optimization. This statistical approach resulted in a reliable transfer function that can applied across all seat designs and enabled us to separate vital few parameters from several many.

This paper demonstrates the benefit of using simulation and robust optimization for the problem of balancing vehicle noise, vibration, and ride performance over road impacts. The psychophysics associated with perception of vehicle performance on an impact is complex because the occupants encounter both tactile and audible stimuli. Tactile impact vibration has multiple dimensions, such as impact hardness and memory shake. Audible impact sound also affects occupant perception of the vehicle quality. This paper uses multiple approaches to produce the similar, robust, optimized tuning strategies for impact performance. A Design for Six Sigma (DFSS) project was established to help identify a balanced, optimized solution. The CAE simulations were combined with software tools such as iSIGHT and internally developed Kriging software to identify response surfaces and find optimal tuning.

Under the initiative of the United States Council for Automotive Research LLC (USCAR§) Transmission Working Group, a collaborative effort was made with LuK USA LLC to study the influence of the friction interface parameters on the shudder durability of a wet launch clutch. A test bench was designed. Clutch configurations with different combinations of four friction materials (A, B, C and D), three groove patterns (waffle, radial and waffle–parallel) and two separator plate conditions (nitrided and non–nitrided) were considered. Considerable improvement in performance was seen by changing from CVT fluid* to DCT fluid*. A thermal analysis based on thermal model predictions and measurement correlations was conducted. Comparisons of clutch configurations with four and five friction plates were done. The waffle and radial groove pattern showed better heat transfer than the waffle–parallel groove pattern.

Under the initiative of the United States Council for Automotive Research LLC (USCAR§) Transmission Working Group, a collaborative effort was made with LuK USA LLC to study the influence of the friction interface parameters on the shudder durability of a wet launch clutch. Clutch configurations with different combinations of four friction materials (A, B, C and D), three groove patterns (waffle, radial and waffle-parallel) and two separator plate conditions (nitrided and non-nitrided) were considered. Durability testing consisted of a test profile, with 110 kJ energy per test cycle, developed earlier in this project. Materials A, B and C with nitrided separator plates reached the end of test criteria for the torque gradient and showed shudder. Materials B and C were more wear resistant as compared to materials A and D. The loss of friction coefficient (μ) was lower for materials B, C and D as compared to material A.

Adopting robust design principles is a proven methodology for increasing design reliability. General Motors Powertrain (GMPT) has incorporated robust design principles into their Signal Delivery Subsystem (SDSS) development process by moving traditional prototype manufacturing and test functions from hardware to software. This virtual manufacturing technique, where subsystems are built and tested using simulation software, increases the number of possible prototype iterations while simultaneously decreasing the time required to gather statistically meaningful test results. This paper describes how virtual manufacturing was developed using distributed computing.

Robust assessment using standardized signal-to-noise (SS/N) is a Design For Six Sigma (DFSS) methodology used to assess the mating quality of USCAR electrical connectors. When the insertion force vs. distance relationship is compared to a standard under varying environmental and system-related noise conditions, the ideal function is transformed into a linear relationship between actual and ideal force at the sample points acquired during the mating displacement. Since the ideal function used in the robust assessment of competing designs has a linear slope of 1 through the origin, the SS/N function used is of the form 10 log (1/σ2), also known as nominal-the-best type 2. Using this assessment methodology, designs are compared, with a higher SS/N indicating lower variation from the standard.

In an endeavor to improve upon historically subjective and hardware-based steering tuning development, a team was formed to find an optimal and objective solution using Design For Six Sigma (DFSS). The goal was to determine the best valve assembly design within a hydraulic power-steering assist system to yield improved steering effort and feel robustness for all vehicle models in a future truck program. The methodology utilized was not only multifaceted with several Design of Experiments (DOEs), but also took advantage of a CAE-based approach leveraging modeling capabilities in ADAMS for simulating full-vehicle, On-Center Handling behavior. The team investigated thirteen control factors to determine which minimized a realistic, compounded noise strategy while also considering the ideal steering effort function (SEF) desired by the customer. In the end, it was found that response-dependent variability dominated the physics of our valve assembly design concept.

General Motors' vehicles are designed with an engine immobilizer theft deterrent system. An engine immobilizer theft deterrent system only allows starting of the vehicle engine after assuring the key is the correct key. The communication link from the vehicle to the key is a critical interface for the starting of the engine. This communication link must be reliable. The vehicle theft deterrent system's ability to communicate between the vehicle and transponder in the key is measured by the coupling factor. There are a number of physical interfaces that affect the coupling factor. The focus of this work is to understand the physics and critical design parameters involved in achieving optimal coupling factor to improve the first time quality in future designs. Achieving this objective will lead to designs robust to variances in material and packaging design and result in less testing. The process used in the past on these systems was the Design-Test-Fix approach.

The Hood ajar sensing system provides customer feedback regarding the latch positional state of hood. If the sensing system is not robust to variation due to manufacturing, thermal conditions, and assembly, diagnostic failures can result. Executing various elements of the design for six sigma process can reduce the potential for diagnostic failures. This paper presents a method for achieving quality improvements by developing transfer functions, and using them for sensitivity and variance analysis. Control parameters were optimized to minimize non-conformal situations in the presence of various noise conditions.

Existing methods for design optimization under uncertainty assume that a high level of information is available, typically in the form of data. In reality, however, insufficient data prevents correct inference of probability distributions, membership functions, or interval ranges. In this article we use an engine design example to show that optimal design decisions and reliability estimations depend strongly on uncertainty characterization. We contrast the reliability-based optimal designs to the ones obtained using worst-case optimization, and ask the question of how to obtain non-conservative designs with incomplete uncertainty information. We propose an answer to this question through the use of Bayesian statistics. We estimate the truck's engine reliability based only on available samples, and demonstrate that the accuracy of our estimates increases as more samples become available.

The goal was to automate the entire analytical process of structural fatigue life variation assessment with respect to the variations associated with the geometry such as thickness, material properties and loading conditions. Consequently, the structural reliability is evaluated systematically. This process automation has been realized by using an internally developed software package called Structural Fatigue/Reliability Sensitivity II (i.e. FRS II). The package is a bundle of MSC/Nastran, nCode, iSIGHT, and internally developed program scripts.

Maximizing customer satisfaction is one key factor for marketing success. It is crucial to have engineering specifications reflecting customer expectations. This paper describes the strategy and methodologies used to generate optimum engineering specification in a case study. This study is part of the DFSS project, which focused on electrical delay time prior to engine crank.

4-Post durability test simulations using a nonlinear FEA model have been executed by engineers responsible for structural durability performance and validation. An integrated Body and Chassis, full FEA model has been used. All components of the test load input were screened and only the most damaging events were incorporated in the simulation. These events included the Potholes, Belgian Block Tracks, Chatter Bump Stops, Twist Ditches, and Driveway Ramps. The CAE technology Virtual Proving Ground (eta/VPG®*) was used to model the full system and the 4-Post test fixtures. The nonlinear dynamic FE solver LS-DYNA** was used in this analysis. The fatigue damage of each selected event was calculated separately and then added together according to the test schedule. Due to the lack of stress/strain information from hardware test, only the analyzed fatigue damage results of the baseline model were scaled to correlate with physical test data.

A Benchmarking technique known as Data Envelopment Analysis (DEA) will be discussed as a jumpstart technique to put energy back into a company's Six Sigma program. A hypothetical example of benchmarking the production lines of a manufacturing company will be discussed using Six Sigma quality measures. Typical DEA software output will be discussed.