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The environmental issues confronting the automotive industry are legion at a time when the industry has not been in the best position to respond. Concerns have been raised that the industry needs to be producing “green mobility products” without definition, specificity, or expression of customer need. Business infrastructure and the regulatory landscapes are uncertain, but likely to be restrictive for the automotive sector, especially with regard to the environment and green issues. Actions the automotive industry could consider include: develop a common dictionary of terms related to “green mobility products”; address the issues affecting the industry before regulations are imposed; make the Mobility Sector part of the solution; focus on being environmentally responsive, cost-saving, and time-sensitive; and assure that the Mobility Sector is recognized as a leader for new, green technology.

Due to the multitude of external design constraints, such as increasing fuel economy standards, and the increasing number of global vehicle programs, developers of automotive transmission controls have had to cope with increasing levels of system complexity while at the same time being forced by the marketplace to improve system quality, reduce development costs, and improve time to market. General Motors Powertrain (GMPT) chose to meet these challenges through General Motors Company's Road-to-Lab-to-Math (RLM) strategy, particularly the Math-based method of a virtual vehicle simulation environment called System Simulation. The use of System Simulation to develop transmission control algorithms has enabled GMPT to improve product quality and reduce development times and costs associated with the dependence on physical prototypes. Additionally, System Simulation has facilitated the reuse of GMPT controls development assets, improving overall controls development efficiency.

As advanced battery systems become a standard choice for mainstream production vehicle portfolios, comprehensive battery system validation plans are essential to ensure that the battery performance, reliability, and durability targets are met prior to vehicle integration. (Note: Safety and Abuse testing are outside of the scope of this paper.) The validation plan for the Chevrolet Volt Rechargeable_Energy Storage System (RESS), the first lithium-ion battery pack designed and manufactured by General Motors (GM), was developed using a functional silo approach based on the battery design requirements documentation. While the Chevrolet Volt was the lead program at General Motors to use this validation plan development approach, other GM programs with different battery system mounting locations and cooling techniques are now using this method.

GM has recently developed two kinds of vehicle electrification architectures. First is VOLTec, a heavy electrification architecture, and second is eAssist, a light electrification architecture. An overview, of IGBT power modules & inverters used in VOLTec and eAssist, is presented. Alternative power modules from few cooperative suppliers are also described in a benchmarking study using key metrics. Inverter test set up, procedure and instrumentation used in GM Power Electronics Development Lab, Milford are described. GM electrification journey depends on Power Electronics lab' passive test benches; double pulse tester, inductive resistive load bench and active emulator test cell without electric machines. Such test benches are preferred before dyne test cells are used for inverter software/hardware integration and motor durability tests cycles. Specific test results are presented.

The main objective of this work is to demonstrate the merits of the Adjoint method to provide comprehensive information for shape sensitivities and design directions to achieve low drag vehicle shapes. The adjoint method is applied to a simple 2D airfoil and a 3D vehicle shape. The discrete Adjoint equations in the flow solvers are used to investigate further potential shape improvements of the low drag vehicle shapes. The low drag vehicle used in this study was designed earlier using the conventional approach (i.e., extensive use of wind tunnel testing). The goal is to use the already low drag vehicle shape and reduce its drag even further using the adjoint methodology without using the time-consuming and the high cost of wind tunnel testing. In addition, the present study is intended to compare the results with the other computational techniques such as surface pressure gradients method.

This work is to propose a new Iterative Learning Observer (ILO)-based strategy for State Of Charge (SOC) estimation. The ILO is able to estimate the SOC in real time while identifying modeling errors and/or disturbances at the same time. An Electrical-Circuit Model (ECM) is adopted to characterize the Lithium-ion battery behavior. The ILO is designed based on this ECM and the stability is proved. Several experiments are conducted and the collected data is used to extract ECM parameters. The effectiveness of the estimated SOCs via ILO is verified by the experimental results. This implies that the ILO-based SOC determination scheme is effective to identify the SOC in real time.

The focus of this study is to validate the predictive capability of a recently developed physiology based thermal comfort modeling tool in a realistic thermal environment of a vehicle passenger compartment. Human subject test data for thermal sensation and comfort was obtained in a climatic wind tunnel for a cross-over vehicle in a relatively warm thermal environment including solar load. A CFD/thermal model that simulates the vehicle operating conditions in the tunnel, is used to provide the necessary inputs required by the stand-alone thermal comfort tool. Comparison of the local and the overall thermal sensation and comfort levels between the human subject test and the tool's predictions shows a reasonably good agreement. The next step is to use this modeling technique in designing and developing energy-efficient HVAC systems without compromising thermal comfort of the vehicle occupants.

This study evaluates utilizing an accelerated test method that correlates customer interaction with a vehicle seat where bagginess and wrinkling is produced. The evaluation includes correlation from warranty returns as well as test vehicle results for test verification. Consumer metrics will be discussed within this paper with respect to potential application of this test method, including but not limited to JD Power ratings. The intent of the test method is to aid in establishing appropriate design parameters of the seat trim covers and to incorporate appropriate design measures such as tie downs and lamination. This test procedure was utilized in a Design for Six Sigma (DFSS) project as an aid in optimizing seat parameters influencing trim cover performance using a Design of Experiment approach.

Purpose - This research aimed to investigate the process of lean manufacturing implementation in automotive industry in China in order to identify the critical success factors. Design/methodology/approach - A review of relevant literature is used to identify potential critical success factors for lean manufacturing implementations. The research had targeted lean-manufacturing management, practitioners, process users, and consultants working in automotive industry in China. Data were collected with an electronic survey which included 20 close ended questions, each measured by using five-point scale, Out of total 200 questionnaire distributed, 80 useable responses were received resulting in 40 % response rate. A judgmental sampling technique had been selected. Both descriptive and inferential statistics had been used to analyze this data.

The present paper describes the results of a research project aimed at studying the impact of nozzle flow number on a Euro5 automotive diesel engine, featuring Closed-Loop Combustion Control. In order to optimize the trade-offs between fuel economy, combustion noise, emissions and power density for the next generation diesel engines, general trend among OEMs is lowering nozzle flow number and, as a consequence, nozzle hole size. In this context, three nozzle configurations have been characterized on a 2.0L Euro5 Common Rail Diesel engine, coupling experimental activities performed on multi-cylinder and optical single cylinder engines to analysis on spray bomb and injector test rigs. More in detail, this paper deeply describes the investigation carried out on the multi-cylinder engine, specifically devoted to the combustion evolution and engine performance analysis, varying the injector flow number.

This paper investigates changes in fuel economy of a mid-size sedan at various engine cooling fan power levels and front grille opening areas. A full vehicle model was built using MATLAB Simulink to calculate the fuel economy (MPG). The model utilized inputs from aerodynamic wind tunnel testing as well as FTP and MVEG dynamometer tests results. Simulation and testing was carried out at three front opening areas and three engine cooling fan power levels. The results provide a guideline for optimizing the front grille opening vs. engine cooling fan power combination at various driving conditions.

The New Car Assessment Program (NCAP), introduced in 1979 by the U.S. National Highway Traffic Safety Administration, is a vehicle safety rating system that conducts crash test and provides motoring consumers with an assessment of the safety performance of new cars. Similar programs were then developed around the world, initially for Europe (EuroNCAP), Australia (ANCAP), Japan (JNCAP), China (CNCAP) and Korea (KNCAP). NCAP most recently reached Latin America (LatinNCAP) and Southeast Asia (AseanNCAP). Although the roots are similar, many NCAP programs have significant differences on the test procedures and rating schemes. This paper is a comparative analysis of the recent NCAP protocols to highlight the most important technical differences.

Chrysler, Ford, General Motors, the U.S. Environmental Protection Agency (EPA) and the California Air Resources Board (CARB) have collaborated over the past two years to develop an efficiency test for mobile air conditioner (MAC) systems. Because the effect of efficiency differences between different MAC systems and different technologies is relatively small compared to overall vehicle fuel consumption, quantifying these differences has been challenging. The objective of this program was to develop a single dynamic test procedure that is capable of discerning small efficiency differences, and is generally representative of mobile air conditioner usage in the United States. The test was designed to be conducted in existing test facilities, using existing equipment, and within a sufficiently short time to fit standard test facility scheduling. Representative ambient climate conditions for the U.S. were chosen, as well as other test parameters, and a solar load was included.

The fifth generation of General Motor's “Small Block” 90-degree V engine family has been developed with a totally new combustion system. This system employs direct fuel injection (DI) and carefully architected in-cylinder flow field development in order to significantly improve all aspects of combustion system performance. Efficiency improvements stem from increased compression ratio, greatly improved dilution tolerance, and excellent knock resistance. The asymmetric, 2-valve (2V) layout of the “Small Block” engine presented unique challenges in developing the combustion system, but also offered unusual opportunities for an elegant solution while retaining the traditional “Small Block” attributes of packaging efficiency and power density.

Rubber isolators and bushings are very important components for vehicle performance. However, one often finds it is difficult to get the dynamic properties to be readily used in CAE analysis, either from suppliers or from OEM's own test labs. In this paper, the author provides an analytical method to obtain the dynamic stiffness of an exhaust isolator, using ABAQUS and iSight, with tested or targeted isolator static stiffness information. The analysis contains two steps. The first step is to select the (rubber/EPDM) material properties for the FE isolator model by matching the static stiffness with either the targeted spring rate (linear or nonlinear) or the (tested) load / deflection curve. The second step is to perform dynamic analysis on the statically “validated” FE isolator model to obtain its dynamic properties.