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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.

This investigation was aimed at measuring the relative performance of two spray-guided, single-cylinder, spark-ignited direct-injected (SIDI) engine combustion system designs. The first utilizes an outwardly-opening poppet, piezo-actuated injector, and the second a conventional, solenoid operated, inwardly-opening multi-hole injector. The single-cylinder engine tests were limited to steady state, warmed-up conditions. The comparison showed that these two spray-guided combustion systems with two very different sprays had surprisingly close results and only differed in some details. Combustion stability and smoke emissions of the systems are comparable to each other over most of the load range. Over a simulated Federal Test Procedure (FTP) cycle, the multi-hole system had 15% lower hydrocarbon and 18% lower carbon monoxide emissions.

A simulation methodology is developed for the Constant Radius Constant Speed (CRCS) analysis to predict the ISO4138 [1] road test performance. The CRCS analysis can be used to predict the vehicle steady-state handling characteristics such as understeer, rear cornering compliance, and roll gradient, etc. The Yaw-Rate Control methodology is applied to replace the traditional driver-in-the-loop path-following approaches. Comparing to the path-following approaches, the proposed method is simpler to use, more efficient, accurate, and robust.

Wind tunnel testing of reduced-scale models is a valuable tool for aerodynamic development during the early stages of a new vehicle program, when basic design themes are being evaluated. Both full-and reduced-scale testing have been conducted for many years at the General Motors Aerodynamics Laboratory (GMAL), but with increased emphasis on aerodynamic drag reduction, it was necessary to identify additional facilities to provide increased test capacity. With vehicle development distributed among engineering teams around the world, it was also necessary to identify facilities local to those teams, to support their work. This paper describes a cooperative effort to determine the correlation among five wind tunnels: GMAL, the Glenn L.

This investigation utilizes a DFSS analysis approach to determine automatic transmission gear content required to minimize fuel consumption for various powertrain - vehicle systems. L18 and L27 inner arrays with automatic transmission design and shift pattern constraint parameters were varied to determine their relative influence on fuel consumption. An outer noise array consisting of two vehicles with various engines, final drive ratios and legislated emissions test cycles was used to make a robust transmission selection based on minimizing fuel consumption. The full details of the DFSS analysis method and assumptions are presented along with a detailed examination of the results. With respect to transmission design parameters, parasitic spinloss and gear mesh efficiency were found to be most important followed by the number of gears. The DFSS analysis further revealed that unique transmission design formulations are potentially required for widely varying engines.

The preform annealing process is a two-stage stamping method for shaping non age-hardenable (i.e. 5000 series) aluminum sheet panels in which the panel is heat treated in between the two steps to improve overall formability of the material. The intermediate annealing heat treatment eliminates the cold work accumulated in the material during the first draw. The process enables the ability to form more complex parts than a conventional aluminum stamping process. A demonstration of local annealing for this process was conducted to form a one-piece aluminum liftgate inner panel for a large sport utility vehicle using the steel product geometry without design concessions. In prior work, this process was demonstrated by placing the entire panel in a convection oven for several minutes to completely anneal the cold work.

Generally linear finite element analysis (FEA) is used to predict fatigue life of spot welded joints in a vehicle body structure. Therefore, the effect of plastic deformation at the vicinity of the spot welded joints is not included on fatigue prediction. This study introduces a simple technique to include the plastic deformation effect without performing elastic-plastic finite element analysis. The S-N curve obtained from fatigue test results is modified to consider this effect. Tensile strength test results of spot welded joint specimens were utilized to find the load range for FEA equivalent to the applied load range for fatigue tests. To demonstrate the proposed approach, fatigue test results of advanced high strength steels (AHSS) for lap-shear and coach peel specimens were used. Both the specimen types were tested at various constant amplitudes with the load ratios of R=0.1 and 0.3.

The ability to make accurate decisions concerning early body-in-white architectures is critical to an automaker since these decisions often have long term cost and weight impacts. We address this need with a methodology which can be used to assist in body architecture decisions using process-based technical cost modeling (TCM) as a filter to evaluate alternate designs. Despite the data limitations of early design concepts, TCM can be used to identify key trends for cost-effectiveness between design variants. A compact body-in-white architecture will be used as a case study to illustrate this technique. The baseline steel structure will be compared to several alternate aluminum intensive structures in the context of production volume.

Today many vehicles are being developed with advanced computing and sensing technologies. These new technologies have contributed in enhancing driving safety and convenience. As an example, the Adaptive Cruise Control (ACC) can automatically adjust the vehicle speed to driver's set speed and maintain the driver-requested headway distance to the lead vehicle. In this paper, we further consider the automatic control of speed according to the road attributes, e.g., the speed limit and curve of the road. Two new features, ‘speed limit follower’ and ‘curve speed control’ algorithms, are proposed in this paper. These new features communicate with the conventional ACC system and control the vehicle speed while traveling across different curved roads and speed limit zones. These new features were developed as an independent function, so they can be integrated with any other existing ACC systems.

ASIL decomposition is a method described in the ISO 26262 standard for the assignment of ASILs to redundant requirements. Although ASIL decomposition appears to have similar intent to the hardware fault tolerance concept of IEC 61508-2, ASIL decomposition is not intended to reduce ASIL assignments to hardware elements for random hardware failures, but instead focuses on functions and requirements in the context of systematic failures. Based on our participation in the development of the standard, the method has been applied in different ways in practice, not all of which are fully consistent with the intent of the standard. Two potential reasons that may result in the use of “modified” ASIL algebra include the need of OEMs to partition a system and specify subsystem requirements to suppliers and the need for designers to construct systems bottom up.

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.

Aerodynamic vehicle design improvements require flow simulation driven iterative shape changes. The 3-D flow field simulations (CFD analysis) are not explicitly descriptive in providing the direction for aerodynamic shape changes (reducing drag force or increasing the down-force). In recent times, aerodynamic shape optimization using the adjoint method has been gaining more attention in the automotive industry. The traditional DOE (Design of Experiment) optimization method based on the shape parameters requires a large number of CFD flow simulations for obtaining design sensitivities of these shape parameters. The large number of CFD flow simulations can be significantly reduced if the adjoint method is applied. The main purpose of the present study is to demonstrate and validate the adjoint method for vehicle aerodynamic shape improvements.

This paper presents some of the challenges and successful outcomes in developing the aerodynamic characteristics of the Chevrolet Volt, an electric vehicle with an extended-range capability. While the Volt's propulsion system doesn't directly affect its shape efficiency, it does make aerodynamics much more important than in traditional vehicles. Aerodynamic performance is the second largest contributor to electric range, behind vehicle mass. Therefore, it was critical to reduce aerodynamic drag as much as possible while maintaining the key styling cues from the original concept car. This presented a number of challenges during the development, such as evaluating drag due to underbody features, balancing aerodynamics with wind noise and cooling flow, and interfacing with other engineering requirements. These issues were resolved by spending hundreds of hours in the wind tunnel and running numerous Computational Fluid Dynamics (CFD) analyses.

In a math-based control algorithm design, model-based simulation and testing are very important as an integral part of design process. There are many advantages of using modeling and simulation in the algorithm design. In this paper, Algorithm-in-the-Loop and Hardware-in-the-Loop approaches are adopted for a transmission control algorithm development. A practical approach is introduced on how to test the control algorithms with a reliable plant (virtual engine, transmission, and vehicle) model in the closed-loop simulation. In using combination of open-loop and closed-loop simulations, various key behavior test cases are developed and documented for the success of control algorithms development. Secondly, the same test cases are reused and verified against the production codes, which are automatically generated from the math-based control algorithm models.

Response Surface Models are often used as a surrogate for expensive black-box functions during optimization to reduce computational cost. Often, the CAE analysis models are highly nonlinear and multi-modal. A response surface approximation of such analysis as a result is highly multi-modal; i.e. it contains multiple local optima. A gradient-based optimizer working with such a response surface will often converge to the nearest local optimum. There does not exist any method to guarantee a global optima for non-convex multi-modal functions. For such problems, we propose an efficient algorithm to find as many distinct local optima as possible. The proposed method is specifically designed to work in large dimensions (about 100 ∼ 1000 design variables and similar number of constraints) and can identify most of the locally optimal solutions in a reasonable amount of time.

An engineering approach was developed to extract the failure plastic strain, thinning failure strain, and major in plane failure strain for finite element simulation applications. This approach takes into account the failure strain dependency on the element size when element deletion scheme is invoked in the simulation of material fracture. Both localized necking fracture and tensile shear fracture can be predicted when appropriate elements and material models are used in LS-DYNA simulations. This leads to a more accurate prediction of fracture and tearing in the finite element simulation of vehicle structure and crash loading conditions.

An extruded Mg-Al-Mn (AM30) magnesium alloy was subjected to uniaxial compression along the extrusion direction (ED) and the extrusion radial direction (RaD) at 450 °C and different strain rates. The microstructure and texture of the AM30 alloy under different deformation conditions were examined. Texture evolution was characterized by electron backscatter diffraction (EBSD). The activity of different deformation modes including twinning were simulated using the visco-plastic self-consistent (VPSC) and the simplistic Sachs polycrystal plasticity models. The results show that the microstructure and the mechanical property of the Mg alloy strongly depend on the strain rate, with twinning activated at strain rates >0.5 s−1. Dynamic recrystallization and twinning interacted with each other and affected the final microstructure and mechanical property of the magnesium alloy.

The introduction of new safety critical features using software-intensive systems presents a growing challenge to hazard analysis and requirements development. These systems are rich in feature content and can interact with other vehicle systems in complex ways, making the early development of proper requirements critical. Catching potential problems as early as possible is essential because the cost increases exponentially the longer problems remain undetected. However, in practice these problems are often subtle and can remain undetected until integration, testing, production, or even later, when the cost of fixing them is the highest. In this paper, a new technique is demonstrated to perform a hazard analysis in parallel with system and requirements development. The proposed model-based technique begins during early development when design uncertainty is highest and is refined iteratively as development progresses to drive the requirements and necessary design features.

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.

Automotive seat comfort systems provide occupants with a choice to adjust the seat to individual preference, enhancing the customized comfort feel. Seat comfort systems such as massager, lumbar support bladders, seat cushion bolster bladders and seat back bolster bladders are increasingly adopted in automotive seats as customer demand for customizable seats is on the rise. Development of seat comfort systems is mainly driven by Tier 1 suppliers to an automotive original equipment manufacturer (OEM). The Automotive OEM must wait until the final seat prototype is ready with all the seat comfort systems packaged to evaluate the seat comfort performance. Computer Aided Engineering (CAE) Tools like CASIMIR provide detail dummies representing humans with tissues and muscles, allowing occupant seat comfort to be predicted virtually.