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This paper proposes a new mixing-controlled, low temperature combustion (LTC) approach for high-speed direct injection (HSDI) diesel engines. The purpose of this approach is to avoid the excessively high pressure-rise rate (PRR) of premixed, kinetics-controlled LTC and to enable the low nitrogen oxides (NOx) combustion to operate over the wide speed and load range of the engine. To address the soot/noise trade-off at high load LTC operating conditions, the pressure modulated multiple-injection coupled with swirl control was applied. This injection strategy enables the injection of high pressure (HP) main spray into the local high temperature region of the already burning low pressure (LP) pilot spray injected from the neighboring injection hole. By employing this injection strategy, the equivalence ratio (φ) distribution of mixture is drastically varied during main combustion processes.

An operational scheme with fuel-lean and exhaust gas dilution in spark-ignited engines increases thermal efficiency and decreases NOx emission, while these operations inherently induce combustion instability and thus large cycle-to-cycle variation in engine. In order to stabilize combustion variations, the development of an advanced ignition system is becoming critical. To quantify the impact of spark-ignition discharge, ignitability tests were conducted in an optically accessible combustion vessel to characterize the flame kernel development of lean methane-air mixture with CO₂ simulating exhaust diluent. A shrouded fan was used to generate turbulence in the vicinity of J-gap spark plug and a Variable Output Ignition System (VOIS) capable of producing a varied set of spark discharge patterns was developed and used as an ignition source. The main feature of the VOIS is to vary the secondary current during glow discharge including naturally decaying and truncated with multiple strikes.

Computer programs and models are playing an increasing role in simulating vehicle crashworthiness, dynamic, and fuel efficiency. To maximize the effectiveness of these models, the validity and predictive capabilities of these models need to be assessed quantitatively. For a successful implementation of Computer Aided Engineering (CAE) models as an integrated part of the current vehicle development process, it is necessary to develop objective validation metric that has the desirable metric properties to quantify the discrepancy between multiple tests and simulation results. However, most of the outputs of dynamic systems are multiple functional responses, such as time history series. This calls for the development of an objective metric that can evaluate the differences of the multiple time histories as well as the key features under uncertainty.

A copula-based approach for model bias characterization was previously proposed [18] aiming at improving prediction accuracy compared to other model characterization approaches such as regression and Gaussian Process. This paper proposes an adaptive copula-based approach for model bias identification to enhance the available methodology. The main idea is to use cluster analysis to preprocess data, then apply the copula-based approach using information from each cluster. The final prediction accumulates predictions obtained from each cluster. Two case studies will be used to demonstrate the superiority of the adaptive copula-based approach over its predecessor.

To date, model validation metric is prominently designed for non-dynamic model responses. Though metrics for dynamic responses are also available, they are specifically designed for the vehicle impact application and uncertainties are not considered in the metric. This paper proposes the validation metric for general dynamic system responses under uncertainty. The metric makes use of the popular U-pooling approach and extends it for dynamic responses. Furthermore, shape deviation metric was proposed to be included in the validation metric with the capability of considering multiple dynamic test data. One vehicle impact model is presented to demonstrate the proposed validation metric.

Simulation based design optimization has become the common practice in automotive product development. Increasing computer models are developed to simulate various dynamic systems. Before applying these models for product development, model validation needs to be conducted to assess their validity. In model validation, for the purpose of obtaining results successfully, it is vital to select or develop appropriate metrics for specific applications. For dynamic systems, one of the key obstacles of model validation is that most of the responses are functional, such as time history curves. This calls for the development of a metric that can evaluate the differences in terms of phase shift, magnitude and shape, which requires information from both time and frequency domain. And by representing time histories in frequency domain, more intuitive information can be obtained, such as magnitude-frequency and phase-frequency characteristics.

Design optimization methods are commonly used for weight reduction subjecting to multiple constraints in automotive industry. One of the major challenges remained is to deal with a large number of design variables for large-scale design optimization problems effectively. In this paper, a new approach based on fuzzy rough set is proposed to address this issue. The concept of rough set theory is to deal with redundant information and seek for a reduced design variable set. The proposed method first exploits fuzzy rough set to screen out the insignificant or redundant design variables with regard to the output functions, then uses the reduced design variable set for design optimization. A vehicle body structure is used to demonstrate the effectiveness of the proposed method and compare with a traditional weighted sensitivity based main effect approach.

One of the major challenges in multiobjective, multidisciplinary design optimization (MDO) is the long computational time required in evaluating the new designs' performances. To shorten the cycle time of product design, a data mining-based strategy is developed to improve the efficiency of heuristic optimization algorithms. Based on the historical information of the optimization process, clustering and classification techniques are employed to identify and eliminate the low quality and repetitive designs before operating the time-consuming design evaluations. The proposed method improves design performances within the same computation budget. Two case studies, one mathematical benchmark problem and one vehicle side impact design problem, are conducted as demonstration.

Ultrasonic fatigue tests (testing frequency around 20 kHz) have been conducted on four different cast aluminum alloys each with a distinct composition, heat treatment, and microstructure. Tests were performed in dry air, laboratory air and submerged in water. For some alloys, the ultrasonic fatigue lives were dramatically affected by the environment humidity. The effects of different factors like material composition, yield strength, secondary dendrite arm spacing and porosity were investigated; it was concluded that the material strength may be the key factor influencing the environmental humidity effect in ultrasonic fatigue testing. Further investigation on the effect of chemical composition, especially copper content, is needed.

Current legform impact test methods using the FlexPLI have been developed to protect pedestrians from lower limb injuries in collisions with low-bumper vehicles. For this type of vehicles, the influence of the upper body on the bending load generated in the lower limb is compensated by setting the impact height of the FlexPLI 50 mm above that of pedestrians. However, neither the effectiveness of the compensation method of the FlexPLI nor the influence of the upper body on the bending load generated in the lower limb of a pedestrian has been clarified with high-bumper vehicles. In this study, therefore, two computer simulation analyses were conducted in order to analyze: (1) The influence of the upper body on the bending load generated in the lower limb of a pedestrian when impacted by high-bumper vehicles and (2) The effectiveness of the compensation method for the lack of the upper body by increasing impact height of the FlexPLI for high-bumper vehicles.

For applying ISO 26262 to motorcycles, controllability classification (C class evaluation) by expert riders is considered an appropriate technique. Expert riders have evaluated commercial product development for years and can appropriately conduct vehicle tests while observing safety restrictions (such as avoiding the risk of falling). Moreover, expert riders can ride safely and can stably evaluate motorcycle performance even if the test conditions are close to the limits of vehicle performance. This study aims to construct a motorcycle C class evaluation method based on an expert rider’s subjective evaluation. On the premise that expert riders can rate the C class, we improved a test procedure that used a subjective evaluation sheet as the concrete C class evaluation method for an actual hazardous event.

To investigate the events that could arise when fighting fires in vehicles with carbon fiber reinforced plastic (CFRP) hydrogen storage cylinders, we conducted experiments to examine whether a hydrogen jet diffusion flame caused by activation of the pressure relief device (PRD) can be extinguished and how spraying water influences the cylinder and PRD. The experiments clarified that the hydrogen jet flame cannot be extinguished easily with water or dry powder extinguishers and that spraying water during activation of the PRD may result in closure of the PRD, but is useful for maintaining the strength of CFRP composite cylinders for vehicles.

The localized fire test provided in the Global Technical Regulation for Hydrogen Fuel Cell Vehicles gives two separate test methods: the ‘generic installation test - Method 1′ and the ‘specific vehicle installation test - Method 2′. Vehicle manufacturers are required to apply either of the two methods. Focused on Method 2, the present study was conducted to determine the characteristics and validity of Method 2. Test results under identical burner flame temperature conditions and the effects of cylinder protection covers made of different materials were compared between Method 1 and Method 2.

The SAE Fuel Cell Vehicle (FCV) Safety Working Group has been addressing FCV safety for over 9 years. The initial document, SAE J2578, was published in 2002. SAE J2578 has been valuable as a Recommended Practice for FCV development with regard to the identification of hazards and the definition of countermeasures to mitigate these hazards such that FCVs can be operated in the same manner as conventional gasoline internal combustion engine (ICE)-powered vehicles. SAE J2578 is currently being revised so that it will continue to be relevant as FCV development moves forward. For example, test methods were refined to verify the acceptability of hydrogen discharges when parking in residential garages and commercial structures and after crash tests prescribed by government regulation, and electrical requirements were updated to reflect the complexities of modern electrical circuits which interconnect both AC and DC circuits to improve efficiency and reduce cost.

The SAE FCV Safety Working Group has been addressing fuel cell vehicle (FCV) safety for over 8 years. The initial document, SAE J2578, was published in 2002. SAE J2578 has been valuable to FCV development with regard to the identification of hazards and the definition of countermeasures to mitigate these hazards such that FCVs can be operated in the same manner as conventional gasoline internal combustion engine (ICE)-powered vehicles. J2578 is currently being updated to clarify and update requirements so that it will continue to be relevant and useful in the future. An update to SAE J1766 for post-crash electrical safety was also published to reflect unique aspects of FCVs and to harmonize electrical requirements with international standards. In addition to revising SAE J2578 and J1766, the Working Group is also developing a new Technical Information Report (TIR) for vehicular hydrogen systems (SAE J2579).

This study demonstrates the use of pressure sensing technology to predict the crash severity of frontal impacts. It presents an investigation of the pressure change in the front structural elements (bumper, crush cans, rails) during crash events. A series of subsystem tests were conducted in the laboratory that represent a typical frontal crash development series and provided empirical data to support the analysis of the concept. The pressure signal energy at different sensor mounting locations was studied and design concepts were developed for amplifying the pressure signal. In addition, a pressure signal processing methodology was developed that relies on the analysis of the air flow behavior by normalizing and integrating the pressure changes. The processed signal from the pressure sensor is combined with the restraint control module (RCM) signals to define the crash severity, discriminate between the frontal crash modes and deploy the required restraint devices.

Gas Metal Arc Welding (GMAW) is widely employed for joining relatively thick sheet steels in automotive body-in-white structures and frames. The GMAW process is very flexible for various joint geometries and has relatively high welding speed. However, fatigue failures can occur at welded joints subjected to various types of loads. Thus, vehicle design engineers need to understand the fatigue characteristics of welded joints produced by GMAW. Currently, automotive structures employ various advanced high strength steels (AHSS) such as dual-phase (DP) and transformation-induced plasticity (TRIP) steels to produce lighter vehicle structures with improved safety performance and fuel economy, and reduced harmful emissions. Relatively thick gages of AHSS are commonly joined to conventional high strength steels and/or mild steels using GMAW in current body-in-white structures and frames.

Hydrogen concentration during combustion in a confined space with a ceiling was investigated. The results indicated that steady-state hydrogen concentration was highest at the ceiling surface for all hydrogen flow rates. When hydrogen concentration was 10-20%, weak flame propagation occurred at the ceiling surface, with the most easily burnable spots being dented areas such as seams, pores and creases on the ceiling surface. The unstable and limited nature of flame propagation at the ceiling surface was attributed to the relationship between temperature and hydrogen concentration in a confined space.

The r-value is a very important parameter in the forming simulations of high strength steels, especially for steels with prominent anisotropy. R-values for sheet steels conventionally measured by extensometers were found neither consistent nor accurate due to difficulties in measuring the width strain. In this study, the Digital Image Correlation (DIC) technique was applied to determine r-values in Longitudinal (L), Transverse (T) and Diagonal (D) directions for cold rolled DP980 GI, DP780 GI, DP600 GI and BH250 GI sheet steels. The r-values measured from DIC were validated by finite element analysis (FEA) of a uniaxial tensile test for BH250. The simulation results of the load-displacement for two plasticity models were compared to experimental data, with one being the isotropic yield (von-Mises) and the other being an anisotropic model (Hill-48) using the r-value measured from DIC.

High cycle fatigue tests at a constant positive mean stress have been performed on a Al-Si-Cu cast aluminum alloy. The Random Fatigue Limit (RFL) model was employed to fit the probabilistic S-N curves based on Maximum Likelihood Estimate (MLE). Fractographic studies indicated that fatigue cracks in most specimens initiate from oxide films located at or very close to specimen surface. The RFL model was proved to be able to accurately capture the scatter in fatigue life. The cumulative density function (CDF) of fatigue life determined by RFL fit is found to be approximately equal to the complementary value of the CDF of the near-surface fatigue initiator size.