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This paper reports a study undertaken by the Crash Safety Working Group (CSWG) of the United States Council for Automotive Research (USCAR) to determine generic acceleration pulses for testing and evaluating advanced batteries subjected to inertial loading for application in electric passenger vehicles. These pulses were based on characterizing vehicle acceleration time histories from standard laboratory vehicle crash tests. Crash tested passenger vehicles in the United States vehicle fleet of the model years 2005-2009 were used in this study. Crash test data, in terms of acceleration time histories, were collected from various crash modes conducted by the National Highway Traffic Safety Administration (NHTSA) during their New Car Assessment Program (NCAP) and Federal Motor Vehicle Safety Standards (FMVSS) evaluations, and the Insurance Institute for Highway Safety (IIHS).

This paper reports a 2010 study undertaken to determine generic acceleration pulses for testing and evaluating advanced batteries for application in electric passenger vehicles. These were based on characterizing vehicle acceleration time histories from standard laboratory vehicle crash tests. Crash tested passenger vehicles in the United States vehicle fleet of the model years 2005-2009 were used. The crash test data were gathered from the following test modes and sources: 1 Frontal rigid flat barrier test at 35 mph (NHTSA NCAP) 2 Frontal 40% offset deformable barrier test at 40 mph (IIHS) 3 Side moving deformable barrier test at 38 mph (NHTSA side NCAP) 4 Side oblique pole test at 20 mph (US FMVSS 214/NHTSA side NCAP) 5 Rear 70% offset moving deformable barrier impact at 50 mph (US FMVSS 301). The accelerometers used were from locations in the vehicle where deformation is minor or non-existent, so that the acceleration represents the “rigid-body” motion of the vehicle.

In this article, the authors illustrate the benefits of axiomatic design (AD) for robust optimization and how to integrate axiomatic design into a total robust design process. Similar to traditional robust design, the purpose of axiomatic design is to improve the probability of a design in meeting its functional targets at early concept generation stage. However, axiomatic design is not a standalone method or tool and it needs to be integrated with other tools to be effective in a total robust development process. A total robust development process includes: system design, parameter design, tolerance design, and tolerance specifications [1]. The authors developed a step-by-step procedure for axiomatic design practices in industrial applications for consistent and efficient deliverables. The authors also integrated axiomatic design with the CAD/CAE/statistical/visualization tools and methods to enhance the efficiency of a total robust development process.

In the automotive industry, a lot of attention has been paid to the effort required for opening/closing the doors, and for a good reason. The door closing and opening effort creates an impression in the customer’s mind about the engineering and quality of the vehicle even before he or she enters it. Although this seems trivial compared to the complexity of the rest of the automobile, effective engineering of the door opening/closing effort is challenging due to the interaction of several design parameters. Some of the best practices focus on satisfying targets for the energy required shutting the door from a small open position (around 10 degrees). However this practice ignores the complete closing/opening motion of the door from a full open position.

In the automotive industry, a lot of attention has been paid to the effort required for opening/closing the doors, and for a good reason. The door closing and opening effort creates an impression in the customer's mind about the engineering and quality of the vehicle even before he or she steps into it. Although this is such an important issue, the precise quantification of what constitutes a good performance target for the door opening/closing effort, has remained somewhat elusive. Thumb rules and best practices abound in the automotive industry. Some of the rules and best practices have focused on setting certain targets for the energy required to shut the door from a small open position (around 10-15 degrees). This target can be misleading. The purpose of this paper is to present an ADAMS® simulation model that includes all the different components of the door design.