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This paper presents the design and manufacture a sandwich structure bumper beam that could withstand at least the same load required to have plastic deformation in a 2002 Jeep Wrangler bumper beam at a lower weight. The dimensions from a bumper beam were scaled down in order to match the limiting length of the sandwich structure specimens. Theoretical optimization calculations were conducted in order to find the optimal dimensions and face thicknesses for the hybrid structures. Sandwich panels were based on Glass Fiber Reinforced Polypropylene (Twintex) and an Aluminum foam core (Alporas). Three point bending tests were performed on the sandwich structures. The resulting failure modes were revealed and found to be in agreement with those offered by the analytical predictions.

Fuel cell based powertrains are considered as potential candidates for future vehicles. Modeling of vehicle powertrains, using a combination of components and energy storage media, are widely used to predict vehicle performances under different duty cycles. This paper deals with performance analysis of a light-duty vehicle comprised of a PEM fuel cell stack, in combination with different energy storage systems using Powertrain Simulation Analysis Toolkit (PSAT). The performance of the stack was characterized by experimental data on a smaller PEM stack and was used in the simulation. The stack data was collected at controlled loading and thermal parameters. Three energy storage systems are considered in the analysis: nickel metal hydride battery storage, lithium-ion battery storage and ultra capacitor energy storage. The simulation results were analyzed for comparative evaluations and to optimize the performance of the fuel cell powertrain configurations.

This paper presents results of a study conducted to compare driving behavior and performance of drivers in two different fixed-base driving simulators (namely, FAAC and STI) while performing a same set of distracting tasks under geometrically similar freeway and traffic conditions. The FAAC simulator had a wider three-screen road view with steering feedback as compared to the STI simulator which had a single screen and narrower road view and had no steering feedback. Twenty four subjects (12 younger and 12 mature) drove each simulator and were asked to perform a set of nine different tasks involving different distracting elements such as, using a cell phone, operating the car radio, retrieving and selecting a map from map pocket in the driver's door, collecting coins to pay toll, etc.

This paper describes the design and application of a business simulation to help train employees about the new business model and culture that for an automotive supplier company that designs connected vehicle and other advanced electronic products for the automotive industry. The simulation, called SIM-i-TRI, is a three to four day collaborative learning activity that simulates the executive, administrative, engineering, manufacturing, and marketing functions in three divisions of a manufacturer that supplies parts and systems to customers in industries similar to the automotive industry. It was originally designed to support the new employee orientation at the Tier 1 supplier and to provide the participants a safe environment to practice the lessons from the orientation. The simulation has been used several times a month in the US, England, and Germany for over four years.

The automotive industry is expected to accelerate the transition to revolutionary products, rapid changes in technology and increasing technological sophistication. This will require engineers to advance their knowledge, connect and integrate different areas of knowledge and be skilled in synthesis. In addition, they must learn to work in cross-disciplinary teams and adopt a systems approach. The College of Engineering and Computer Science (CECS) at the University of Michigan-Dearborn (UM-Dearborn) responded by creating interdisciplinary MS and Ph.D. programs in automotive systems engineering (ASE) and augmenting them with hands-on research. Students at the undergraduate level can also engage in numerous ASE activities. UM-Dearborn's ASE programs offer interesting and possibly unique advantages. The first is that it offers a spectrum of ASE degree and credit programs, from the MS to the Ph.D. to continuing education.

Although computer models for vehicle and sub-system performance simulations have been developed and used extensively in the past several decades, there is currently a need to enhance the overall availability of these types of tools. Increasing demands on vehicle performance targets have intensified the need to obtain rapid feedback on the effects of vehicle modifications throughout the entire development cycle. At the same time, evolution of the PC and development of Web-based applications have contributed to the availability, accessibility, and user-friendliness of sophisticated computer analysis. Web engineering is an ideal approach in supporting globalization and is a cost-effective design-analysis integration business strategy. There is little doubt that this new approach will have positive impacts on product cost, quality, and development cycle time. This paper will show how Microsoft Excel and the Web can be powerful and effective tools in the development process.

This paper begins with a baseline multi-objective optimization problem for the lithium-ion battery cell. Maximizing the energy per unit separator area and minimizing the mass per unit separator area are considered as the objectives when the thickness and the porosity of the positive electrode are chosen as design variables in the baseline problem. By employing a reaction zone model of a Graphite/Iron Phosphate Lithium-ion Cell and the Genetic Algorithm, it is shown the shape of the Pareto optimal front for the formulated optimization takes a convex form. The identified shape of the Pareto optimal front is expected to guide Design of Experiments (DOE) and product design. Compared with the conventional studies whose optimizations are based on a single objective of maximizing the specific energy, the proposed multi-objective optimization approach offers more flexibility to the product designers when trade-off between conflicting objectives is required.

Most of the present electric vehicle (EV) on-board chargers utilize a conventional design, i.e., a boost-type Power Factor Correction (PFC) controller followed by an isolated DC/DC converter. Such design usually yields a ~94% wall-to-battery efficiency and 2~3kW/L power density at most, which makes a high-power charger, e.g., 20kW module difficult to fit in the vehicle. As described in this paper, first, an E-mode GaN HEMT based 7.2kW single-phase charger was built. Connecting three such modules to the three-phase grid allows a three-phase >20kW charger to be built, which compared to the conventional three-phase charger, saves the bulky DC-bus capacitor by using the indirect matrix converter topology. To push the efficiency and power density to the limit, comprehensive optimization is processed to optimize the single-phase module through incorporating the GaN HEMT switching performance and securing its zero-voltage switching.

Recent stringent government regulations on emission control and fuel economy drive the vehicles and their associated components and systems to the direction of lighter weight. However, the achieved lightweight must not be obtained by sacrificing other important performance requirements such as manufacturability, strength, durability, reliability, safety, noise, vibration and harshness (NVH). Additionally, cost is always a dominating factor in the lightweight design of automotive products. Therefore, a successful lightweight design can only be accomplished by better understanding the performance requirements, the potentials and limitations of the designed products, and by balancing many conflicting design parameters. The combined knowledge-based design optimization procedures and, inevitably, some trial-and-error design iterations are the practical approaches that should be adopted in the lightweight design for the automotive applications.

Nowadays, the automotive industry is experiencing the advent of unprecedented applications with connected devices, such as identifying safe users for insurance companies or assessing vehicle health. To enable such applications, driving behavior data are collected from vehicles and provided to third parties (e.g., insurance firms, car sharing businesses, healthcare providers). In the new wave of IoT (Internet of Things), driving statistics and users’ data generated from wearable devices can be exploited to better assess driving behaviors and construct driver models. We propose a framework for securely collecting data from multiple sources (e.g., vehicles and brought-in devices) and integrating them in the cloud to enable next-generation services with guaranteed user privacy protection.

Vehicle roll dynamics is strongly influenced by suspension properties such as roll center height, roll steer and roll camber. In this paper, the effects of suspension properties on vehicle roll response has been investigated using a multi-body vehicle dynamics program. A full vehicle model equipped with front MacPherson and rear multilink suspensions has been used for the study. Roll dynamics of the vehicle were evaluated by performing fixed timing fishhook maneuver in the simulation. Variations of vehicle roll response due to changes in the suspension properties were assessed by quantitatively analyzing the vehicle response through simulation. Critical suspension design parameters for vehicle roll dynamics were identified and adjusted to improve roll stability of the vehicle model with passive suspension. Design of Experiments has been used for identifying critical hardpoints affecting the suspension parameters and optimization techniques were employed for parameter optimization.

In this paper, a new algorithm, named Nonlinear Optimization Method (NOM) has been mathematically and computationally developed for several geometric elements. The initial condition of the NOM is obtained by LSM, then the minimum zone is optimized in accordance with tolerancing principles in ANSI Y14.5.1M. The results are verified to be the Minimum Zone Evaluation (MZE) for the inspected geometric features. The algorithm, together with its computational realization programs, are proved to be considerably reliable and robust for practical applications.

This paper presents a design and development approach for automotive bucket seat frame using a parametric modeling and a finite element analysis methodology. This approach is expected to help build a lightweight seat structure quickly and efficiently. This approach is general, and it can be applied in designing and developing any mechanical structural component. The design process involves, first parametric modeling of the front bucket seat frame using Pro E. This CAD model was then optimized using optimization software called Optistruct, for two cases of load case and boundary condition. The optimized design was then tested for FMVSS seat requirements using LS-DYNA. The dynamic nature of the design approach helps in changing design parameters during different stages of the design process, until the seat structure satisfies the design criteria and the strength requirements. The construction and testing of this design and the design model are still under progress.

With recent advances in microprocessors and data storage technologies, vehicle users can now bring or access large amounts of data in vehicles for purposes such as communication (e.g. e-mail, phone books), entertainment (e.g. music and video files), browsing and searching for information (e.g. on-board computers and internet). The challenge for the vehicle designer is how to design data displays and retrieval methods to allow data search and manipulation tasks by managing driver workload at safe acceptable levels. This paper presents a data retrieval menu system developed to assess levels of screens (depth of menu) that may be needed to select required information when a vehicle is equipped with the capability to access audio files, cell phone, PDA, e-mail and “On-star” type functions.

This paper presents results of a research project conducted to develop a methodology and to refine the specifications of a small, low mass, low cost vehicle being developed at the University of Michigan-Dearborn. The challenge was to assure that the design would meet the needs and expectations of customers in three different countries, namely, China, India and the United States. U.S, Chinese and Indian students studying on the university campus represented customers from their respective countries for our surveys and provided us with the necessary data on: 1) Importance of various vehicle level attributes to the entry level small car customer, 2) Preferences to various features, and 3) Direction magnitude estimation on parameters to size the vehicle for each of the three markets.

This paper discusses the evolution of graduate education in manufacturing engineering and the curriculum needed to educate manufacturing engineers in the automotive industry. This paper examines the master's and doctoral curriculum in manufacturing engineering at the University of Michigan-Dearborn. Finally, it proposes future direction for graduate education in manufacturing that will be needed for the automotive industry of the future.

This study presents a methodology for comparative analysis of seat and suspension parameters on a system level to achieve minimum occupant head displacement and acceleration, thereby improving occupant ride comfort. A lumped-parameter full-vehicle ride model with seat structures, seat cushions and five occupants has been used. Two different vehicle masses are considered. A low amplitude pulse signal is provided as the road disturbance input. The peak vertical displacement and acceleration of the occupant’s head due to the road disturbance are determined and used as measures of ride comfort. Using a design of experiments approach, the most critical seat cushion, seat structure and suspension parameters and their interactions affecting the occupant head displacement and acceleration are determined. An optimum combination of parameters to achieve minimum peak vertical displacement and acceleration of the occupant’s head is identified using a response surface methodology.

As intelligent automated vehicle technologies evolve, there is a greater need to understand and define the role of the human user, whether completely hands-off (L5) or partly hands-on. At all levels of automation, the human occupant may feel anxious or ill-at-ease. This may reflect as higher stress/workload. The study in this paper further refines how perceived workload may be determined based on occupant physiological measures. Because of great variation in individual personalities, age, driving experiences, gender, etc., a generic model applicable to all could not be developed. Rather, individual workload models that used physiological and vehicle measures were developed.

The engine operating point (EOP), which is determined by the engine speed and torque, is an important part of a vehicle's powertrain performance and it impacts FC, available propulsion power, and emissions. Predicting instantaneous EOP in real-time subject to dynamic driver behaviour and environmental conditions is a challenging problem, and in existing literature, engine performance is predicted based on internal powertrain parameters. However, a driver cannot directly influence these internal parameters in real-time and can only accommodate changes in driving behaviour and cabin temperature. It would be beneficial to develop a direct relationship between the vehicle-level parameters that a driver could influence in real-time, and the instantaneous EOP. Such a relationship can be exploited to dynamically optimize engine performance.