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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.

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.

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.