Search Results

With the recent push for electrification, automotive engineers are constantly striving to improve efficiency and performance of vehicle concepts. Although multiple vehicle attributes affect range, the overall mass of the vehicle plays a significant role. Computational tools such as topology optimization (TO) have long been utilized in industry to reduce mass while meeting structural design constraints. Over time, TO methods have been extended from traditional single material topology optimization (SMTO) to advanced methods such as multi-material topology optimization (MMTO). These advanced computational tools provide more design freedom in the conceptual design phase to develop superior load paths not possible with SMTO. However, MMTO is limited by the assumption of perfect joining between dissimilar materials, requiring manual re-interpretation to develop manufacturable designs.

Rising gas prices and increasingly stringent vehicle emissions standards have pushed automakers to increase fuel economy. Mass reduction is the most practical method to increase fuel economy of a vehicle. New materials and CAE technology allow for lightweight automotive components to be designed and manufactured, which outperform traditional component designs. Topology optimization and other design optimization techniques are widely used by designers to create lightweight structural automotive parts. Other design optimization techniques include free-size, gauge, and size optimization. These optimization techniques are typically used in sequence or independently during the design process. Performing various types of design optimization simultaneously is only practical in certain cases, where different parts of the structure have different manufacturing constraints.

Automakers are under constant pressure to improve fuel economy and vehicle range to achieve a competitive advantage within the industry and meet government regulations. Reducing the overall weight of a vehicle contributes significantly to achieving this goal. Topology optimization (TO) has been identified within industry as a leading method to reduce weight on both a component and assembly level. With this tool, components can be redesigned to maintain structural performance requirements while also providing significant weight savings. On an assembly level, TO can be used to determine optimal loadpaths within large structures such as frames or bodies. These loadpaths can be interpreted to determine the locations of different components within the structure. To support the development of lightweight vehicle design, this paper presents a revised methodology and application of multi-joint topology optimization (MJTO).

Topology optimization (TO) represents an invaluable instrument for the structural design of components, with extensive use in numerous industries including automotive and aerospace. TO allows designers to generate lightweight, non-intuitive solutions that often improve overall system performance. Utilization of multiple materials within TO expands its range of applications, granting additional freedom and structural performance to designers. Often, use of multiple materials in TO results in material placement that may not have been previously identified as optimal, providing designers with the ability to produce novel high performance systems. As numerous modern engineering materials possess anisotropic properties, a logical extension of multi-material TO is to include provisions for anisotropic materials. Herein lies the focus of this work.

Evolving fuel efficiency and emissions standards, along with consumer demand for performance, are strong pressures for light-weighting of performance oriented motorcycles. The field of topology optimization (TO), with the extension of multi-material topology optimization (MMTO) provide manufacturers with advanced structural light-weighting methodology. TO methodology has been adopted in many industries, including automotive where light-weighting assists in meeting efficiency regulations. The development of process specific manufacturing constraints within MMTO is a critical step in increasing adoption within industries dealing with manufacturing cost restrictions. This capability can decrease design complexity, lowering manufacturing costs of optimization solutions. A conventional all-aluminum perimeter style motorcycle chassis is analyzed to develop baseline compliance (total strain energy) metrics.

As automakers continue to develop new lightweight vehicles, the application of multi-material parts, assemblies and systems is needed to enhance overall performance and safety of new and emerging architectures. To achieve these goals conventional material selection and design strategies may be employed, such as standard material performance indices or full-combinatorial substitution studies. While these detailed processes exist, they often succeed at only suggesting one material per component, and cannot consider a clean-slate design; here, multi-material topology optimization (MMTO) is suggested as an effective computational tool for performing large-scale combined multi-material selection and design. Unlike previous manual methods, MMTO provides an efficient method for simultaneously determining material existence and distribution within a predefined design domain from a library of material options.

The automotive industry is facing significant challenges for next-generation vehicle design as fuel economy regulations and tailpipe emission standards continue to strive for greater efficiency. In order to ensure vehicle design reaches these sustainability targets, lightweighting through multi-material design and topology optimization (TO) has been suggested as the leading method to reduce weight from conventional component and small assembly structures. More effective tools, techniques, and methodologies are now required to advance the development of multi-phase optimization tools beyond current commercial capability, and help automotive designers achieve critical efficiency improvements without sacrificing performance. Presented here is a unique tool description and practical application of multi-material topology optimization (MMTO), a direct extension of the classical single-material problem statement (SMTO).